Context
It remains unclear whether patients with a suspicion of prostate cancer (PCa) and negative multiparametric magnetic resonance imaging (mpMRI) can safely obviate prostate biopsy.
Objective
To systematically review the literature assessing the negative predictive value (NPV) of mpMRI in patients with a suspicion of PCa.
Evidence acquisition
The Embase, Medline, and Cochrane databases were searched up to February 2016. Studies reporting prebiopsy mpMRI results using transrectal or transperineal biopsy as a reference standard were included. We further selected for meta-analysis studies with at least 10-core biopsies as the reference standard, mpMRI comprising at least T2-weighted and diffusion-weighted imaging, positive mpMRI defined as a Prostate Imaging Reporting Data System/Likert score of ≥3/5 or ≥4/5, and results reported at patient level for the detection of overall PCa or clinically significant PCa (csPCa) defined as Gleason ≥7 cancer.
Evidence synthesis
A total of 48 studies (9613 patients) were eligible for inclusion. At patient level, the median prevalence was 50.4% (interquartile range [IQR], 36.4–57.7%) for overall cancer and 32.9% (IQR, 28.1–37.2%) for csPCa. The median mpMRI NPV was 82.4% (IQR, 69.0–92.4%) for overall cancer and 88.1% (IQR, 85.7–92.3) for csPCa. NPV significantly decreased when cancer prevalence increased, for overall cancer ( r = –0.64, p < 0.0001) and csPCa ( r = –0.75, p = 0.032). Eight studies fulfilled the inclusion criteria for meta-analysis. Seven reported results for overall PCa. When the overall PCa prevalence increased from 30% to 60%, the combined NPV estimates decreased from 88% (95% confidence interval [95% CI], 77–99%) to 67% (95% CI, 56–79%) for a cut-off score of 3/5. Only one study selected for meta-analysis reported results for Gleason ≥7 cancers, with a positive biopsy rate of 29.3%. The corresponding NPV for a cut-off score of ≥3/5 was 87.9%.
Conclusions
The NPV of mpMRI varied greatly depending on study design, cancer prevalence, and definitions of positive mpMRI and csPCa. As cancer prevalence was highly variable among series, risk stratification of patients should be the initial step before considering prebiopsy mpMRI and defining those in whom biopsy may be omitted when the mpMRI is negative.
Patient summary
This systematic review examined if multiparametric magnetic resonance imaging (MRI) scan can be used to reliably predict the absence of prostate cancer in patients suspected of having prostate cancer, thereby avoiding a prostate biopsy. The results suggest that whilst it is a promising tool, it is not accurate enough to replace prostate biopsy in such patients, mainly because its accuracy is variable and influenced by the prostate cancer risk. However, its performance can be enhanced if there were more accurate ways of determining the risk of having prostate cancer. When such tools are available, it should be possible to use an MRI scan to avoid biopsy in patients at a low risk of prostate cancer.
A correlation with radical prostatectomy specimens has demonstrated that multiparametric magnetic resonance imaging (mpMRI) has excellent sensitivity in detecting prostate cancer (PCa) with a Gleason score of ≥7 1 2 3 . As a result, prostate mpMRI is increasingly used in patients with a suspicion of PCa to localise abnormal areas before biopsy. A large body of literature has shown that targeted biopsies of suspicious lesions seen on mpMRI (TBx) improved the detection of clinically significant PCa (csPCa), at least in the repeat biopsy setting 4 5 6 . As a result, it is now recommended that an mpMRI is performed before repeat biopsy to allow TBx of suspicious lesions in addition to standard biopsies [7] .
Some authors have recently suggested that, besides improving csPCa detection, mpMRI could also be used as a triage test so that patients with negative mpMRI findings could obviate biopsy. Such a strategy remains highly controversial [8] and depends upon the negative predictive value (NPV) of mpMRI. Therefore, the European Association of Urology Prostate Cancer Guidelines Panel undertook this systematic review and meta-analysis to assess the NPV of mpMRI in patients with a suspicion of PCa and, thus, its potential role in eliminating unnecessary prostate biopsy.
Our primary aim was to systematically evaluate the performance of negative prebiopsy prostate mpMRI in predicting a negative biopsy result for overall PCa and csPCa in biopsy-naïve men and in men with previously negative biopsies. A further objective was to explore and define factors that may contribute to relevant thresholds in order to provide guidance for future studies.
The review was performed according to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) statement [9] . The review protocol was published in PROSPERO database ( http://www.crd.york.ac.uk/PROSPERO; registration number CRD42015021929). Databases searched included the Embase and OVID Medline databases, the Cochrane database of systematic reviews, and the Cochrane Central Register for Clinical Trials, covering from January 1, 2000 to February 13, 2016. Systematic or standard prostate biopsies were used as reference standards, with positive or negative cases of PCa being determined by histopathological examination. The detailed search strategy is presented in Supplement 1.
Included studies focused on men who were assessed for suspected PCa by mpMRI before undergoing prostate biopsy. Studies enrolling both biopsy-naïve men and men who had undergone previous negative biopsies were included. Prebiopsy prostate mpMRI was considered the index test and comprised T2-weighted imaging (T2WI) and at least one functional imaging technique (diffusion-weighted imaging [DWI], dynamic contrast-enhanced imaging [DCEI], or magnetic resonance spectroscopic imaging [MRSI]). For inclusion, studies had to report on false negatives and true negatives, in order to calculate NPV (ie, results of systematic/standard prostate biopsies when the mpMRI was negative). When available, false positive and true positive findings were also noted to calculate the positive predictive value (PPV) and the cancer prevalence. There was restriction neither on the biopsy technique (transrectal or transperineal) nor on the number of biopsy cores. Studies using radical prostatectomy specimens as reference standards were excluded, as were studies evaluating men with histologically proven PCa. Studies with less than 50 participants were excluded. No language restrictions were applied.
Two reviewers (P.C.M. and T.V.D.B.) independently screened all abstracts and full-text articles for eligibility. Disagreement was resolved by consensus or reference to an independent third party (L.M.). All screening was performed using a predefined eligibility form.
Using a data extraction form developed a priori, the same two reviewers independently extracted data concerning study methodology, patient characteristics, technical characteristics of the MR scanners, mpMRI protocol, mpMRI scoring system, definition of positive mpMRI, biopsy protocol, and definition of csPCa. Any discrepancies concerning data extraction were resolved by consensus or reference to an independent arbiter (O.R. or T.B.L.).
To assess the risk of bias (RoB), all included reports were reviewed using the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool for diagnostic accuracy studies [10] .
Outcome data regarding false negative and true negative values of mpMRI before prostate biopsy were recorded as reported by authors. When not available, data were indirectly derived from specificity, sensitivity, and prevalence values reported by authors using an online Bayesian statistics calculator ( http://www.medcalc.com/bayes.html ). Descriptive statistics were used to summarise baseline characteristics and outcomes, including median and interquartile range (IQR) for estimates of NPV across studies. A correlation between mpMRI NPV and a positive biopsy rate was established using the Pearson's correlation coefficient.
A meta-analysis was undertaken to calculate pooled NPV and PPV. To ensure appropriate clinical homogeneity of the studies included in the meta-analysis, we selected only the studies enrolling biopsy-naïve patients and/or patients with a history of negative biopsy, and fulfilling the following criteria that were defined a priori: (1) reference standard consisting of prostate biopsy with at least 10 samples on all patients; (2) mpMRI protocol comprising at least T2WI and DWI; (3) mpMRI results presented as a five-level score, using a subjective Likert scale or the Prostate Imaging Reporting Data System (PI-RADS) score [11] ; (4) definition of positive mpMRI as a score ≥3/5 or ≥4/5; and (5) results reported on a per patient basis. In addition, only studies defining csPCa as Gleason ≥7 cancers were selected for the meta-analysis assessing the mpMRI NPV for csPCa. A bivariate random-effects approach was employed using the Midas package in Stata 12 (StataCorp LP, College Station, TX, USA). Since the NPV decreases and the PPV increases as the prevalence increases, post-test probability estimates of NPV and PPV were reported for the given values of the prevalence based on Bayes’ theorem.
For other studies not included in the meta-analysis based on the criteria described above, a narrative synthesis of the data was performed. To explore and define clinical heterogeneity, subgroups were analysed at patient level based on the following variables: biopsy-naïve versus previous negative biopsy; patients with positive versus negative digital rectal examination (DRE); mpMRI performed with an endorectal versus without an endorectal coil; transrectal ultrasound (TRUS) versus template transperineal (TTP) biopsy approach; and ≤16 cores versus >16 cores as the reference standard. Studies reporting mpMRI NPV for patients with a prostate-specific antigen (PSA) level of ≤10 ng/ml were also reported separately.
The study selection process is depicted in the PRISMA flow diagram ( Fig. 1 ). A total of 2980 abstracts were retrieved. After abstract screening and removal of duplicates, 240 articles were eligible for full text screening, of which 48 studies were eligible for inclusion 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 .
Out of the 48 included studies, 42 were single-centre and six were multicentre studies. Thirty-four studies were prospective and six were retrospective, whilst the design of the rest was unclear. RoB assessment using QUADAS-2 was performed for each of the individual studies ( Fig. 2 A and B). Overall, the RoB was highly heterogeneous across studies for all criteria, except for the reference standard domain, in which RoB was low in most studies.
The 48 studies comprised a total of 9613 men who underwent prostate mpMRI followed by biopsy. The study and patient baseline characteristics are presented in Table 1 . The patient population consisted of biopsy-naive men in nine studies, men with at least one previous negative biopsy in 16 studies, and both biopsy-naïve men and men with a history of previous negative biopsy in nine studies. In 14 studies, the biopsy history of the patients was unclear.
Study | Study design | Period | Population | Pt Nb | Mean/median* age (yr) | Mean/median* PSA (ng/ml) | Mean/median* prostate volume (cm 3 ) | Magnetic field strength | MR pulse sequences | Endorectal coil | MR score | Definition of positive MRI | Reference standard |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Hauth (2015) [25] | Prospective | 2011–2013 | FB | 94 | 64 (43–83) | 9 (3–31) | 51 (17–140) | 1.5 T | T2WI/DWI/DCEI/MRSI | No | PI-RADS v1 | ≥3 | 11–13-core TRUS SBx + TBx |
Lamb (2015) [36] | Retrospective | 2013–2013 | FB & PNB | 173 | NR | NR | NR | 1.5 T | T2WI/DWI | NR | NR | NR | 12-core TRUS SBx |
Brock (2015) [15] | Prospective | 2013–2014 | PNB | 168 | 64* (IQR 59–70) | 9.2* (IQR 6.7–13.4) | 55.4* (IQR 42–80) | 3 T | T2WI/DWI/DCEI | No | PI-RADS v1 | NR | 12/24-core TRUS SBx + TBx |
Grenabo Bergdahl (2016) [22] | Prospective | 2013–2014 | FB & PNB | 83 | 69.3* (IQR 69–69.6) | 1.6* (IQR 0.9–2.7) | NR | 3 T | T2WI/DWI/DCEI/MRSI | No | PI-RADS v1 | ≥3 | 10-core TRUS SBx + TBx |
Wang (2015) [58] | Prospective | 2002–2009 | FB & PNB | 586 | 70 (26–91) | 11.11* (0.02–9794) | NR | 1.5 T | T2WI/DWI/DCEI/MRSI | Yes | PI-RADS v1 | ≥3 | TRUS SBx |
Pepe (2015) [41] | Prospective | 2011–2014 | PNB | 100 | 64* | 8.6* (4.2–10) | NR | 3 T | T2WI/DWI/DCEI/MRSI | No | PI-RADS v1 | ≥4 | TPBx + TBx |
Panebianco (2015) [39] | Prospective | 2011–2014 | FB (61.62%) & PNB (38.34%) | 925 (1140 total cohort) |
NR | NR | NR | 3 T | T2WI/DWI/DCEI | Yes | PI-RADS v1 | NR | 14-core TRUS SBx; 45-core sat TPBx + TBx |
Radtke (2015) [46] | Prospective | 2013–2013 | FB (63.3%) & PNB (36.7%) | 294 | 64* (60–71) | 7.3 (6.0) | 47 (37.5) | 3 T | T2WI/DWI/DCEI | No | PI-RADS v1 | PI-RADS ≥2; PI-RADS ≥3; PI-RADS ≥4; PI-RADS = 5; |
24-core TPBx + TBx |
Itatani (2014) [27] | Retrospective | 2004–2007 | NR | 193 | 68.9 (8.4); 70* (47–89) | 11.8 (15.9); 7.9* (1.22–159) | NR | 1.5 T | T2WI/DWI/DCEI | No | 1–5 scale (Likert) | ≥3 | 12–14-core TRUS SBx |
Porpiglia (2014) [44] | Prospective | 2011–2013 | PNB | 170 | 65* (60–70) | 6.9* (5.2–9.8) | 42* (36–48) | 1.5 T | T2WI/DWI/DCEI | Yes | Dichotomous | Positive: at least 2/3 MR seq. with suspicious findings | 18–24-core TRUS SBx (volume dependent) |
Thompson (2014) [56] | Prospective | 2012–2013 | FB (88%) & PNB (12%) | 150 | 62.4* (IQR 55.0–66.4) | 5.6* (IQR 4.5–7.5) | 40* (IQR 30–57) | 1.5 T (47%) & 3 T (53%) | T2WI/DWI/DCEI | No | PI-RADS v1 | ≥3 | Median of 30 TPBx (volume dependent) |
Pokorny (2014) [43] | Prospective | 2012–2013 | FB | 223 | 63* (IQR 57–68) | 5.3* (IQR 4.1–6.6) | 41* (IQR 30–59) | 3 T | T2WI/DWI/DCEI | No | PI-RADS v1 | ≥3 (primary); ≥4 |
12-core TRUS SBx + TBx |
Petrillo (2014) [42] | Prospective | 2009–2010 | NR | 136 | NR | NR | NR | 1.5 T | T2WI/DWI/MRSI | Yes | 1–5 scale (Likert) | ≥3 | 12–16-core TRUS SBx (volume + PSA dependent) |
Javali (2014) [29] | Retrospective | 2002–2011 | NR | 140 | Control: 62.4 (10.5); Study: 62.9 (12.1) | Control: 6.8 (2.3); Study: 6.87 (2.6) | Control: 44 (14.2); Study: 43 (18.4) | 1.5 T | T2WI/MRSI | Yes | Dichotomous | Cit/[Cho + Cr] < 1.2 | 6-core TRUS SBx ( n = 69), 12-core TRUS SBx ( n = 119) |
Abd-Alazeez (2014) [13] | Prospective | 2007–2011 | FB | 129 | 62* (41–82) | 5.8* (1.2–20) | 40* (16–137) | 1.5 & 3 T | T2WI/DWI/DCEI | No | PI-RADS v1 | ≥3 (primary); ≥4 |
20-core TPBx |
Abd-Alazeez (2014) [12] | Retrospective | NR | PNB | 54 | 64* (39–75) | 10* (2–23) | 53* (19–136) | 1.5 & 3 T | T2WI/DWI/DCEI | No | PI-RADS v1 | ≥3 (primary); ≥4 |
≥20-core TPBx + TBx ( n = 15) |
Matsuoka (2014) [37] | Prospective | 2007–2012 | NR | 135 | 67* (50–80) | 7.0* (2.9–19.8) | 25.4* (12.7–90.2) | 1.5 T | T2WI/DWI | No | 1–5 scale (Likert) | ≥3 | 14-core TRUS SBX |
Junker (2013) [30] | Retrospective | 2011–2013 | PNB | 73 | 62 (7.4) | 7.0* (5.1–12.9) | 45* (34–61) | 3 T | T2WI/DWI/DCEI | No | PI-RADS | PI-RADS ≥10 and ≥11 for all PCa PI-RADS ≥13 for significant PCa |
10-core TRUS SBx + TBx |
Busetto (2013) [16] | Prospective | 2010–2012 | PNB | 163 | 66.4 (5.3) | 6.8 (1.6) | NR | 3 T | T2WI/DWI/DCEI/MRSI | Yes | NR | NR | 10-core TRUS SBx + TBx |
Rais-Bahrami (2013) [47] | Prospective | 2007–2012 | NR | 583 | 61.3 (8.4) | 9.9 (13.1) | NR | 3 T | T2WI/DWI/DCEI/MRSI | Yes | 1–4 scale (Likert) | ≥2 ≥3 |
12-core TRUS SBx + TBx |
Kuru (2013) [34] | Prospective | 2010–2011 | FB (51%) & PNB (49%) | 347 | 65.3 (42–82) | 9.85 (0.5–104) | 48.7 (9–180) | 3 T | T2WI/DWI/DCEI | No | 1–3 scale (Likert) | ≥2 | 12–36-core TRUS SBx (volume dependent) + TBx |
Ferda (2013) [20] | Prospective | NR | NR | 164 | (49–74) | (4.2–123) | NR | 3 T | T2WI/DWI/DCEI/MRSI | No | NR | In house | TRUS SBx |
Ganie (2013) [21] | NR | 2007–2009 | PNB | 87 | NR | NR | NR | 1.5 T | T2WI/MRSI | Yes | MRSI Cho/Cit ratio | In house | 6 core TRUS SBx + MRI TBx |
Vinet (2013) [57] | Prospective | 2009–2011 | FB | 69 | NR | 5.2* (3.2–28) | NR | 1.5 T (35 pts) & 3 T (34 pts) | T2WI/DWI/DCEI | No | 1–5 scale (Likert) | ≥3 | 12-core TRUS SBx + TBx |
Numao (2013) [38] | Prospective | 2006–2010 | FB | 351 | 65* (59–70) | 6.3* (4.9–9.1) | 32* (24–42) | 1.5 T | T2WI/DWI/DCEI (no DCEI in 42 pts) | No | 1–5 scale (Likert) | ≥3 | 3D 26-core (12 TRUS SBx + 14 TPBx – 203 pts); 3D 14-core (6 TRUS SBx + 8 TPBx – 102 pts); TPBx 14 core (46 pts) |
Belas (2012) [14] | Prospective | 2010–2011 | FB | 71 | 66* (47–76) | 7* (4–10) | 45* (15–150) | 1.5 T | T2WI/DWI/DCEI | No | TZ: 0–4 scale PZ: 0–10 scale |
TZ: >2 PZ: >6 |
12-core TRUS SBx + TBx |
Ibrahiem (2012) [26] | Prospective | 2008–2009 | FB | 100 | 65.03 (7.13) | 26.3 (24.2) | 60.09 (28.7) | 1.5 T | T2WI/DWI | No | NR | In house | 12-core TRUS SBX |
Sciarra (2012) [51] | Prospective | 2008–2011 | PNB | 84 | 64.09 (46–76) | 7.07 (4.2–15.5) | NR | 3 T | T2WI/DWI/DCEI/MRSI | Yes | NR | NR | 10-core TRUS Bx + TBx |
Portalez (2012) [45] | Prospective | 2011 | PNB | 129 | 64.7 (47–79) | 9.6 (2.7–40) | 51.1 (12–192) | 1.5 T | T2WI/DWI/DCEI | Mixed | 1–5 scale (Likert) PI-RADS |
Likert ≥3 PI-RADS ≥9 |
10–12-core TRUS SBx + TBx |
Watanabe (2012) [59] | Prospective | 2004–2008 | NR | 1448 | 72 (7.5) | NR | NR | 1.5 T | T2WI/DWI | No | NR | ADC value ≤1.35 × 10 −3 mm 2 /s | 8-core TRUS SBx + TBx |
Tamada (2011) [54] | Retrospective | 2006–2009 | NR | 50 | 70 (40–84) | 6.84* (4.06–9.94) | NR | 1.5 T | T2WI/DWI/DCEI | No | NR | In house | 12-core TRUS SBx |
Choi (2011) [18] | NR | 2009–2010 | NR | 51 | 67.16 (56–90) | 14.16 (1.02–38.9) | 42.98 (13.8–77.3) | 3 T | T2WI/DWI | NR | NR | NR | 10–12-core TRUS SBx + TBx |
Iwazawa (2011) [28] | Retrospective | 2008–2009 | NR | 178 | 68.8 (41–86) | 20.51 (4.04–568.5) | NR | 1.5 T | T2WI/DWI/DCEI | NR | 1–4 scale (Likert) | NR | 10–12-core TRUS SBx (TBx included in SBx chart) |
Rouse (2011) [48] | Prospective | 2005–2007 | PNB | 114 | 63.6 (41–83) | 13.4 (0–228) | NR | 1.5 T | T2WI/DWI/DCEI | NR | 1–5 scale (Likert) | ≥3 | TRUS SBx |
Haffner (2011) [23] | Prospective | 2005–2009 | FB | 555 | 64* (47–83) | 6.75* (0.18–100) | 46* (15–200) | 1.5 T | T2WI/DCEI | No | 1–5 scale (Likert) | ≥3 | 10-core TRUS SBx + TBx |
Panebianco (2010) [40] | Prospective | 2007–2009 | PNB | 150 | 61.2 (46–78) | 9.42 (3.91) | 41.17 (7.47) | 1.5 T | T2WI/DCEI/MRSI | Yes | NR | In house | 10-core TRUS SBx (TBx included in SBx chart) |
Roy (2010) [49] | Not specified | 2011–2009 | FB (53%) & PNB (47%) | 103 | 63 (52–78) | 7* | NR | 3 T | T2WI/DWI/DCEI | Yes | NR | NR | 8-core TRUS SBx + TBx |
Testa (2010) [55] | Not specified | 2007 | PNB | 54 | 63.9 (52–76) | 11.4 (3–42) | 59.3 (30–150) | 1.5 T | T2WI/MRSI | Yes | 1–3 scale (Likert) | ≥2 | 12-core TRUS SBx + TBx |
Sciarra (2010) [52] | Prospective | 2007–2009 | PNB | 110 | 63.5 (49–74) | NR | NR | 1.5 T | T2WI/DCEI/MRSI | Yes | NR | In house | 10-core TRUS SBx + TBx |
Kitajima (2010) [31] | Prospective | 2008–2009 | NR | 53 | 69* (56–84) | 11.1* (4.2–112.1) | NR | 3 T | T2WI/DWI/DCEI | No | 1–5 scale (Likert) | ≥3 | 20-core TPBx |
Labanaris (2010) [35] | Prospective | 2004–2008 | PNB | 260 | NR | NR | NR | 1 T | T2WI/DWI/DCEI | Yes | Dichotomous | In house | 18-core TRUS SBx |
Kumar (2009) [32] | NR | NR | NR | 61 | 65.3 (9.3) | 16.5 (0.21–155) | NR | 1.5 T | T2WI/MRSI | Yes | NR | (Cit/(Cho + Cr) ≤ 1.2 | TRUS Bx |
Schmuecking (2009) [50] | NR | NR | FB & PNB | 67 | 68 | 11.5 | NR | 1.5 T | T2WI/DCEI | No | NR | NR | 20-core Bx |
Cheikh (2009) [17] | Retrospective | 2005–2008 | PNB | 93 | 63.2 (52–74) | 9.63 (1.6–40) | NR | 1.5 T | T2WI/DCEI | No | Dichotomous | In house | 12-core TRUS SBx + TBx |
Cirillo (2008) [19] | Prospective | 2004–2006 | PNB | 54 | 65.5 (5.2) | 10.8 (7.5) | NR | 1.5 T | T2WI/MRSI | Yes | Dichotomous | In house | 10-core TRUS SBx + TBx |
Kumar (2007) [33] | Prospective | 2003–2005 | NR | 83 | NR | NR | NR | 1.5 T | T2WI/MRSI | Yes | NR | NR | 12-core TRUS SBx + TBx |
Squillaci (2005) [53] | Prospective | 2004–2005 | NR | 65 | NR | NR | NR | 1.5 T | T2WI/DCEI/MRSI | No | 1–3 scale (Likert) | ≥2 | 10-core TRUS SBx + TBx |
Hara (2005) [24] | Prospective | 2003–2004 | FB | 90 | 67.2 (NR) | NR | NR | 1.5 T | T2WI/DCEI | No | 1–3 scale (Likert) | ≥2 = 3 |
14-core TRUS SBx |
The magnetic field strength was 1, 1.5, and 3 T in one, 28, and 15 studies, respectively. Four studies used both 1.5 and 3 T MR systems. DWI and DCEI were used in 36 and 35 studies, respectively. Nineteen studies also added MRSI. An endorectal coil was used in 18 studies. The definition of positive mpMRI varied across studies. The PI-RADS v1 score was used in 12 studies, a five-level subjective (Likert) score was used in eight studies, and one study reported data based on the two scoring systems. In-house criteria were used in 13 studies for defining positive mpMRI, and five studies used a dichotomous definition. Nine studies did not report on the criteria for positive mpMRI. No study used the PI-RADS v2 score.
Regarding the reference standard, TRUS-guided biopsies were used in 39 studies, TTP biopsies in six studies, and mixed TRUS-guided and TTP biopsies in two studies. In one study, the biopsy approach was unclear. The number of cores per biopsy procedure was ≤16 in 30 studies, >16 in nine studies, and variable among patients in three studies. For six studies, the number of biopsy cores taken was unclear.
At patient level, the median biopsy positivity rate (ie, cancer prevalence) was 50.4% (IQR, 36.4–57.7%) for overall cancer and 32.9% (IQR, 28.1–37.2%) for csPCa ( Table 2 ). The median mpMRI NPV was 82.4% (IQR, 69.0–92.4%) for overall cancer and 88.1% (IQR, 85.7–92.3) for csPCa. NPV significantly decreased when cancer prevalence increased, both for overall cancer ( r = –0.64, p < 0.0001) and csPCa ( r = –0.75, p = 0.032; Fig. 3 ). In addition, NPV was highly dependent on the definition used for csPCa, with differences of up to 21% when several definitions were used in the same dataset [12 13 38 47 48] .
Study | Overall PCa prevalence (%) | Reporting level | Multiparametric MRI performance for PCa detection | Definition of csPCa | csPCa prevalence | Multiparametric MRI performance for csPCa detection | ||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
TN | FN | TP | FP | NPV | PPV | TN | FN | TP | FP | NPV | PPV | |||||
Hauth (2015) [25] | 45.7 | Patient | 6 | 1 | 42 | 45 | 85.7% | 48.3% | Low grade: GS ≤ 6 High grade: GS ≥ 7 |
NR | NR | NR | NR | NR | NR | NR |
Lesion | 59 | 13 | 55 | 73 | 81.9% | 43% | ||||||||||
Lamb (2015) [36] | 65.9 | Patient | 23 | 22 | 92 | 36 | 51.1% | 71.9% | GS ≥ 7 | 50.9% | 31 | 14 | 71 | 57 | 68.9% | 55.5% |
Brock (2015) [15] | 42.3 | Patient | 17 | 7 | 56 | 88 | 70.8% | SBx: 38.8% TBx: 22.2% Duo: 44.4% |
Epstein: GS > 6 and/or max CCL ≥50% | 24.4% | SBx: 21 | SBx: 3 | SBx: 38 TBx: 27 duo: 47 |
SBx: 106 TBx: 117 duo: 97 |
87.5% | SBx: 26.4% TBx: 18.8% duo: 32.6% |
Grenabo Bergdahl (2016) [22] | 33.7 | Patient | 36 | 7 | 19 | 21 | 83.7% | 47.5% | Clinically insignificant PCa: T1c, PSAd < 0.15, GS < 7, ≤2 positive cores, and unilateral cancer | NR | NR | NR | NR | NR | NR | NR |
Wang (2015) [58] | 58 | Patient | 165 | 8 | 332 | 81 | 95.4% | 80.4% | NR | NR | NR | NR | NR | NR | NR | NR |
Pepe (2015) [41] | 37 | Patient | 23 | 8 | 29 | 40 | 74.2% | 42% | GS ≥ 7 or GS 6 with CCL ≥ 50% | NR | NR | NR | NR | NR | 100% | 55.8% |
Panebianco (2015) [39] | 74.7 | Patient | Group A (satBx): 104 | Group A (satBx): 43 | Group A: 186 | Group A: 22 | Group A (satBx): 70.7% | Group A: 89.4% | NR | 60% | Group A: 147 | Group A: 0 | Group A: 183 | Group A: 25 | Group A: 100% | Group A: 88% |
Group B (TRUSGB NR TRUS G satBx): 93 | Group B (TRUSGB NR TRUS G satBx): 37 | Group B: 417 before and 425 after satBx | Group B: 23/440 and 15/440 after satBx. | Group B (TRUSGB–TRUS G satBx): 71.5% | Group B: 94.8% before and 96.6% after satBx | 71.9% | Group B: 130 | Group B: 0 | Group B: 410 |
Group B: 30 | Group B: 100% | Group B: 93.2% | ||||
Radtke (2015) [46] | 51 | Patient | ≥2/5: 80 ≥3: 103 ≥4: 138 = 5: 142 |
≥2/5: 18 ≥3/5: 38 ≥4/5: 78 = 5/5: 126 |
≥2/5: 132 ≥3/5: 112 ≥4/5: 72 = 5/5: 24 |
≥2/5: 64 ≥3/5: 41 ≥4/5: 6 = 5/5: 2 |
≥2/5: 81.6% ≥ 3/5: 73.1% ≥ 4/5: 63.9% = 5/5: 53% |
≥2/5: 67.4% ≥ 3/5: 73.2% ≥ 4/5: 92.3% = 5/5: 92.3% |
GS ≥ 7 | 29.3% | ≥2/5: 91 ≥3/5: 124 ≥4/5: 183 = 5/5: 203 |
≥2/5: 7 ≥3/5: 17 ≥4/5: 33 = 5/5: 65 |
≥2/5: 79 ≥3/5: 69 ≥4/5: 53 = 5/5: 21 |
≥2/5: 117 ≥3/5: 84 ≥4/5: 25 = 5/5: 5 |
≥2/5: 92.2% ≥3/5: 87.9% ≥4/5: 84.7% = 5/5: 75.8% |
≥2/5: 40.3% ≥3/5: 45.1% ≥4/5: 68% = 5/5: 80.7% |
Itatani (2014) [27] | 13 | Patient | 168 | 25 | NR | NR | 87% | NR | (1) PSAd ≥ 0.1 or GP 4/5 or ≥ 3/6 pos cores; max CCL < 50% (2) PSAd ≥ 0.15 or GP 4/5 or max core length invasion < 3 mm (min 6 cores) |
NR | NR | NR | NR | NR | NR | NR |
Porpiglia (2014) [44] | 30.6 | Patient | 107 | 5 | 47 | 11 | 95.5% | 81% | NR | NR | NR | NR | NR | NR | NR | NR |
Thompson (2014) [56] | 61.3 | Patient | 35 | 16 | 76 | 23 | 68.6% | 76.7% | Moderate or high risk Moderate risk: GS 7 (GP4 >5%) and <50% of positive cores or GS 6–7 (GP4 ≤ 5%) and either ≥30% of positive cores or max core length invasion ≥8 mm High risk: GS ≥ 7 (GP4 > 5%); ≥50% + cores or GS ≥ 8 |
34% | 49 | 2 | 49 | 50 | 96% | 49.5% |
Pokorny (2014) [43] | 63.7 | Patient | ≥3/5: 56 ≥4/5: 74 |
≥3/5: 25 ≥4/5: 40 |
≥3/5: 101 ≥4/5: 86 |
≥3/5: 41 ≥4/5: 23 |
≥3/5: 69.1% ≥4/5: 64.9% |
≥3/5: 71.1% ≥4/5: 78.9% |
NR | NR | NR | NR | NR | NR | NR | NR |
Petrillo (2014) [42] | 18.4 | Patient | 56 | 4 | 21 | 55 | 93% | 28% | NR | NR | NR | NR | NR | NR | NR | NR |
Javali (2014) [29] | 16.4 | Patient | 49 | 1 | 22 | 68 | 98% | 24.4% | NR | NR | NR | NR | NR | NR | NR | NR |
Abd-Alazeez (2014) [13] | 54.7 | Lobe | ≥3/5: 33 | ≥3/5: 14 | ≥3/5: 127 | ≥3/5: 84 | ≥3/5: 70% | ≥3/5: 60% | Def 1: GS ≥ 4 + 3 and/or max CCL ≥ 6 mm Def 2: GS ≥ 3 + 4 and/or max CCL ≥ 4 mm Def 3: GS ≥ 4 + 3 Def 4: GS ≥ 3 + 4 Def 5: max CCL ≥ 6 mm Def 6: max CCL ≥ 4 mm |
Def 1: NR Def 2: 44.2% Def 3: 23.2% Def 4: 36% Def 5: 32.9% Def 6: 39.5% |
Def 1: 46 Def 2: 42 Def 3: 47 Def 4: 43 Def 5: 46 Def 6: 43 |
Def 1: 1 Def 2: 5 Def 3: 0 Def 4: 4 Def 5: 1 Def 6: 4 |
Def 1: 45 Def 2: 72 Def 3: 13 Def 4: 50 Def 5: 39 Def 6: 59 |
Def 1: 166 Def2: 139 Def 3: 198 Def 4: 161 Def 5: 172 Def 6: 152 |
Def 1: 98 Def 2: 89 Def 3: 100 Def 4: 92 Def 5: 98 Def 6: 91 |
Def 1: 21 Def 2: 34 Deg 3: 6 Def 4: 24 Def 5: 19 Def 6: 28 |
≥4/5: 87 | ≥3/5: 62 | ≥3/5: 79 | ≥3/5: 30 | ≥3/5: 58% | ≥3/5: 73% | Def 1: 140 Def 2: 124 Def 3: 148 Def 4: 133 Def 5: 141 Def 6: 131 |
Def 1: 9 Def 2: 25 Def 3: 1 Def 4: 16 Def 5: 8 Def 6: 18 |
Def 1: 37 Def 2: 52 Def 3: 12 Def 4: 38 Def 5: 32 Def 6: 45 |
Def 1: 72 Def 2: 57 Def 3: 97 Def 4: 71 Def 5: 77 Def 6: 64 |
Def 1: 94 Def 2: 83 Def 3: 99 Def 4: 89 Def 5: 95 Def 6: 88 |
Def 1: 34 Def 2: 48 Def 3: 11 Def 4: 35 Def 5: 30 Def 6: 42 |
|||||
Abd-Alazeez (2014) [12] | 47.2 | Lobe | ≥3/5: 26 | ≥3/5: 13 | ≥3/5: 38 | ≥3/5: 31 | ≥3/5: 66% | ≥3/5: 55% | Def 1: GS ≥ 4 + 3 and/or max CCL ≥ 6 mm Def 2: GS ≥ 3 + 4 and/or max CCL ≥ 4 mm Def 3: GS ≥ 4 + 3 Def 4: GS ≥ 3 + 4 Def 5: max CCL ≥ 6 mm Def 6: max CCL ≥ 4 mm |
Def 1: 18.5% Def 2: 31.5% Def 3: 4.6% Def 4: 21.3% Def 5: 16.7% Def 6: 25% |
Def 1: 37 Def 2: 31 Def 3: 39 Def 4: 36 Def 5: 37 Def 6: 32 |
Def 1: 2 Def 2: 8 Def 3: 0 Def 4: 3 Def 5: 2 Def 6: 7 |
Def 1: 18 Def 2: 26 Def 3: 5 Def 4: 20 Def 5: 16 Def 6: 20 |
Def 1: 51 Def 2: 43 Def 3: 64 Def 4: 49 Def 5: 53 Def 6: 49 |
Def 1: 95 Def 2: 79 Def 3: 100 Def 4: 92 Def 5: 95 Def 6: 82 |
Def 1: 26 Def 2: 38 Def 3: 7 Def 4: 29 Def 5: 23 Def 6: 29 |
≥4/5: 49 | ≥4/5: 25 | ≥4/5: 26 | ≥4/5: 8 | ≥4/5: 66% | ≥4/5: 76% | Def 1: 70 Def 2: 63 Def 3: 73 Def 4: 68 Def 5: 70 Def 6: 64 |
Def 1: 4 Def 2: 11 Def 3: 1 Def 4: 6 Def 5: 4 Def 6: 10 |
Def 1: 16 Def 2: 23 Def 3: 4 Def 4: 17 Def 5: 14 Def 6: 17 |
Def 1: 18; Def 2: 11 Def 3: 30 Def 4: 17 Def 5: 20 Def 6: 17 |
Def 1: 94 Def 2: 85 Def 3: 99 Def 4: 92 Def 5: 94 Def 6: 86 |
Def 1: 47 Def 2: 67 Def 3: 12 Def 4: 50 Def 5: 41 Def 6: 49 |
|||||
Matsuoka (2014) [37] | 64.8 | Lobe | 46 | 49 | 149 | 26 | 48.4% | 85.1% | NR | NR | NR | NR | NR | NR | NR | NR |
Junker (2013) [30] | 53.4 | Patient | ≥10/15: 21 ≥11/15: 28 |
≥10/15: 4 ≥11/15: 12 |
≥10/15: 35 ≥11/15: 27 |
≥10/15: 13 ≥11/15: 6 |
≥10/15: 84% ≥11/15: 70% |
≥10/15: 72.9% ≥11/15: 81.8% |
GS ≥ 4 + 3 | 13.7% | ≥13: 54 | ≥13: 2 | ≥13: 8 | ≥13: 9 | ≥13: 96.4% | ≥13: 47% |
Busetto (2013) [16] | 41.7 | Patient | 59 | 7 | 61 | 36 | 89% | 63% | NR | NR | NR | NR | NR | NR | NR | NR |
Rais-Bahrami (2013) [47] | 54.2 | Patient | ≥2/4 : 80 | ≥2/4: 275 | ≥2/4: 187 | ≥2/4: 275 | ≥2/4: 66% | ≥2/4: 59% | GS ≥ 7: GS ≥ 8 |
31.7% | NR | NR | NR | NR | GS ≥ 7: 91% GS ≥ 8: 91% |
GS ≥ 7: 38% GS ≥ 8: 18% |
≥3/4: 251 | ≥3/4: 76 | ≥3/4: 16 | ≥3/4: 76 | ≥3/4: 51% | ≥3/4: 82% | NR | NR | NR | NR | GS ≥ 7: 75% GS ≥ 8: 91% |
GS ≥ 7: 67% GS ≥ 8: 41% |
|||||
Kuru (2013) [34] | 57.6 | Patient | 80 | 14 | 67 | 186 | 85.1% | 73.5% | NR | NR | NR | NR | NR | NR | NR | NR |
Ferda (2013) [20] | 51.2 | Patient | 52 | 2 | 82 | 28 | 96.3% | 74.5% | NR | NR | NR | NR | NR | NR | NR | NR |
Ganie (2013) [21] | 74.7 | Patient | 13 | 3 | 62 | 9 | 59.1% | 95.4% | NR | NR | NR | NR | NR | NR | NR | NR |
Vinet (2013) [57] | 49.3 | Patient | ≥3/5: 11 | ≥3/5: 6 | ≥3/5: 28 | ≥3/5: 24 | ≥3/5: 64.7% | ≥3/5: 53.8% | NR | NR | NR | NR | NR | NR | NR | NR |
≥4/5: 22 | ≥4/5: 11 | ≥4/5: 23 | ≥4/5: 13 | ≥4/5: 66.7% | ≥4/5: 63.8% | NR | NR | NR | NR | NR | NR | NR | NR | |||
Numao (2013) [38] | 45 | Patient | 137 | 57 | 101 | 56 | 70.6% | 64.3% | Def 1: GS ≥4 + 3 and/or ≥20% positive cores and/or max CCL ≥5 mm Def 2: GS ≥ 3 + 4 and/or ≥20% + cores and/or max CCL ≥5 mm Def 3: GS ≥ 3 + 4 and/or ≥20% + cores |
Def 1: 33.3% Def 2:37.8% Def 3: 35.8% |
Def 1: 74 Def 2: 65 Def 3: 69 |
Def 1: 83 Def 2: 92 Def 3: 88 |
Def 1: 160 Def 2: 153 Def 3: 156 |
Def 1: 34 Def 2: 41 Def 3: 38 |
Def 1: 82.4% Def 2: 78.8% Def 3: 80.4% |
Def 1: 58.8% Def 2: 58.5% Def 3: 56% |
Belas (2012) [14] | 53.5 | Patient | 22 | 12 | 23 | 13 | 64.7% | 63.8% | NR | NR | NR | NR | NR | NR | NR | NR |
Ibrahiem (2012) [26] | 73.9 | Patient | 14 | 11 | 57 | 10 | 56% | 85.1% | NR | NR | NR | NR | NR | NR | NR | NR |
Sciarra (2012) [51] | 34.5 | Patient | 41 | 4 | 25 | 14 | 91.1% | 64.1% | NR | NR | NR | NR | NR | NR | NR | NR |
Portalez (2012) [45] | 48.1 | Lesion | Likert: 357 | Likert: 50 | Likert: 81 | Likert: 50 | Likert: 95% | Likert: 38% | Max CCL >3 mm and/or GG 4/5 | NR | NR | NR | NR | NR | NR | NR |
PI-RADS: 404 | PI-RADS: 47 | PI-RADS: 34 | PI-RADS: 47 | PI-RADS: 95% | PI-RADS: 58% | |||||||||||
Watanabe (2012) [59] | 48.1 | Patient | 485 | 73 | 624 | 266 | 86.9% | 70.1% | NR | NR | NR | NR | NR | NR | NR | NR |
Tamada (2011) [54] | 70 | Patient | 12 | 6 | 29 | 3 | 67% | 91% | NR | NR | NR | NR | NR | NR | NR | NR |
Region | 277 | 48 | 55 | 20 | 85% | 73% | ||||||||||
Choi (2011) [18] | 70.6 | Patient | 9 | 5 | 31 | 6 | 64.2% | 75.7% | NR | NR | NR | NR | NR | NR | NR | NR |
Iwazawa (2011) [28] | 40.5 | Region | 887 | 86 | 232 | 219 | 91.1% | 51.4% | NR | NR | NR | NR | NR | NR | NR | NR |
Rouse (2011) [48] | 33.7 | Sextant | 145 | 11 | 74 | 22 | 92.9% | 77.1% | GS ≥ 7: Def 1: ≥3 mm Def 2: ≥5 mm |
Def 1: 26.6% Def 2: 26.2% |
Def 1: 153 Def 2: 153 |
Def 1: 3 Def 2: 3 |
Def 1: 64 Def 1: 63 |
Def 1: 32 Def 2: 33 |
Def 1: 98.1% Def 2: 98.1% |
Def 1: 68.1% Def 2: 67% |
59.6 | Patient | 24 | 14 | 54 | 22 | 63.2% | 71.1% | Def 1: 41.2% Def 2: 36.8% |
Def 1: 30 Def 2: 31 |
Def 1: 4 Def 2: 3 |
Def 1: 43 Def 2: 39 |
Def 1: 4 Def 2: 3 |
Def 1: 88.2% Def 2: 91.2% |
Def 1: 53.8% Def 2: 48.8% |
||
Haffner (2011) [23] | 54.4 | Patient | 154 | 50 | 240 | 111 | 75.4% | 68.3% | NR | NR | NR | NR | NR | NR | NR | NR |
Panebianco (2010) [40] | 42.7 | Patient | NR | NR | NR | NR | 95.1% | 88.2% | NR | NR | NR | NR | NR | NR | NR | NR |
Roy (2010) [49] | 55.9 | Patient | NR | NR | NR | NR | 71% | 75% | NR | NR | NR | NR | NR | NR | NR | NR |
Testa (2010) [55] | 40.7 | Patient | NR | NR | NR | NR | 79.3% | 64% | NR | NR | NR | NR | NR | NR | NR | NR |
Sciarra (2010) [52] | 50 | Patient | 61 | 4 | 66 | 9 | 93.8% | 88% | NR | NR | NR | NR | NR | NR | NR | NR |
Kitajima (2010) [31] | 56.6 | Patient | 311 | 19 | 80 | 14 | 92.2% | 85.1% | NR | NR | NR | NR | NR | NR | NR | NR |
Labanaris (2010) [35] | 73.9 | Patient | 17 | 73 | 96 | 74 | 81.11% | 56.47% | NR | NR | NR | NR | NR | NR | NR | NR |
Kumar (2009) [32] | 21.7 | Patient | 39 | 3 | 10 | 8 | 92.8% | 55% | NR | NR | NR | NR | NR | NR | NR | NR |
Schmuecking (2009) [50] | NR | Lobe | NR | NR | NR | NR | 96% | 61% | NR | NR | NR | NR | NR | NR | NR | NR |
Cheikh (2009) [17] | 24.7 | Patient | 36 | 12 | 11 | 34 | 80% | 22.9% | NR | NR | NR | NR | NR | NR | NR | NR |
Cirillo (2008) [19] | 31.5 | Patient | 19 | 0 | 17 | 18 | 100% | 48.6% | NR | NR | NR | NR | NR | NR | NR | NR |
Kumar (2007) [33] | 13.3 | Patient | 39 | 0 | 11 | 33 | 100% | 25% | NR | NR | NR | NR | NR | NR | NR | NR |
Squillaci (2005) [53] | 50.8 | Patient | 29% | 8% | 25% | 3% | 89% | 80% | NR | NR | NR | NR | NR | NR | NR | NR |
Hara (2005) [24] | 41.5 | Patient | ≥2/3: 40 = 3/3: 47 |
≥2/3: 4 = 3/3: 8 |
≥2/3 30 = 3/3: 26 |
≥2/3: 8 = 3/3: 1 |
≥2/3: 90% = 3/3: 85% |
≥2/3: 78.9% = 3/3: 96.3% |
NR | NR | NR | NR | NR | NR | NR | NR |
Cancer prevalence tended to be higher and mpMRI NPV lower in the biopsy-naïve group as compared with the repeat biopsy group, in men with positive DRE as compared with men with negative DRE and when an endorectal coil was not used ( Table 3 ). There were no clear differences in the prevalence and NPV of the other analysed subgroups (TRUS-guided vs TTP biopsy, biopsy procedures with ≤16 cores vs >16 cores; Table 3 ). However, comparisons must be interpreted with care, due to the small number of studies in some subgroups. In patients with a PSA level of ≤10 ng/ml, the median NPV for overall PCa was 86.3% (IQR, 73.3–93.6%) for a median cancer prevalence of 35.4% (IQR, 27.6–42.5%).
Nb of studies | Median PCa prevalence | Median mpMRI NPV | Nb of studies | Median csPCa prevalence | Median mpMRI NPV | |
---|---|---|---|---|---|---|
Biopsy-naïve patients | 8 | 51.4% (45.5–56.7) | 69.9% (64.2–78) | 1 | 35.8% (NA) | 80.4% (NA) |
Repeat biopsy | 14 | 42% (35.1–52.6) | 82.6% (75.5–93.1) | 3 | 24.4% (19.1–32.8) | 88.2% (87.9–92.3) |
TRUS-guided biopsy | 36 | 49.7% (34.3–57.7) | 84.6% (68.6–92.8) | 4 | 28.1% (21.7–36.5) | 89.3% (82.9–92.4) |
TTP biopsy | 4 | 53.8% (47.5–57.8) | 73.6% (72–78.7) | 2 | 31.6% (30.5–32.8) | 92% (89.9–94) |
Biopsy with ≤16 cores | 28 | 48.7% (39.2–54.8) | 81.9% (66.8–89.3) | 5 | 28.1% (21.8–36.5) | 89.3% (82.9–92.4) |
Biopsy with >16 cores | 5 | 56.6% (51–61.3) | 81.1% (73.1–92.2) | 2 | 31.7% (30.5–32.8) | 92% (89.9–93.9) |
Positive DRE | 1 | 73.9% (NA) | 56% (NA) | 0 | – | – |
Negative DRE | 6 | 36% (34.6–46.8) | 82.7% (74.2–93.1) | 0 | – | – |
Endorectal coil | 17 | 41.7% (30.6–55.9) | 92.8% (79.3–95.4) | 1 | 31.7% (NA) | 91% (NA) |
No endorectal coil | 22 | 50.9% (41.7–56.1) | 77.7% (69.5–86.6) | 7 | 34% (26.9–46.1%) | 87.9% (78.2–92.1) |
Eight studies reported NPV at patient level for overall PCa and fulfilled the inclusion criteria for meta-analysis ( Table 4 ) [22 25 38 41 43 46 56 57] .
Study | Prevalence a (%) | Neg MRI (%) | NPV (%) | PPV (%) | Spe (%) | Se (%) | ||
---|---|---|---|---|---|---|---|---|
All PCa | Score ≥ 3/5 | Grenabo Bergdahl (2016) [22] | 31.3 | 66.9 | 83.7 | 47.5 | 63.2 | 73.1 |
Numao (2013) [38] | 45 | 29.4 | 70.6 | 64.3 | 71.0 | 63.9 | ||
Hauth (2015) [25] | 45.7 | 14.3 | 85.7 | 48.3 | 11.8 | 97.7 | ||
Vinet (2013) [57] | 49.3 | 24.6 | 64.7 | 53.8 | 31.4 | 82.4 | ||
Radtke (2015) [46] | 51 | 27 | 73 | 73.2 | 71.5 | 74.7 | ||
Thompson (2014) [56] | 61.3 | 31.4 | 68.6 | 76.8 | 60.3 | 82.6 | ||
Pokorny (2014) [43] | 63.7 | 30.9 | 69.1 | 82.4 | 69.1 | 82.4 | ||
Score ≥ 4/5 | Pepe (2015) [41] | 37 | 31 | 74.2 | 42 | 36.5 | 78.4% | |
Vinet (2013) [57] | 49.3 | 47.8 | 66.7 | 63.9 | 62.9 | 67.6% | ||
Radtke (2015) [46] | 51 | 73.5 | 63.9 | 92.3 | 95.8 | 48% | ||
Gleason ≥7 PCa | Score ≥ 3/5 | Radtke (2015) [46] | 29.3 | 27 | 87.9 | 45.1 | 59.6 | 80.2% |
a Prevalence of overall prostate cancers (10 first lines) or Gleason ≥7 cancers (last line).
PCa = prostate cancer; MRI = magnetic resonance imaging; Neg MRI = proportion of negative magnetic resonance imaging; NPV = negative predictive value; PPV = positive predictive value; Se = sensitivity; Spe = specificity.
Seven studies used a score of ≥3/5 for defining positive mpMRI ( Fig. 4 A and B) [22 25 38 43 46 56 57] . Fig. 4 C shows the conditional probability plot of 1 – NPV and PPV as a function of overall PCa prevalence. Table 5 shows NPV and PPV estimates for the given values of PCa prevalence.
PCaPrev | PPV | NPV |
---|---|---|
0.30 | 0.43 (0.34–0.53) | 0.88 (0.77–0.99) |
0.40 | 0.54 (0.45–0.64) | 0.82 (0.70–0.94) |
0.50 | 0.64 (0.55–0.73) | 0.76 (0.64–0.88) |
0.60 | 0.73 (0.65–0.80) | 0.67 (0.56–0.79) |
0.70 | 0.81 (0.75–0.87) | 0.57 (0.47–0.67) |
0.75 | 0.84 (0.79–0.89) | 0.51 (0.42–0.59) |
Only three studies used a score of ≥4/5 for defining positive mpMRI ( Table 4 ) [41 46 57] , and a formal meta-analysis could not be performed.
Only one study reporting NPV at patient level for Gleason ≥7 cancers met the selection criteria for inclusion in the meta-analysis. It reported NPV and PPV of 87.9% and 45.1%, respectively, for a prevalence of 29.3% ( Table 4 ) [46] .
We observed a large variability in reported NPV. Many factors, such as differences in mpMRI protocols, definition of negative mpMRI, or biopsy protocols, can explain this variability. However, two major causes of variability must be pointed out. First, the cancer prevalence was highly variable, ranging at patient level from 13% to 74.7% for overall PCa, and from 13.7% to 50.9% for csPCa. This variability was observed in both the biopsy-naïve and the repeat biopsy setting. As NPV depends on prevalence, this had a major impact on reported NPV ( Fig. 3 ). Second, the definition of csPCa was highly variable from one series to another, and differences of up to 21% could be observed in NPV when different definitions of csPCa were used in the same dataset [12 13 38 47 48] .
To account for clinical heterogeneity and to further explore the clinical relevance of the results, we carefully selected studies for inclusion in the meta-analysis based on stringent criteria. Particularly, we included only studies that: (1) had biopsy protocols with at least 10 cores, since it is no longer recommended to obtain less than 10 cores per biopsy; (2) used DWI, which is the most informative technique, at least for cancers in the peripheral zone [60] ; and (3) reported mpMRI findings using a five-level score, so that negative findings could be better defined. We accepted studies using a subjective (Likert) scale because experienced readers obtained equivalent [45 61 62] or better [63] results with the Likert score than with the PI-RADS v1 score. Owing to the large variations of NPV induced by differences in definitions of csPCa, we did not include different definitions in the meta-analysis since this would have introduced unacceptable clinical heterogeneity in the results, possibly resulting in erroneous and biased estimates. We, therefore, a priori restricted the definition of csPCa to cancers with a Gleason score of ≥7, given the low lethal potential of Gleason 6 cancers [64] and the lack of consensus among pathologists on the best method to measure biopsy core invasion length [65 66] .
In this more homogeneous group of studies, the prevalence range was still large (31.3–63.7%). As a result, we modelled the evolution of NPV (and PPV) as a function of overall PCa prevalence. Unfortunately, we could not duplicate this for csPCa since only one study reporting NPV for Gleason ≥7 cancers met the inclusion criteria for meta-analysis.
We included only studies that reported the results of systematic/standard biopsy in patients with negative mpMRI and used the systematic/standard biopsy as a reference standard. It is well known that TRUS-guided biopsy harbours both random and systematic errors, as evidenced by the high rates of positivity of immediate repeat biopsy after a first series of negative biopsies [67 68] , and as confirmed recently by the PROMIS trial [69] . Therefore, using TRUS-guided biopsy as a reference standard may have overestimated the NPV of mpMRI. However, studies using radical prostatectomy specimens as a reference standard have already reported mpMRI detection rates in relation to PCa Gleason score and volume [1] . In this review, we intended to address the more pragmatic question as to whether a negative mpMRI could predict a negative subsequent biopsy. This is an important question because if the NPV of mpMRI was sufficiently high in comparison with the reference standard of systematic/standard biopsies, then in practice a negative mpMRI result could indeed avoid the need for prostate biopsy. Therefore, studies reporting only biopsy results when the mpMRI was positive (eg, obtained through MRI-targeted, guided, or fusion biopsies with added systematic biopsies) were not included in this review.
It is now well established that mpMRI is a sensitive tool for detecting aggressive PCa 1 2 3 69] . However several reasons preclude its broad use as a triage test before biopsy.
Firstly, the population referred to prostate biopsy is not standardised. The large range of reported prevalence for overall PCa and csPCa suggests substantial heterogeneity in the way patients are selected for biopsy. Owing to this heterogeneity, we did not provide a pooled estimate for mpMRI NPV. The role of mpMRI as a triage test before prostate biopsy should be evaluated in the broader context of the selection of patients with a suspicion of (aggressive) PCa. In a recent retrospective study of 514 patients, mpMRI NPV for Gleason ≥7 cancers was 91% when the PSA density was ≤0.2 ng/ml/ml, and only 71% when the PSA density was >0.2 ng/ml/ml ( p = 0.003) [70] . In another series of 288 biopsy-naïve patients, no csPCa (Gleason score ≥7 or maximum cancer core length ≥4 mm) was found in 44 patients with a PSA density of <0.15 ng/ml/ml and a PI-RADS v2 score of <3/5 [71] . We believe that such prestratification of the risk of csPCa is an interesting way for rationalising the use of mpMRI before biopsy. Patients found at very low risk would be spared both mpMRI and biopsy. Patients at a low risk—for whom mpMRI would have an NPV high enough to be used as a triage test—could avoid biopsy in case of negative mpMRI. Patients at a higher risk would need biopsy even in case of negative mpMRI. Many tools can be used to risk stratify the population of patients referred to biopsy, ranging from simple parameters such as PSA density to more complicated risk calculators [72 73] . The impact of these tools on the NPV of prebiopsy mpMRI needs to be carefully evaluated, both in the biopsy-naïve and in the repeat biopsy setting. For the moment, it is impossible to make any recommendations on the best way to risk stratify patients before referring them for mpMRI.
Secondly, the large variability in the definition of csPCa precludes any definitive conclusion on the ability of mpMRI to rule out aggressive cancer. The issue of the most appropriate definition of csPCa on biopsy is complex, since biopsy results may accurately reflect neither tumour burden nor aggressiveness. Nonetheless, there is an urgent need to standardise the histological definition(s) of csPCa, to allow meaningful comparisons between studies.
Thirdly, the specificity of mpMRI remains moderate, and there is a substantial proportion of false positives in the lesions scored 3/5 or 4/5 [1 74 75] , even with the new PI-RADS v2 score [76] . In a series of 62 patients with 116 lesions biopsied under magnetic resonance/ultrasound fusion, the overall cancer detection rates for PI-RADS v2 scores of 3/5 and 4/5 were only 15.8% and 29.8%, respectively [77] . In theory, a triage test used to rule out a disease needs to be highly sensitive for this disease. However, if its specificity is too low, it will be clinically useless since most patients will be positive, whether they have the disease or not. Therefore, if mpMRI is to be used as a triage test in the future, there is a need to improve its specificity. This could be achieved by a continuous refinement of scores [78] . Promising results in characterising csPCa have also been reported with a quantitative analysis [79] .
Finally, all published studies were conducted in specialised centres. The broad use of mpMRI as a triage test assumes good interobserver reproducibility. Unfortunately, interobserver reproducibility of existing scoring systems remains moderate [62 63 80] even with the use of the PI-RADS v2 score [80 81] . Studies evaluating on a large scale the reproducibility of mpMRI findings between expert and nonexpert centres are currently lacking.
Three systematic reviews (including two meta-analyses) regarding the role of mpMRI in localised PCa have been published recently 4 5 6 . Crucially, all three reviews focused exclusively on the sensitivity of mpMRI-targeted, guided, or fusion biopsies in diagnosing overall PCa and csPCa, using TRUS-guided prostate biopsies as reference standards. The impact of systematic biopsies on the outcome was not addressed in any of the reviews, within either the index test or the reference standard. Our review had a totally different research question and objective, focusing on NPV of mpMRI to see if a negative mpMRI can avoid the need for a prostate biopsy. As MRI-targeted/guided/fusion biopsies are not relevant if the mpMRI was negative for cancer, it can be argued that the three reviews assessed a different index test altogether. As such, we believe that the findings of this review are novel and unique, and pave the way for further focused clinical studies.
The current study represents the first systematic review addressing the role of mpMRI as a triage test before biopsy. The review elements were developed in conjunction with a multidisciplinary panel of experts (EAU Prostate Cancer Guidelines Panel), which included a patient representative, and the review was performed robustly in accordance with recognised standards. However, it is limited by the major heterogeneity of the existing literature in patient population, study design, and definitions of positive mpMRI and csPCa. It highlighted further areas of research that could help in defining the best use of mpMRI in the early detection of aggressive PCa in the future.
Although mpMRI can detect aggressive PCa with excellent sensitivity, a definitive conclusion on its role as a triage test before prostate biopsy will be possible only when three main issues are addressed. Firstly, because NPV depends on prevalence, and because overall PCa and csPCa prevalence was highly variable in the published series, it becomes mandatory to define the optimal way to pre-evaluate the risk of csPCa in patients with a suspicion of PCa. Depending on the risk category, mpMRI could then be used to obviate biopsies or not. Secondly, there is a need for consensus definitions of csPCa on biopsy findings to allow interstudy comparisons. Thirdly, although efforts have been made to standardise mpMRI technical protocols and interpretation in the past few years [11 60 76] , there is still a crucial need to improve mpMRI specificity and inter-reader reproducibility.
This systematic review was performed under the auspices of:
The European Association of Urology Guidelines Office Board
The European Association of Urology Prostate Cancer Guideline Panel
Author contributions: Olivier Rouvière had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.
Study concept and design: Rouvière, Mottet, Cornford.
Acquisition of data: Rouvière, Moldovan, Van den Broeck, Yuan.
Analysis and interpretation of data: Rouvière, Moldovan, Van den Broeck, Lam.
Drafting of the manuscript: Rouvière, Moldovan, Van den Broeck, Lam.
Critical revision of the manuscript for important intellectual content: Bellmunt, van den Bergh, Bolla, Briers, Van den Broeck, Cornford, Cumberbatch, De Santis, Fossati, Gross, Henry, Joniau, Lam, Matveev, Moldovan, van der Poel, van der Kwast, Rouvière, Schoots, Wiegel, Mottet.
Statistical analysis: None.
Obtaining funding: None.
Administrative, technical, or material support: Yuan, Sylvester, Marconi.
Supervision: None.
Other: None.
Financial disclosures: Olivier Rouvière certifies that all conflicts of interest, including specific financial interests and relationships and affiliations relevant to the subject matter or materials discussed in the manuscript (eg, employment/affiliation, grants or funding, consultancies, honoraria, stock ownership or options, expert testimony, royalties, or patents filed, received, or pending), are the following: Bellmunt is a company consultant for Janssen, Astellas, Pierre Fabre, Genentech, Merck, Ipsen, Pfizer, Novartis, and Sanofi Aventis. He has received research support from Takeda, Novartis, and Sanofi, and received travel grants from Pfizer and Pierre Fabre. Bolla has received company speaker honoraria from Ipsen and Astellas, honoraria or consultation fees from Janssen, and fellowship and travel grants from Janssen, AstraZeneca, and Astellas. Briers has received grant and research support from Ipsen, European Association of Urology, and Bayer; is an ex officio board member for Europa UOMO; is an ethics committee and advisory group member for REQUITE; is a member patient advisory board member for PAGMI; and is a member of SCA and EMA PCWP. Cornford is a company consultant for Astellas, Ipsen, and Ferring. He receives company speaker honoraria from Astellas, Janssen, Ipsen, and Pfizer; participates in trials from Ferring; and receives fellowships and travel grants from Astellas and Janssen. De Santis is a company consultant for GlaxoSmithKline, Janssen, Bayer, Novartis, Pierre Fabre, Astellas, Amgen, Eisai Inc., ESSA, Merck, and Synthon; has received company speaker honoraria from Pfizer, Takeda, Sanofi Aventis, Shionogi, Celgene, and Teva OncoGenex; has participated in trials for Pierre Fabre, Astellas, Exelixis, Bayer, and Roche; has received fellowship and travel grants from Bayer, Novartis, Ferring, Astellas, Sanofi Aventis, and Janssen; has received grant and research support from Pierre Fabre; has received honoraria from AstraZeneca; and is associated with Amgen. Joniau is a company consultant for Astellas, Ipsen, Bayer, Sanofi, and Janssen; has received company speaker honoraria from Astellas, Amgen, Bayer, Sanofi, Janssen, and Ipsen; has participated in trials for Astellas, Janssen, and Bayer; has received fellowship and travel grants from Astellas, Amgen, Bayer, Sanofi, Janssen, Ipsen, and Pfizer; and has received grant and research support from Astellas, Bayer, and Janssen. Matveev has received company speaker honoraria from Sanofi and Astellas, has participated in trials for Astellas, Pfizer and Novartis. Lam is a company consultant for and has received company speaker honoraria from Pfizer, GSK, Astellas, and Ipsen. van der Poel is a company consultant for Intuitive Surgical, has participated in trials for Astellas and Steba Biotech, and has received grant and research support from Astellas. Rouvière is a company consultant for EDAP-TMS, Bracco, and Philips; has received company speaker honoraria from EDAP-TMS, Bracco, and Philips; and has participated in trials for EDAP-TMS and Bracco. Wiegel has received company speaker honoraria from Astellas, Takeda, Hexal, Ipsen, Janssen-Cilac, and Ferring. Mottet has received grant and research support from Takeda Pharmaceutical, Millenium, Astellas, Pierre Fabre, Sanofi, and Pasteur, and has received honoraria or consultation fees from Takeda Pharaceutical, Millenium, Jansen, Astellas, BMS, Bayer, Ipsen, Ferring, Novartis, Nuclétron, Pierre Fabre, Sanofi, and Zeneca. van den Bergh, Van den Broeck, Cumberbatch, Fossati, Gross, Henry, van der Kwast, Sylvester, Yuan, Schoots, Moldovan, and Marconi have nothing to disclose.
Funding/Support and role of the sponsor: None.
A correlation with radical prostatectomy specimens has demonstrated that multiparametric magnetic resonance imaging (mpMRI) has excellent sensitivity in detecting prostate cancer (PCa) with a Gleason score of ≥7 1 2 3 . As a result, prostate mpMRI is increasingly used in patients with a suspicion of PCa to localise abnormal areas before biopsy. A large body of literature has shown that targeted biopsies of suspicious lesions seen on mpMRI (TBx) improved the detection of clinically significant PCa (csPCa), at least in the repeat biopsy setting 4 5 6 . As a result, it is now recommended that an mpMRI is performed before repeat biopsy to allow TBx of suspicious lesions in addition to standard biopsies [7] .
Some authors have recently suggested that, besides improving csPCa detection, mpMRI could also be used as a triage test so that patients with negative mpMRI findings could obviate biopsy. Such a strategy remains highly controversial [8] and depends upon the negative predictive value (NPV) of mpMRI. Therefore, the European Association of Urology Prostate Cancer Guidelines Panel undertook this systematic review and meta-analysis to assess the NPV of mpMRI in patients with a suspicion of PCa and, thus, its potential role in eliminating unnecessary prostate biopsy.
Our primary aim was to systematically evaluate the performance of negative prebiopsy prostate mpMRI in predicting a negative biopsy result for overall PCa and csPCa in biopsy-naïve men and in men with previously negative biopsies. A further objective was to explore and define factors that may contribute to relevant thresholds in order to provide guidance for future studies.
The review was performed according to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) statement [9] . The review protocol was published in PROSPERO database ( http://www.crd.york.ac.uk/PROSPERO; registration number CRD42015021929). Databases searched included the Embase and OVID Medline databases, the Cochrane database of systematic reviews, and the Cochrane Central Register for Clinical Trials, covering from January 1, 2000 to February 13, 2016. Systematic or standard prostate biopsies were used as reference standards, with positive or negative cases of PCa being determined by histopathological examination. The detailed search strategy is presented in Supplement 1.
Included studies focused on men who were assessed for suspected PCa by mpMRI before undergoing prostate biopsy. Studies enrolling both biopsy-naïve men and men who had undergone previous negative biopsies were included. Prebiopsy prostate mpMRI was considered the index test and comprised T2-weighted imaging (T2WI) and at least one functional imaging technique (diffusion-weighted imaging [DWI], dynamic contrast-enhanced imaging [DCEI], or magnetic resonance spectroscopic imaging [MRSI]). For inclusion, studies had to report on false negatives and true negatives, in order to calculate NPV (ie, results of systematic/standard prostate biopsies when the mpMRI was negative). When available, false positive and true positive findings were also noted to calculate the positive predictive value (PPV) and the cancer prevalence. There was restriction neither on the biopsy technique (transrectal or transperineal) nor on the number of biopsy cores. Studies using radical prostatectomy specimens as reference standards were excluded, as were studies evaluating men with histologically proven PCa. Studies with less than 50 participants were excluded. No language restrictions were applied.
Two reviewers (P.C.M. and T.V.D.B.) independently screened all abstracts and full-text articles for eligibility. Disagreement was resolved by consensus or reference to an independent third party (L.M.). All screening was performed using a predefined eligibility form.
Using a data extraction form developed a priori, the same two reviewers independently extracted data concerning study methodology, patient characteristics, technical characteristics of the MR scanners, mpMRI protocol, mpMRI scoring system, definition of positive mpMRI, biopsy protocol, and definition of csPCa. Any discrepancies concerning data extraction were resolved by consensus or reference to an independent arbiter (O.R. or T.B.L.).
To assess the risk of bias (RoB), all included reports were reviewed using the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool for diagnostic accuracy studies [10] .
Outcome data regarding false negative and true negative values of mpMRI before prostate biopsy were recorded as reported by authors. When not available, data were indirectly derived from specificity, sensitivity, and prevalence values reported by authors using an online Bayesian statistics calculator ( http://www.medcalc.com/bayes.html ). Descriptive statistics were used to summarise baseline characteristics and outcomes, including median and interquartile range (IQR) for estimates of NPV across studies. A correlation between mpMRI NPV and a positive biopsy rate was established using the Pearson's correlation coefficient.
A meta-analysis was undertaken to calculate pooled NPV and PPV. To ensure appropriate clinical homogeneity of the studies included in the meta-analysis, we selected only the studies enrolling biopsy-naïve patients and/or patients with a history of negative biopsy, and fulfilling the following criteria that were defined a priori: (1) reference standard consisting of prostate biopsy with at least 10 samples on all patients; (2) mpMRI protocol comprising at least T2WI and DWI; (3) mpMRI results presented as a five-level score, using a subjective Likert scale or the Prostate Imaging Reporting Data System (PI-RADS) score [11] ; (4) definition of positive mpMRI as a score ≥3/5 or ≥4/5; and (5) results reported on a per patient basis. In addition, only studies defining csPCa as Gleason ≥7 cancers were selected for the meta-analysis assessing the mpMRI NPV for csPCa. A bivariate random-effects approach was employed using the Midas package in Stata 12 (StataCorp LP, College Station, TX, USA). Since the NPV decreases and the PPV increases as the prevalence increases, post-test probability estimates of NPV and PPV were reported for the given values of the prevalence based on Bayes’ theorem.
For other studies not included in the meta-analysis based on the criteria described above, a narrative synthesis of the data was performed. To explore and define clinical heterogeneity, subgroups were analysed at patient level based on the following variables: biopsy-naïve versus previous negative biopsy; patients with positive versus negative digital rectal examination (DRE); mpMRI performed with an endorectal versus without an endorectal coil; transrectal ultrasound (TRUS) versus template transperineal (TTP) biopsy approach; and ≤16 cores versus >16 cores as the reference standard. Studies reporting mpMRI NPV for patients with a prostate-specific antigen (PSA) level of ≤10 ng/ml were also reported separately.
The study selection process is depicted in the PRISMA flow diagram ( Fig. 1 ). A total of 2980 abstracts were retrieved. After abstract screening and removal of duplicates, 240 articles were eligible for full text screening, of which 48 studies were eligible for inclusion 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 .
Out of the 48 included studies, 42 were single-centre and six were multicentre studies. Thirty-four studies were prospective and six were retrospective, whilst the design of the rest was unclear. RoB assessment using QUADAS-2 was performed for each of the individual studies ( Fig. 2 A and B). Overall, the RoB was highly heterogeneous across studies for all criteria, except for the reference standard domain, in which RoB was low in most studies.
The 48 studies comprised a total of 9613 men who underwent prostate mpMRI followed by biopsy. The study and patient baseline characteristics are presented in Table 1 . The patient population consisted of biopsy-naive men in nine studies, men with at least one previous negative biopsy in 16 studies, and both biopsy-naïve men and men with a history of previous negative biopsy in nine studies. In 14 studies, the biopsy history of the patients was unclear.
Study | Study design | Period | Population | Pt Nb | Mean/median* age (yr) | Mean/median* PSA (ng/ml) | Mean/median* prostate volume (cm 3 ) | Magnetic field strength | MR pulse sequences | Endorectal coil | MR score | Definition of positive MRI | Reference standard |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Hauth (2015) [25] | Prospective | 2011–2013 | FB | 94 | 64 (43–83) | 9 (3–31) | 51 (17–140) | 1.5 T | T2WI/DWI/DCEI/MRSI | No | PI-RADS v1 | ≥3 | 11–13-core TRUS SBx + TBx |
Lamb (2015) [36] | Retrospective | 2013–2013 | FB & PNB | 173 | NR | NR | NR | 1.5 T | T2WI/DWI | NR | NR | NR | 12-core TRUS SBx |
Brock (2015) [15] | Prospective | 2013–2014 | PNB | 168 | 64* (IQR 59–70) | 9.2* (IQR 6.7–13.4) | 55.4* (IQR 42–80) | 3 T | T2WI/DWI/DCEI | No | PI-RADS v1 | NR | 12/24-core TRUS SBx + TBx |
Grenabo Bergdahl (2016) [22] | Prospective | 2013–2014 | FB & PNB | 83 | 69.3* (IQR 69–69.6) | 1.6* (IQR 0.9–2.7) | NR | 3 T | T2WI/DWI/DCEI/MRSI | No | PI-RADS v1 | ≥3 | 10-core TRUS SBx + TBx |
Wang (2015) [58] | Prospective | 2002–2009 | FB & PNB | 586 | 70 (26–91) | 11.11* (0.02–9794) | NR | 1.5 T | T2WI/DWI/DCEI/MRSI | Yes | PI-RADS v1 | ≥3 | TRUS SBx |
Pepe (2015) [41] | Prospective | 2011–2014 | PNB | 100 | 64* | 8.6* (4.2–10) | NR | 3 T | T2WI/DWI/DCEI/MRSI | No | PI-RADS v1 | ≥4 | TPBx + TBx |
Panebianco (2015) [39] | Prospective | 2011–2014 | FB (61.62%) & PNB (38.34%) | 925 (1140 total cohort) |
NR | NR | NR | 3 T | T2WI/DWI/DCEI | Yes | PI-RADS v1 | NR | 14-core TRUS SBx; 45-core sat TPBx + TBx |
Radtke (2015) [46] | Prospective | 2013–2013 | FB (63.3%) & PNB (36.7%) | 294 | 64* (60–71) | 7.3 (6.0) | 47 (37.5) | 3 T | T2WI/DWI/DCEI | No | PI-RADS v1 | PI-RADS ≥2; PI-RADS ≥3; PI-RADS ≥4; PI-RADS = 5; |
24-core TPBx + TBx |
Itatani (2014) [27] | Retrospective | 2004–2007 | NR | 193 | 68.9 (8.4); 70* (47–89) | 11.8 (15.9); 7.9* (1.22–159) | NR | 1.5 T | T2WI/DWI/DCEI | No | 1–5 scale (Likert) | ≥3 | 12–14-core TRUS SBx |
Porpiglia (2014) [44] | Prospective | 2011–2013 | PNB | 170 | 65* (60–70) | 6.9* (5.2–9.8) | 42* (36–48) | 1.5 T | T2WI/DWI/DCEI | Yes | Dichotomous | Positive: at least 2/3 MR seq. with suspicious findings | 18–24-core TRUS SBx (volume dependent) |
Thompson (2014) [56] | Prospective | 2012–2013 | FB (88%) & PNB (12%) | 150 | 62.4* (IQR 55.0–66.4) | 5.6* (IQR 4.5–7.5) | 40* (IQR 30–57) | 1.5 T (47%) & 3 T (53%) | T2WI/DWI/DCEI | No | PI-RADS v1 | ≥3 | Median of 30 TPBx (volume dependent) |
Pokorny (2014) [43] | Prospective | 2012–2013 | FB | 223 | 63* (IQR 57–68) | 5.3* (IQR 4.1–6.6) | 41* (IQR 30–59) | 3 T | T2WI/DWI/DCEI | No | PI-RADS v1 | ≥3 (primary); ≥4 |
12-core TRUS SBx + TBx |
Petrillo (2014) [42] | Prospective | 2009–2010 | NR | 136 | NR | NR | NR | 1.5 T | T2WI/DWI/MRSI | Yes | 1–5 scale (Likert) | ≥3 | 12–16-core TRUS SBx (volume + PSA dependent) |
Javali (2014) [29] | Retrospective | 2002–2011 | NR | 140 | Control: 62.4 (10.5); Study: 62.9 (12.1) | Control: 6.8 (2.3); Study: 6.87 (2.6) | Control: 44 (14.2); Study: 43 (18.4) | 1.5 T | T2WI/MRSI | Yes | Dichotomous | Cit/[Cho + Cr] < 1.2 | 6-core TRUS SBx ( n = 69), 12-core TRUS SBx ( n = 119) |
Abd-Alazeez (2014) [13] | Prospective | 2007–2011 | FB | 129 | 62* (41–82) | 5.8* (1.2–20) | 40* (16–137) | 1.5 & 3 T | T2WI/DWI/DCEI | No | PI-RADS v1 | ≥3 (primary); ≥4 |
20-core TPBx |
Abd-Alazeez (2014) [12] | Retrospective | NR | PNB | 54 | 64* (39–75) | 10* (2–23) | 53* (19–136) | 1.5 & 3 T | T2WI/DWI/DCEI | No | PI-RADS v1 | ≥3 (primary); ≥4 |
≥20-core TPBx + TBx ( n = 15) |
Matsuoka (2014) [37] | Prospective | 2007–2012 | NR | 135 | 67* (50–80) | 7.0* (2.9–19.8) | 25.4* (12.7–90.2) | 1.5 T | T2WI/DWI | No | 1–5 scale (Likert) | ≥3 | 14-core TRUS SBX |
Junker (2013) [30] | Retrospective | 2011–2013 | PNB | 73 | 62 (7.4) | 7.0* (5.1–12.9) | 45* (34–61) | 3 T | T2WI/DWI/DCEI | No | PI-RADS | PI-RADS ≥10 and ≥11 for all PCa PI-RADS ≥13 for significant PCa |
10-core TRUS SBx + TBx |
Busetto (2013) [16] | Prospective | 2010–2012 | PNB | 163 | 66.4 (5.3) | 6.8 (1.6) | NR | 3 T | T2WI/DWI/DCEI/MRSI | Yes | NR | NR | 10-core TRUS SBx + TBx |
Rais-Bahrami (2013) [47] | Prospective | 2007–2012 | NR | 583 | 61.3 (8.4) | 9.9 (13.1) | NR | 3 T | T2WI/DWI/DCEI/MRSI | Yes | 1–4 scale (Likert) | ≥2 ≥3 |
12-core TRUS SBx + TBx |
Kuru (2013) [34] | Prospective | 2010–2011 | FB (51%) & PNB (49%) | 347 | 65.3 (42–82) | 9.85 (0.5–104) | 48.7 (9–180) | 3 T | T2WI/DWI/DCEI | No | 1–3 scale (Likert) | ≥2 | 12–36-core TRUS SBx (volume dependent) + TBx |
Ferda (2013) [20] | Prospective | NR | NR | 164 | (49–74) | (4.2–123) | NR | 3 T | T2WI/DWI/DCEI/MRSI | No | NR | In house | TRUS SBx |
Ganie (2013) [21] | NR | 2007–2009 | PNB | 87 | NR | NR | NR | 1.5 T | T2WI/MRSI | Yes | MRSI Cho/Cit ratio | In house | 6 core TRUS SBx + MRI TBx |
Vinet (2013) [57] | Prospective | 2009–2011 | FB | 69 | NR | 5.2* (3.2–28) | NR | 1.5 T (35 pts) & 3 T (34 pts) | T2WI/DWI/DCEI | No | 1–5 scale (Likert) | ≥3 | 12-core TRUS SBx + TBx |
Numao (2013) [38] | Prospective | 2006–2010 | FB | 351 | 65* (59–70) | 6.3* (4.9–9.1) | 32* (24–42) | 1.5 T | T2WI/DWI/DCEI (no DCEI in 42 pts) | No | 1–5 scale (Likert) | ≥3 | 3D 26-core (12 TRUS SBx + 14 TPBx – 203 pts); 3D 14-core (6 TRUS SBx + 8 TPBx – 102 pts); TPBx 14 core (46 pts) |
Belas (2012) [14] | Prospective | 2010–2011 | FB | 71 | 66* (47–76) | 7* (4–10) | 45* (15–150) | 1.5 T | T2WI/DWI/DCEI | No | TZ: 0–4 scale PZ: 0–10 scale |
TZ: >2 PZ: >6 |
12-core TRUS SBx + TBx |
Ibrahiem (2012) [26] | Prospective | 2008–2009 | FB | 100 | 65.03 (7.13) | 26.3 (24.2) | 60.09 (28.7) | 1.5 T | T2WI/DWI | No | NR | In house | 12-core TRUS SBX |
Sciarra (2012) [51] | Prospective | 2008–2011 | PNB | 84 | 64.09 (46–76) | 7.07 (4.2–15.5) | NR | 3 T | T2WI/DWI/DCEI/MRSI | Yes | NR | NR | 10-core TRUS Bx + TBx |
Portalez (2012) [45] | Prospective | 2011 | PNB | 129 | 64.7 (47–79) | 9.6 (2.7–40) | 51.1 (12–192) | 1.5 T | T2WI/DWI/DCEI | Mixed | 1–5 scale (Likert) PI-RADS |
Likert ≥3 PI-RADS ≥9 |
10–12-core TRUS SBx + TBx |
Watanabe (2012) [59] | Prospective | 2004–2008 | NR | 1448 | 72 (7.5) | NR | NR | 1.5 T | T2WI/DWI | No | NR | ADC value ≤1.35 × 10 −3 mm 2 /s | 8-core TRUS SBx + TBx |
Tamada (2011) [54] | Retrospective | 2006–2009 | NR | 50 | 70 (40–84) | 6.84* (4.06–9.94) | NR | 1.5 T | T2WI/DWI/DCEI | No | NR | In house | 12-core TRUS SBx |
Choi (2011) [18] | NR | 2009–2010 | NR | 51 | 67.16 (56–90) | 14.16 (1.02–38.9) | 42.98 (13.8–77.3) | 3 T | T2WI/DWI | NR | NR | NR | 10–12-core TRUS SBx + TBx |
Iwazawa (2011) [28] | Retrospective | 2008–2009 | NR | 178 | 68.8 (41–86) | 20.51 (4.04–568.5) | NR | 1.5 T | T2WI/DWI/DCEI | NR | 1–4 scale (Likert) | NR | 10–12-core TRUS SBx (TBx included in SBx chart) |
Rouse (2011) [48] | Prospective | 2005–2007 | PNB | 114 | 63.6 (41–83) | 13.4 (0–228) | NR | 1.5 T | T2WI/DWI/DCEI | NR | 1–5 scale (Likert) | ≥3 | TRUS SBx |
Haffner (2011) [23] | Prospective | 2005–2009 | FB | 555 | 64* (47–83) | 6.75* (0.18–100) | 46* (15–200) | 1.5 T | T2WI/DCEI | No | 1–5 scale (Likert) | ≥3 | 10-core TRUS SBx + TBx |
Panebianco (2010) [40] | Prospective | 2007–2009 | PNB | 150 | 61.2 (46–78) | 9.42 (3.91) | 41.17 (7.47) | 1.5 T | T2WI/DCEI/MRSI | Yes | NR | In house | 10-core TRUS SBx (TBx included in SBx chart) |
Roy (2010) [49] | Not specified | 2011–2009 | FB (53%) & PNB (47%) | 103 | 63 (52–78) | 7* | NR | 3 T | T2WI/DWI/DCEI | Yes | NR | NR | 8-core TRUS SBx + TBx |
Testa (2010) [55] | Not specified | 2007 | PNB | 54 | 63.9 (52–76) | 11.4 (3–42) | 59.3 (30–150) | 1.5 T | T2WI/MRSI | Yes | 1–3 scale (Likert) | ≥2 | 12-core TRUS SBx + TBx |
Sciarra (2010) [52] | Prospective | 2007–2009 | PNB | 110 | 63.5 (49–74) | NR | NR | 1.5 T | T2WI/DCEI/MRSI | Yes | NR | In house | 10-core TRUS SBx + TBx |
Kitajima (2010) [31] | Prospective | 2008–2009 | NR | 53 | 69* (56–84) | 11.1* (4.2–112.1) | NR | 3 T | T2WI/DWI/DCEI | No | 1–5 scale (Likert) | ≥3 | 20-core TPBx |
Labanaris (2010) [35] | Prospective | 2004–2008 | PNB | 260 | NR | NR | NR | 1 T | T2WI/DWI/DCEI | Yes | Dichotomous | In house | 18-core TRUS SBx |
Kumar (2009) [32] | NR | NR | NR | 61 | 65.3 (9.3) | 16.5 (0.21–155) | NR | 1.5 T | T2WI/MRSI | Yes | NR | (Cit/(Cho + Cr) ≤ 1.2 | TRUS Bx |
Schmuecking (2009) [50] | NR | NR | FB & PNB | 67 | 68 | 11.5 | NR | 1.5 T | T2WI/DCEI | No | NR | NR | 20-core Bx |
Cheikh (2009) [17] | Retrospective | 2005–2008 | PNB | 93 | 63.2 (52–74) | 9.63 (1.6–40) | NR | 1.5 T | T2WI/DCEI | No | Dichotomous | In house | 12-core TRUS SBx + TBx |
Cirillo (2008) [19] | Prospective | 2004–2006 | PNB | 54 | 65.5 (5.2) | 10.8 (7.5) | NR | 1.5 T | T2WI/MRSI | Yes | Dichotomous | In house | 10-core TRUS SBx + TBx |
Kumar (2007) [33] | Prospective | 2003–2005 | NR | 83 | NR | NR | NR | 1.5 T | T2WI/MRSI | Yes | NR | NR | 12-core TRUS SBx + TBx |
Squillaci (2005) [53] | Prospective | 2004–2005 | NR | 65 | NR | NR | NR | 1.5 T | T2WI/DCEI/MRSI | No | 1–3 scale (Likert) | ≥2 | 10-core TRUS SBx + TBx |
Hara (2005) [24] | Prospective | 2003–2004 | FB | 90 | 67.2 (NR) | NR | NR | 1.5 T | T2WI/DCEI | No | 1–3 scale (Likert) | ≥2 = 3 |
14-core TRUS SBx |
The magnetic field strength was 1, 1.5, and 3 T in one, 28, and 15 studies, respectively. Four studies used both 1.5 and 3 T MR systems. DWI and DCEI were used in 36 and 35 studies, respectively. Nineteen studies also added MRSI. An endorectal coil was used in 18 studies. The definition of positive mpMRI varied across studies. The PI-RADS v1 score was used in 12 studies, a five-level subjective (Likert) score was used in eight studies, and one study reported data based on the two scoring systems. In-house criteria were used in 13 studies for defining positive mpMRI, and five studies used a dichotomous definition. Nine studies did not report on the criteria for positive mpMRI. No study used the PI-RADS v2 score.
Regarding the reference standard, TRUS-guided biopsies were used in 39 studies, TTP biopsies in six studies, and mixed TRUS-guided and TTP biopsies in two studies. In one study, the biopsy approach was unclear. The number of cores per biopsy procedure was ≤16 in 30 studies, >16 in nine studies, and variable among patients in three studies. For six studies, the number of biopsy cores taken was unclear.
At patient level, the median biopsy positivity rate (ie, cancer prevalence) was 50.4% (IQR, 36.4–57.7%) for overall cancer and 32.9% (IQR, 28.1–37.2%) for csPCa ( Table 2 ). The median mpMRI NPV was 82.4% (IQR, 69.0–92.4%) for overall cancer and 88.1% (IQR, 85.7–92.3) for csPCa. NPV significantly decreased when cancer prevalence increased, both for overall cancer ( r = –0.64, p < 0.0001) and csPCa ( r = –0.75, p = 0.032; Fig. 3 ). In addition, NPV was highly dependent on the definition used for csPCa, with differences of up to 21% when several definitions were used in the same dataset [12 13 38 47 48] .
Study | Overall PCa prevalence (%) | Reporting level | Multiparametric MRI performance for PCa detection | Definition of csPCa | csPCa prevalence | Multiparametric MRI performance for csPCa detection | ||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
TN | FN | TP | FP | NPV | PPV | TN | FN | TP | FP | NPV | PPV | |||||
Hauth (2015) [25] | 45.7 | Patient | 6 | 1 | 42 | 45 | 85.7% | 48.3% | Low grade: GS ≤ 6 High grade: GS ≥ 7 |
NR | NR | NR | NR | NR | NR | NR |
Lesion | 59 | 13 | 55 | 73 | 81.9% | 43% | ||||||||||
Lamb (2015) [36] | 65.9 | Patient | 23 | 22 | 92 | 36 | 51.1% | 71.9% | GS ≥ 7 | 50.9% | 31 | 14 | 71 | 57 | 68.9% | 55.5% |
Brock (2015) [15] | 42.3 | Patient | 17 | 7 | 56 | 88 | 70.8% | SBx: 38.8% TBx: 22.2% Duo: 44.4% |
Epstein: GS > 6 and/or max CCL ≥50% | 24.4% | SBx: 21 | SBx: 3 | SBx: 38 TBx: 27 duo: 47 |
SBx: 106 TBx: 117 duo: 97 |
87.5% | SBx: 26.4% TBx: 18.8% duo: 32.6% |
Grenabo Bergdahl (2016) [22] | 33.7 | Patient | 36 | 7 | 19 | 21 | 83.7% | 47.5% | Clinically insignificant PCa: T1c, PSAd < 0.15, GS < 7, ≤2 positive cores, and unilateral cancer | NR | NR | NR | NR | NR | NR | NR |
Wang (2015) [58] | 58 | Patient | 165 | 8 | 332 | 81 | 95.4% | 80.4% | NR | NR | NR | NR | NR | NR | NR | NR |
Pepe (2015) [41] | 37 | Patient | 23 | 8 | 29 | 40 | 74.2% | 42% | GS ≥ 7 or GS 6 with CCL ≥ 50% | NR | NR | NR | NR | NR | 100% | 55.8% |
Panebianco (2015) [39] | 74.7 | Patient | Group A (satBx): 104 | Group A (satBx): 43 | Group A: 186 | Group A: 22 | Group A (satBx): 70.7% | Group A: 89.4% | NR | 60% | Group A: 147 | Group A: 0 | Group A: 183 | Group A: 25 | Group A: 100% | Group A: 88% |
Group B (TRUSGB NR TRUS G satBx): 93 | Group B (TRUSGB NR TRUS G satBx): 37 | Group B: 417 before and 425 after satBx | Group B: 23/440 and 15/440 after satBx. | Group B (TRUSGB–TRUS G satBx): 71.5% | Group B: 94.8% before and 96.6% after satBx | 71.9% | Group B: 130 | Group B: 0 | Group B: 410 |
Group B: 30 | Group B: 100% | Group B: 93.2% | ||||
Radtke (2015) [46] | 51 | Patient | ≥2/5: 80 ≥3: 103 ≥4: 138 = 5: 142 |
≥2/5: 18 ≥3/5: 38 ≥4/5: 78 = 5/5: 126 |
≥2/5: 132 ≥3/5: 112 ≥4/5: 72 = 5/5: 24 |
≥2/5: 64 ≥3/5: 41 ≥4/5: 6 = 5/5: 2 |
≥2/5: 81.6% ≥ 3/5: 73.1% ≥ 4/5: 63.9% = 5/5: 53% |
≥2/5: 67.4% ≥ 3/5: 73.2% ≥ 4/5: 92.3% = 5/5: 92.3% |
GS ≥ 7 | 29.3% | ≥2/5: 91 ≥3/5: 124 ≥4/5: 183 = 5/5: 203 |
≥2/5: 7 ≥3/5: 17 ≥4/5: 33 = 5/5: 65 |
≥2/5: 79 ≥3/5: 69 ≥4/5: 53 = 5/5: 21 |
≥2/5: 117 ≥3/5: 84 ≥4/5: 25 = 5/5: 5 |
≥2/5: 92.2% ≥3/5: 87.9% ≥4/5: 84.7% = 5/5: 75.8% |
≥2/5: 40.3% ≥3/5: 45.1% ≥4/5: 68% = 5/5: 80.7% |
Itatani (2014) [27] | 13 | Patient | 168 | 25 | NR | NR | 87% | NR | (1) PSAd ≥ 0.1 or GP 4/5 or ≥ 3/6 pos cores; max CCL < 50% (2) PSAd ≥ 0.15 or GP 4/5 or max core length invasion < 3 mm (min 6 cores) |
NR | NR | NR | NR | NR | NR | NR |
Porpiglia (2014) [44] | 30.6 | Patient | 107 | 5 | 47 | 11 | 95.5% | 81% | NR | NR | NR | NR | NR | NR | NR | NR |
Thompson (2014) [56] | 61.3 | Patient | 35 | 16 | 76 | 23 | 68.6% | 76.7% | Moderate or high risk Moderate risk: GS 7 (GP4 >5%) and <50% of positive cores or GS 6–7 (GP4 ≤ 5%) and either ≥30% of positive cores or max core length invasion ≥8 mm High risk: GS ≥ 7 (GP4 > 5%); ≥50% + cores or GS ≥ 8 |
34% | 49 | 2 | 49 | 50 | 96% | 49.5% |
Pokorny (2014) [43] | 63.7 | Patient | ≥3/5: 56 ≥4/5: 74 |
≥3/5: 25 ≥4/5: 40 |
≥3/5: 101 ≥4/5: 86 |
≥3/5: 41 ≥4/5: 23 |
≥3/5: 69.1% ≥4/5: 64.9% |
≥3/5: 71.1% ≥4/5: 78.9% |
NR | NR | NR | NR | NR | NR | NR | NR |
Petrillo (2014) [42] | 18.4 | Patient | 56 | 4 | 21 | 55 | 93% | 28% | NR | NR | NR | NR | NR | NR | NR | NR |
Javali (2014) [29] | 16.4 | Patient | 49 | 1 | 22 | 68 | 98% | 24.4% | NR | NR | NR | NR | NR | NR | NR | NR |
Abd-Alazeez (2014) [13] | 54.7 | Lobe | ≥3/5: 33 | ≥3/5: 14 | ≥3/5: 127 | ≥3/5: 84 | ≥3/5: 70% | ≥3/5: 60% | Def 1: GS ≥ 4 + 3 and/or max CCL ≥ 6 mm Def 2: GS ≥ 3 + 4 and/or max CCL ≥ 4 mm Def 3: GS ≥ 4 + 3 Def 4: GS ≥ 3 + 4 Def 5: max CCL ≥ 6 mm Def 6: max CCL ≥ 4 mm |
Def 1: NR Def 2: 44.2% Def 3: 23.2% Def 4: 36% Def 5: 32.9% Def 6: 39.5% |
Def 1: 46 Def 2: 42 Def 3: 47 Def 4: 43 Def 5: 46 Def 6: 43 |
Def 1: 1 Def 2: 5 Def 3: 0 Def 4: 4 Def 5: 1 Def 6: 4 |
Def 1: 45 Def 2: 72 Def 3: 13 Def 4: 50 Def 5: 39 Def 6: 59 |
Def 1: 166 Def2: 139 Def 3: 198 Def 4: 161 Def 5: 172 Def 6: 152 |
Def 1: 98 Def 2: 89 Def 3: 100 Def 4: 92 Def 5: 98 Def 6: 91 |
Def 1: 21 Def 2: 34 Deg 3: 6 Def 4: 24 Def 5: 19 Def 6: 28 |
≥4/5: 87 | ≥3/5: 62 | ≥3/5: 79 | ≥3/5: 30 | ≥3/5: 58% | ≥3/5: 73% | Def 1: 140 Def 2: 124 Def 3: 148 Def 4: 133 Def 5: 141 Def 6: 131 |
Def 1: 9 Def 2: 25 Def 3: 1 Def 4: 16 Def 5: 8 Def 6: 18 |
Def 1: 37 Def 2: 52 Def 3: 12 Def 4: 38 Def 5: 32 Def 6: 45 |
Def 1: 72 Def 2: 57 Def 3: 97 Def 4: 71 Def 5: 77 Def 6: 64 |
Def 1: 94 Def 2: 83 Def 3: 99 Def 4: 89 Def 5: 95 Def 6: 88 |
Def 1: 34 Def 2: 48 Def 3: 11 Def 4: 35 Def 5: 30 Def 6: 42 |
|||||
Abd-Alazeez (2014) [12] | 47.2 | Lobe | ≥3/5: 26 | ≥3/5: 13 | ≥3/5: 38 | ≥3/5: 31 | ≥3/5: 66% | ≥3/5: 55% | Def 1: GS ≥ 4 + 3 and/or max CCL ≥ 6 mm Def 2: GS ≥ 3 + 4 and/or max CCL ≥ 4 mm Def 3: GS ≥ 4 + 3 Def 4: GS ≥ 3 + 4 Def 5: max CCL ≥ 6 mm Def 6: max CCL ≥ 4 mm |
Def 1: 18.5% Def 2: 31.5% Def 3: 4.6% Def 4: 21.3% Def 5: 16.7% Def 6: 25% |
Def 1: 37 Def 2: 31 Def 3: 39 Def 4: 36 Def 5: 37 Def 6: 32 |
Def 1: 2 Def 2: 8 Def 3: 0 Def 4: 3 Def 5: 2 Def 6: 7 |
Def 1: 18 Def 2: 26 Def 3: 5 Def 4: 20 Def 5: 16 Def 6: 20 |
Def 1: 51 Def 2: 43 Def 3: 64 Def 4: 49 Def 5: 53 Def 6: 49 |
Def 1: 95 Def 2: 79 Def 3: 100 Def 4: 92 Def 5: 95 Def 6: 82 |
Def 1: 26 Def 2: 38 Def 3: 7 Def 4: 29 Def 5: 23 Def 6: 29 |
≥4/5: 49 | ≥4/5: 25 | ≥4/5: 26 | ≥4/5: 8 | ≥4/5: 66% | ≥4/5: 76% | Def 1: 70 Def 2: 63 Def 3: 73 Def 4: 68 Def 5: 70 Def 6: 64 |
Def 1: 4 Def 2: 11 Def 3: 1 Def 4: 6 Def 5: 4 Def 6: 10 |
Def 1: 16 Def 2: 23 Def 3: 4 Def 4: 17 Def 5: 14 Def 6: 17 |
Def 1: 18; Def 2: 11 Def 3: 30 Def 4: 17 Def 5: 20 Def 6: 17 |
Def 1: 94 Def 2: 85 Def 3: 99 Def 4: 92 Def 5: 94 Def 6: 86 |
Def 1: 47 Def 2: 67 Def 3: 12 Def 4: 50 Def 5: 41 Def 6: 49 |
|||||
Matsuoka (2014) [37] | 64.8 | Lobe | 46 | 49 | 149 | 26 | 48.4% | 85.1% | NR | NR | NR | NR | NR | NR | NR | NR |
Junker (2013) [30] | 53.4 | Patient | ≥10/15: 21 ≥11/15: 28 |
≥10/15: 4 ≥11/15: 12 |
≥10/15: 35 ≥11/15: 27 |
≥10/15: 13 ≥11/15: 6 |
≥10/15: 84% ≥11/15: 70% |
≥10/15: 72.9% ≥11/15: 81.8% |
GS ≥ 4 + 3 | 13.7% | ≥13: 54 | ≥13: 2 | ≥13: 8 | ≥13: 9 | ≥13: 96.4% | ≥13: 47% |
Busetto (2013) [16] | 41.7 | Patient | 59 | 7 | 61 | 36 | 89% | 63% | NR | NR | NR | NR | NR | NR | NR | NR |
Rais-Bahrami (2013) [47] | 54.2 | Patient | ≥2/4 : 80 | ≥2/4: 275 | ≥2/4: 187 | ≥2/4: 275 | ≥2/4: 66% | ≥2/4: 59% | GS ≥ 7: GS ≥ 8 |
31.7% | NR | NR | NR | NR | GS ≥ 7: 91% GS ≥ 8: 91% |
GS ≥ 7: 38% GS ≥ 8: 18% |
≥3/4: 251 | ≥3/4: 76 | ≥3/4: 16 | ≥3/4: 76 | ≥3/4: 51% | ≥3/4: 82% | NR | NR | NR | NR | GS ≥ 7: 75% GS ≥ 8: 91% |
GS ≥ 7: 67% GS ≥ 8: 41% |
|||||
Kuru (2013) [34] | 57.6 | Patient | 80 | 14 | 67 | 186 | 85.1% | 73.5% | NR | NR | NR | NR | NR | NR | NR | NR |
Ferda (2013) [20] | 51.2 | Patient | 52 | 2 | 82 | 28 | 96.3% | 74.5% | NR | NR | NR | NR | NR | NR | NR | NR |
Ganie (2013) [21] | 74.7 | Patient | 13 | 3 | 62 | 9 | 59.1% | 95.4% | NR | NR | NR | NR | NR | NR | NR | NR |
Vinet (2013) [57] | 49.3 | Patient | ≥3/5: 11 | ≥3/5: 6 | ≥3/5: 28 | ≥3/5: 24 | ≥3/5: 64.7% | ≥3/5: 53.8% | NR | NR | NR | NR | NR | NR | NR | NR |
≥4/5: 22 | ≥4/5: 11 | ≥4/5: 23 | ≥4/5: 13 | ≥4/5: 66.7% | ≥4/5: 63.8% | NR | NR | NR | NR | NR | NR | NR | NR | |||
Numao (2013) [38] | 45 | Patient | 137 | 57 | 101 | 56 | 70.6% | 64.3% | Def 1: GS ≥4 + 3 and/or ≥20% positive cores and/or max CCL ≥5 mm Def 2: GS ≥ 3 + 4 and/or ≥20% + cores and/or max CCL ≥5 mm Def 3: GS ≥ 3 + 4 and/or ≥20% + cores |
Def 1: 33.3% Def 2:37.8% Def 3: 35.8% |
Def 1: 74 Def 2: 65 Def 3: 69 |
Def 1: 83 Def 2: 92 Def 3: 88 |
Def 1: 160 Def 2: 153 Def 3: 156 |
Def 1: 34 Def 2: 41 Def 3: 38 |
Def 1: 82.4% Def 2: 78.8% Def 3: 80.4% |
Def 1: 58.8% Def 2: 58.5% Def 3: 56% |
Belas (2012) [14] | 53.5 | Patient | 22 | 12 | 23 | 13 | 64.7% | 63.8% | NR | NR | NR | NR | NR | NR | NR | NR |
Ibrahiem (2012) [26] | 73.9 | Patient | 14 | 11 | 57 | 10 | 56% | 85.1% | NR | NR | NR | NR | NR | NR | NR | NR |
Sciarra (2012) [51] | 34.5 | Patient | 41 | 4 | 25 | 14 | 91.1% | 64.1% | NR | NR | NR | NR | NR | NR | NR | NR |
Portalez (2012) [45] | 48.1 | Lesion | Likert: 357 | Likert: 50 | Likert: 81 | Likert: 50 | Likert: 95% | Likert: 38% | Max CCL >3 mm and/or GG 4/5 | NR | NR | NR | NR | NR | NR | NR |
PI-RADS: 404 | PI-RADS: 47 | PI-RADS: 34 | PI-RADS: 47 | PI-RADS: 95% | PI-RADS: 58% | |||||||||||
Watanabe (2012) [59] | 48.1 | Patient | 485 | 73 | 624 | 266 | 86.9% | 70.1% | NR | NR | NR | NR | NR | NR | NR | NR |
Tamada (2011) [54] | 70 | Patient | 12 | 6 | 29 | 3 | 67% | 91% | NR | NR | NR | NR | NR | NR | NR | NR |
Region | 277 | 48 | 55 | 20 | 85% | 73% | ||||||||||
Choi (2011) [18] | 70.6 | Patient | 9 | 5 | 31 | 6 | 64.2% | 75.7% | NR | NR | NR | NR | NR | NR | NR | NR |
Iwazawa (2011) [28] | 40.5 | Region | 887 | 86 | 232 | 219 | 91.1% | 51.4% | NR | NR | NR | NR | NR | NR | NR | NR |
Rouse (2011) [48] | 33.7 | Sextant | 145 | 11 | 74 | 22 | 92.9% | 77.1% | GS ≥ 7: Def 1: ≥3 mm Def 2: ≥5 mm |
Def 1: 26.6% Def 2: 26.2% |
Def 1: 153 Def 2: 153 |
Def 1: 3 Def 2: 3 |
Def 1: 64 Def 1: 63 |
Def 1: 32 Def 2: 33 |
Def 1: 98.1% Def 2: 98.1% |
Def 1: 68.1% Def 2: 67% |
59.6 | Patient | 24 | 14 | 54 | 22 | 63.2% | 71.1% | Def 1: 41.2% Def 2: 36.8% |
Def 1: 30 Def 2: 31 |
Def 1: 4 Def 2: 3 |
Def 1: 43 Def 2: 39 |
Def 1: 4 Def 2: 3 |
Def 1: 88.2% Def 2: 91.2% |
Def 1: 53.8% Def 2: 48.8% |
||
Haffner (2011) [23] | 54.4 | Patient | 154 | 50 | 240 | 111 | 75.4% | 68.3% | NR | NR | NR | NR | NR | NR | NR | NR |
Panebianco (2010) [40] | 42.7 | Patient | NR | NR | NR | NR | 95.1% | 88.2% | NR | NR | NR | NR | NR | NR | NR | NR |
Roy (2010) [49] | 55.9 | Patient | NR | NR | NR | NR | 71% | 75% | NR | NR | NR | NR | NR | NR | NR | NR |
Testa (2010) [55] | 40.7 | Patient | NR | NR | NR | NR | 79.3% | 64% | NR | NR | NR | NR | NR | NR | NR | NR |
Sciarra (2010) [52] | 50 | Patient | 61 | 4 | 66 | 9 | 93.8% | 88% | NR | NR | NR | NR | NR | NR | NR | NR |
Kitajima (2010) [31] | 56.6 | Patient | 311 | 19 | 80 | 14 | 92.2% | 85.1% | NR | NR | NR | NR | NR | NR | NR | NR |
Labanaris (2010) [35] | 73.9 | Patient | 17 | 73 | 96 | 74 | 81.11% | 56.47% | NR | NR | NR | NR | NR | NR | NR | NR |
Kumar (2009) [32] | 21.7 | Patient | 39 | 3 | 10 | 8 | 92.8% | 55% | NR | NR | NR | NR | NR | NR | NR | NR |
Schmuecking (2009) [50] | NR | Lobe | NR | NR | NR | NR | 96% | 61% | NR | NR | NR | NR | NR | NR | NR | NR |
Cheikh (2009) [17] | 24.7 | Patient | 36 | 12 | 11 | 34 | 80% | 22.9% | NR | NR | NR | NR | NR | NR | NR | NR |
Cirillo (2008) [19] | 31.5 | Patient | 19 | 0 | 17 | 18 | 100% | 48.6% | NR | NR | NR | NR | NR | NR | NR | NR |
Kumar (2007) [33] | 13.3 | Patient | 39 | 0 | 11 | 33 | 100% | 25% | NR | NR | NR | NR | NR | NR | NR | NR |
Squillaci (2005) [53] | 50.8 | Patient | 29% | 8% | 25% | 3% | 89% | 80% | NR | NR | NR | NR | NR | NR | NR | NR |
Hara (2005) [24] | 41.5 | Patient | ≥2/3: 40 = 3/3: 47 |
≥2/3: 4 = 3/3: 8 |
≥2/3 30 = 3/3: 26 |
≥2/3: 8 = 3/3: 1 |
≥2/3: 90% = 3/3: 85% |
≥2/3: 78.9% = 3/3: 96.3% |
NR | NR | NR | NR | NR | NR | NR | NR |
Cancer prevalence tended to be higher and mpMRI NPV lower in the biopsy-naïve group as compared with the repeat biopsy group, in men with positive DRE as compared with men with negative DRE and when an endorectal coil was not used ( Table 3 ). There were no clear differences in the prevalence and NPV of the other analysed subgroups (TRUS-guided vs TTP biopsy, biopsy procedures with ≤16 cores vs >16 cores; Table 3 ). However, comparisons must be interpreted with care, due to the small number of studies in some subgroups. In patients with a PSA level of ≤10 ng/ml, the median NPV for overall PCa was 86.3% (IQR, 73.3–93.6%) for a median cancer prevalence of 35.4% (IQR, 27.6–42.5%).
Nb of studies | Median PCa prevalence | Median mpMRI NPV | Nb of studies | Median csPCa prevalence | Median mpMRI NPV | |
---|---|---|---|---|---|---|
Biopsy-naïve patients | 8 | 51.4% (45.5–56.7) | 69.9% (64.2–78) | 1 | 35.8% (NA) | 80.4% (NA) |
Repeat biopsy | 14 | 42% (35.1–52.6) | 82.6% (75.5–93.1) | 3 | 24.4% (19.1–32.8) | 88.2% (87.9–92.3) |
TRUS-guided biopsy | 36 | 49.7% (34.3–57.7) | 84.6% (68.6–92.8) | 4 | 28.1% (21.7–36.5) | 89.3% (82.9–92.4) |
TTP biopsy | 4 | 53.8% (47.5–57.8) | 73.6% (72–78.7) | 2 | 31.6% (30.5–32.8) | 92% (89.9–94) |
Biopsy with ≤16 cores | 28 | 48.7% (39.2–54.8) | 81.9% (66.8–89.3) | 5 | 28.1% (21.8–36.5) | 89.3% (82.9–92.4) |
Biopsy with >16 cores | 5 | 56.6% (51–61.3) | 81.1% (73.1–92.2) | 2 | 31.7% (30.5–32.8) | 92% (89.9–93.9) |
Positive DRE | 1 | 73.9% (NA) | 56% (NA) | 0 | – | – |
Negative DRE | 6 | 36% (34.6–46.8) | 82.7% (74.2–93.1) | 0 | – | – |
Endorectal coil | 17 | 41.7% (30.6–55.9) | 92.8% (79.3–95.4) | 1 | 31.7% (NA) | 91% (NA) |
No endorectal coil | 22 | 50.9% (41.7–56.1) | 77.7% (69.5–86.6) | 7 | 34% (26.9–46.1%) | 87.9% (78.2–92.1) |
Eight studies reported NPV at patient level for overall PCa and fulfilled the inclusion criteria for meta-analysis ( Table 4 ) [22 25 38 41 43 46 56 57] .
Study | Prevalence a (%) | Neg MRI (%) | NPV (%) | PPV (%) | Spe (%) | Se (%) | ||
---|---|---|---|---|---|---|---|---|
All PCa | Score ≥ 3/5 | Grenabo Bergdahl (2016) [22] | 31.3 | 66.9 | 83.7 | 47.5 | 63.2 | 73.1 |
Numao (2013) [38] | 45 | 29.4 | 70.6 | 64.3 | 71.0 | 63.9 | ||
Hauth (2015) [25] | 45.7 | 14.3 | 85.7 | 48.3 | 11.8 | 97.7 | ||
Vinet (2013) [57] | 49.3 | 24.6 | 64.7 | 53.8 | 31.4 | 82.4 | ||
Radtke (2015) [46] | 51 | 27 | 73 | 73.2 | 71.5 | 74.7 | ||
Thompson (2014) [56] | 61.3 | 31.4 | 68.6 | 76.8 | 60.3 | 82.6 | ||
Pokorny (2014) [43] | 63.7 | 30.9 | 69.1 | 82.4 | 69.1 | 82.4 | ||
Score ≥ 4/5 | Pepe (2015) [41] | 37 | 31 | 74.2 | 42 | 36.5 | 78.4% | |
Vinet (2013) [57] | 49.3 | 47.8 | 66.7 | 63.9 | 62.9 | 67.6% | ||
Radtke (2015) [46] | 51 | 73.5 | 63.9 | 92.3 | 95.8 | 48% | ||
Gleason ≥7 PCa | Score ≥ 3/5 | Radtke (2015) [46] | 29.3 | 27 | 87.9 | 45.1 | 59.6 | 80.2% |
a Prevalence of overall prostate cancers (10 first lines) or Gleason ≥7 cancers (last line).
PCa = prostate cancer; MRI = magnetic resonance imaging; Neg MRI = proportion of negative magnetic resonance imaging; NPV = negative predictive value; PPV = positive predictive value; Se = sensitivity; Spe = specificity.
Seven studies used a score of ≥3/5 for defining positive mpMRI ( Fig. 4 A and B) [22 25 38 43 46 56 57] . Fig. 4 C shows the conditional probability plot of 1 – NPV and PPV as a function of overall PCa prevalence. Table 5 shows NPV and PPV estimates for the given values of PCa prevalence.
PCaPrev | PPV | NPV |
---|---|---|
0.30 | 0.43 (0.34–0.53) | 0.88 (0.77–0.99) |
0.40 | 0.54 (0.45–0.64) | 0.82 (0.70–0.94) |
0.50 | 0.64 (0.55–0.73) | 0.76 (0.64–0.88) |
0.60 | 0.73 (0.65–0.80) | 0.67 (0.56–0.79) |
0.70 | 0.81 (0.75–0.87) | 0.57 (0.47–0.67) |
0.75 | 0.84 (0.79–0.89) | 0.51 (0.42–0.59) |
Only three studies used a score of ≥4/5 for defining positive mpMRI ( Table 4 ) [41 46 57] , and a formal meta-analysis could not be performed.
Only one study reporting NPV at patient level for Gleason ≥7 cancers met the selection criteria for inclusion in the meta-analysis. It reported NPV and PPV of 87.9% and 45.1%, respectively, for a prevalence of 29.3% ( Table 4 ) [46] .
We observed a large variability in reported NPV. Many factors, such as differences in mpMRI protocols, definition of negative mpMRI, or biopsy protocols, can explain this variability. However, two major causes of variability must be pointed out. First, the cancer prevalence was highly variable, ranging at patient level from 13% to 74.7% for overall PCa, and from 13.7% to 50.9% for csPCa. This variability was observed in both the biopsy-naïve and the repeat biopsy setting. As NPV depends on prevalence, this had a major impact on reported NPV ( Fig. 3 ). Second, the definition of csPCa was highly variable from one series to another, and differences of up to 21% could be observed in NPV when different definitions of csPCa were used in the same dataset [12 13 38 47 48] .
To account for clinical heterogeneity and to further explore the clinical relevance of the results, we carefully selected studies for inclusion in the meta-analysis based on stringent criteria. Particularly, we included only studies that: (1) had biopsy protocols with at least 10 cores, since it is no longer recommended to obtain less than 10 cores per biopsy; (2) used DWI, which is the most informative technique, at least for cancers in the peripheral zone [60] ; and (3) reported mpMRI findings using a five-level score, so that negative findings could be better defined. We accepted studies using a subjective (Likert) scale because experienced readers obtained equivalent [45 61 62] or better [63] results with the Likert score than with the PI-RADS v1 score. Owing to the large variations of NPV induced by differences in definitions of csPCa, we did not include different definitions in the meta-analysis since this would have introduced unacceptable clinical heterogeneity in the results, possibly resulting in erroneous and biased estimates. We, therefore, a priori restricted the definition of csPCa to cancers with a Gleason score of ≥7, given the low lethal potential of Gleason 6 cancers [64] and the lack of consensus among pathologists on the best method to measure biopsy core invasion length [65 66] .
In this more homogeneous group of studies, the prevalence range was still large (31.3–63.7%). As a result, we modelled the evolution of NPV (and PPV) as a function of overall PCa prevalence. Unfortunately, we could not duplicate this for csPCa since only one study reporting NPV for Gleason ≥7 cancers met the inclusion criteria for meta-analysis.
We included only studies that reported the results of systematic/standard biopsy in patients with negative mpMRI and used the systematic/standard biopsy as a reference standard. It is well known that TRUS-guided biopsy harbours both random and systematic errors, as evidenced by the high rates of positivity of immediate repeat biopsy after a first series of negative biopsies [67 68] , and as confirmed recently by the PROMIS trial [69] . Therefore, using TRUS-guided biopsy as a reference standard may have overestimated the NPV of mpMRI. However, studies using radical prostatectomy specimens as a reference standard have already reported mpMRI detection rates in relation to PCa Gleason score and volume [1] . In this review, we intended to address the more pragmatic question as to whether a negative mpMRI could predict a negative subsequent biopsy. This is an important question because if the NPV of mpMRI was sufficiently high in comparison with the reference standard of systematic/standard biopsies, then in practice a negative mpMRI result could indeed avoid the need for prostate biopsy. Therefore, studies reporting only biopsy results when the mpMRI was positive (eg, obtained through MRI-targeted, guided, or fusion biopsies with added systematic biopsies) were not included in this review.
It is now well established that mpMRI is a sensitive tool for detecting aggressive PCa 1 2 3 69] . However several reasons preclude its broad use as a triage test before biopsy.
Firstly, the population referred to prostate biopsy is not standardised. The large range of reported prevalence for overall PCa and csPCa suggests substantial heterogeneity in the way patients are selected for biopsy. Owing to this heterogeneity, we did not provide a pooled estimate for mpMRI NPV. The role of mpMRI as a triage test before prostate biopsy should be evaluated in the broader context of the selection of patients with a suspicion of (aggressive) PCa. In a recent retrospective study of 514 patients, mpMRI NPV for Gleason ≥7 cancers was 91% when the PSA density was ≤0.2 ng/ml/ml, and only 71% when the PSA density was >0.2 ng/ml/ml ( p = 0.003) [70] . In another series of 288 biopsy-naïve patients, no csPCa (Gleason score ≥7 or maximum cancer core length ≥4 mm) was found in 44 patients with a PSA density of <0.15 ng/ml/ml and a PI-RADS v2 score of <3/5 [71] . We believe that such prestratification of the risk of csPCa is an interesting way for rationalising the use of mpMRI before biopsy. Patients found at very low risk would be spared both mpMRI and biopsy. Patients at a low risk—for whom mpMRI would have an NPV high enough to be used as a triage test—could avoid biopsy in case of negative mpMRI. Patients at a higher risk would need biopsy even in case of negative mpMRI. Many tools can be used to risk stratify the population of patients referred to biopsy, ranging from simple parameters such as PSA density to more complicated risk calculators [72 73] . The impact of these tools on the NPV of prebiopsy mpMRI needs to be carefully evaluated, both in the biopsy-naïve and in the repeat biopsy setting. For the moment, it is impossible to make any recommendations on the best way to risk stratify patients before referring them for mpMRI.
Secondly, the large variability in the definition of csPCa precludes any definitive conclusion on the ability of mpMRI to rule out aggressive cancer. The issue of the most appropriate definition of csPCa on biopsy is complex, since biopsy results may accurately reflect neither tumour burden nor aggressiveness. Nonetheless, there is an urgent need to standardise the histological definition(s) of csPCa, to allow meaningful comparisons between studies.
Thirdly, the specificity of mpMRI remains moderate, and there is a substantial proportion of false positives in the lesions scored 3/5 or 4/5 [1 74 75] , even with the new PI-RADS v2 score [76] . In a series of 62 patients with 116 lesions biopsied under magnetic resonance/ultrasound fusion, the overall cancer detection rates for PI-RADS v2 scores of 3/5 and 4/5 were only 15.8% and 29.8%, respectively [77] . In theory, a triage test used to rule out a disease needs to be highly sensitive for this disease. However, if its specificity is too low, it will be clinically useless since most patients will be positive, whether they have the disease or not. Therefore, if mpMRI is to be used as a triage test in the future, there is a need to improve its specificity. This could be achieved by a continuous refinement of scores [78] . Promising results in characterising csPCa have also been reported with a quantitative analysis [79] .
Finally, all published studies were conducted in specialised centres. The broad use of mpMRI as a triage test assumes good interobserver reproducibility. Unfortunately, interobserver reproducibility of existing scoring systems remains moderate [62 63 80] even with the use of the PI-RADS v2 score [80 81] . Studies evaluating on a large scale the reproducibility of mpMRI findings between expert and nonexpert centres are currently lacking.
Three systematic reviews (including two meta-analyses) regarding the role of mpMRI in localised PCa have been published recently 4 5 6 . Crucially, all three reviews focused exclusively on the sensitivity of mpMRI-targeted, guided, or fusion biopsies in diagnosing overall PCa and csPCa, using TRUS-guided prostate biopsies as reference standards. The impact of systematic biopsies on the outcome was not addressed in any of the reviews, within either the index test or the reference standard. Our review had a totally different research question and objective, focusing on NPV of mpMRI to see if a negative mpMRI can avoid the need for a prostate biopsy. As MRI-targeted/guided/fusion biopsies are not relevant if the mpMRI was negative for cancer, it can be argued that the three reviews assessed a different index test altogether. As such, we believe that the findings of this review are novel and unique, and pave the way for further focused clinical studies.
The current study represents the first systematic review addressing the role of mpMRI as a triage test before biopsy. The review elements were developed in conjunction with a multidisciplinary panel of experts (EAU Prostate Cancer Guidelines Panel), which included a patient representative, and the review was performed robustly in accordance with recognised standards. However, it is limited by the major heterogeneity of the existing literature in patient population, study design, and definitions of positive mpMRI and csPCa. It highlighted further areas of research that could help in defining the best use of mpMRI in the early detection of aggressive PCa in the future.
Although mpMRI can detect aggressive PCa with excellent sensitivity, a definitive conclusion on its role as a triage test before prostate biopsy will be possible only when three main issues are addressed. Firstly, because NPV depends on prevalence, and because overall PCa and csPCa prevalence was highly variable in the published series, it becomes mandatory to define the optimal way to pre-evaluate the risk of csPCa in patients with a suspicion of PCa. Depending on the risk category, mpMRI could then be used to obviate biopsies or not. Secondly, there is a need for consensus definitions of csPCa on biopsy findings to allow interstudy comparisons. Thirdly, although efforts have been made to standardise mpMRI technical protocols and interpretation in the past few years [11 60 76] , there is still a crucial need to improve mpMRI specificity and inter-reader reproducibility.
This systematic review was performed under the auspices of:
The European Association of Urology Guidelines Office Board
The European Association of Urology Prostate Cancer Guideline Panel
Author contributions: Olivier Rouvière had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.
Study concept and design: Rouvière, Mottet, Cornford.
Acquisition of data: Rouvière, Moldovan, Van den Broeck, Yuan.
Analysis and interpretation of data: Rouvière, Moldovan, Van den Broeck, Lam.
Drafting of the manuscript: Rouvière, Moldovan, Van den Broeck, Lam.
Critical revision of the manuscript for important intellectual content: Bellmunt, van den Bergh, Bolla, Briers, Van den Broeck, Cornford, Cumberbatch, De Santis, Fossati, Gross, Henry, Joniau, Lam, Matveev, Moldovan, van der Poel, van der Kwast, Rouvière, Schoots, Wiegel, Mottet.
Statistical analysis: None.
Obtaining funding: None.
Administrative, technical, or material support: Yuan, Sylvester, Marconi.
Supervision: None.
Other: None.
Financial disclosures: Olivier Rouvière certifies that all conflicts of interest, including specific financial interests and relationships and affiliations relevant to the subject matter or materials discussed in the manuscript (eg, employment/affiliation, grants or funding, consultancies, honoraria, stock ownership or options, expert testimony, royalties, or patents filed, received, or pending), are the following: Bellmunt is a company consultant for Janssen, Astellas, Pierre Fabre, Genentech, Merck, Ipsen, Pfizer, Novartis, and Sanofi Aventis. He has received research support from Takeda, Novartis, and Sanofi, and received travel grants from Pfizer and Pierre Fabre. Bolla has received company speaker honoraria from Ipsen and Astellas, honoraria or consultation fees from Janssen, and fellowship and travel grants from Janssen, AstraZeneca, and Astellas. Briers has received grant and research support from Ipsen, European Association of Urology, and Bayer; is an ex officio board member for Europa UOMO; is an ethics committee and advisory group member for REQUITE; is a member patient advisory board member for PAGMI; and is a member of SCA and EMA PCWP. Cornford is a company consultant for Astellas, Ipsen, and Ferring. He receives company speaker honoraria from Astellas, Janssen, Ipsen, and Pfizer; participates in trials from Ferring; and receives fellowships and travel grants from Astellas and Janssen. De Santis is a company consultant for GlaxoSmithKline, Janssen, Bayer, Novartis, Pierre Fabre, Astellas, Amgen, Eisai Inc., ESSA, Merck, and Synthon; has received company speaker honoraria from Pfizer, Takeda, Sanofi Aventis, Shionogi, Celgene, and Teva OncoGenex; has participated in trials for Pierre Fabre, Astellas, Exelixis, Bayer, and Roche; has received fellowship and travel grants from Bayer, Novartis, Ferring, Astellas, Sanofi Aventis, and Janssen; has received grant and research support from Pierre Fabre; has received honoraria from AstraZeneca; and is associated with Amgen. Joniau is a company consultant for Astellas, Ipsen, Bayer, Sanofi, and Janssen; has received company speaker honoraria from Astellas, Amgen, Bayer, Sanofi, Janssen, and Ipsen; has participated in trials for Astellas, Janssen, and Bayer; has received fellowship and travel grants from Astellas, Amgen, Bayer, Sanofi, Janssen, Ipsen, and Pfizer; and has received grant and research support from Astellas, Bayer, and Janssen. Matveev has received company speaker honoraria from Sanofi and Astellas, has participated in trials for Astellas, Pfizer and Novartis. Lam is a company consultant for and has received company speaker honoraria from Pfizer, GSK, Astellas, and Ipsen. van der Poel is a company consultant for Intuitive Surgical, has participated in trials for Astellas and Steba Biotech, and has received grant and research support from Astellas. Rouvière is a company consultant for EDAP-TMS, Bracco, and Philips; has received company speaker honoraria from EDAP-TMS, Bracco, and Philips; and has participated in trials for EDAP-TMS and Bracco. Wiegel has received company speaker honoraria from Astellas, Takeda, Hexal, Ipsen, Janssen-Cilac, and Ferring. Mottet has received grant and research support from Takeda Pharmaceutical, Millenium, Astellas, Pierre Fabre, Sanofi, and Pasteur, and has received honoraria or consultation fees from Takeda Pharaceutical, Millenium, Jansen, Astellas, BMS, Bayer, Ipsen, Ferring, Novartis, Nuclétron, Pierre Fabre, Sanofi, and Zeneca. van den Bergh, Van den Broeck, Cumberbatch, Fossati, Gross, Henry, van der Kwast, Sylvester, Yuan, Schoots, Moldovan, and Marconi have nothing to disclose.
Funding/Support and role of the sponsor: None.
A correlation with radical prostatectomy specimens has demonstrated that multiparametric magnetic resonance imaging (mpMRI) has excellent sensitivity in detecting prostate cancer (PCa) with a Gleason score of ≥7 1 2 3 . As a result, prostate mpMRI is increasingly used in patients with a suspicion of PCa to localise abnormal areas before biopsy. A large body of literature has shown that targeted biopsies of suspicious lesions seen on mpMRI (TBx) improved the detection of clinically significant PCa (csPCa), at least in the repeat biopsy setting 4 5 6 . As a result, it is now recommended that an mpMRI is performed before repeat biopsy to allow TBx of suspicious lesions in addition to standard biopsies [7] .
Some authors have recently suggested that, besides improving csPCa detection, mpMRI could also be used as a triage test so that patients with negative mpMRI findings could obviate biopsy. Such a strategy remains highly controversial [8] and depends upon the negative predictive value (NPV) of mpMRI. Therefore, the European Association of Urology Prostate Cancer Guidelines Panel undertook this systematic review and meta-analysis to assess the NPV of mpMRI in patients with a suspicion of PCa and, thus, its potential role in eliminating unnecessary prostate biopsy.
Our primary aim was to systematically evaluate the performance of negative prebiopsy prostate mpMRI in predicting a negative biopsy result for overall PCa and csPCa in biopsy-naïve men and in men with previously negative biopsies. A further objective was to explore and define factors that may contribute to relevant thresholds in order to provide guidance for future studies.
The review was performed according to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) statement [9] . The review protocol was published in PROSPERO database ( http://www.crd.york.ac.uk/PROSPERO; registration number CRD42015021929). Databases searched included the Embase and OVID Medline databases, the Cochrane database of systematic reviews, and the Cochrane Central Register for Clinical Trials, covering from January 1, 2000 to February 13, 2016. Systematic or standard prostate biopsies were used as reference standards, with positive or negative cases of PCa being determined by histopathological examination. The detailed search strategy is presented in Supplement 1.
Included studies focused on men who were assessed for suspected PCa by mpMRI before undergoing prostate biopsy. Studies enrolling both biopsy-naïve men and men who had undergone previous negative biopsies were included. Prebiopsy prostate mpMRI was considered the index test and comprised T2-weighted imaging (T2WI) and at least one functional imaging technique (diffusion-weighted imaging [DWI], dynamic contrast-enhanced imaging [DCEI], or magnetic resonance spectroscopic imaging [MRSI]). For inclusion, studies had to report on false negatives and true negatives, in order to calculate NPV (ie, results of systematic/standard prostate biopsies when the mpMRI was negative). When available, false positive and true positive findings were also noted to calculate the positive predictive value (PPV) and the cancer prevalence. There was restriction neither on the biopsy technique (transrectal or transperineal) nor on the number of biopsy cores. Studies using radical prostatectomy specimens as reference standards were excluded, as were studies evaluating men with histologically proven PCa. Studies with less than 50 participants were excluded. No language restrictions were applied.
Two reviewers (P.C.M. and T.V.D.B.) independently screened all abstracts and full-text articles for eligibility. Disagreement was resolved by consensus or reference to an independent third party (L.M.). All screening was performed using a predefined eligibility form.
Using a data extraction form developed a priori, the same two reviewers independently extracted data concerning study methodology, patient characteristics, technical characteristics of the MR scanners, mpMRI protocol, mpMRI scoring system, definition of positive mpMRI, biopsy protocol, and definition of csPCa. Any discrepancies concerning data extraction were resolved by consensus or reference to an independent arbiter (O.R. or T.B.L.).
To assess the risk of bias (RoB), all included reports were reviewed using the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool for diagnostic accuracy studies [10] .
Outcome data regarding false negative and true negative values of mpMRI before prostate biopsy were recorded as reported by authors. When not available, data were indirectly derived from specificity, sensitivity, and prevalence values reported by authors using an online Bayesian statistics calculator ( http://www.medcalc.com/bayes.html ). Descriptive statistics were used to summarise baseline characteristics and outcomes, including median and interquartile range (IQR) for estimates of NPV across studies. A correlation between mpMRI NPV and a positive biopsy rate was established using the Pearson's correlation coefficient.
A meta-analysis was undertaken to calculate pooled NPV and PPV. To ensure appropriate clinical homogeneity of the studies included in the meta-analysis, we selected only the studies enrolling biopsy-naïve patients and/or patients with a history of negative biopsy, and fulfilling the following criteria that were defined a priori: (1) reference standard consisting of prostate biopsy with at least 10 samples on all patients; (2) mpMRI protocol comprising at least T2WI and DWI; (3) mpMRI results presented as a five-level score, using a subjective Likert scale or the Prostate Imaging Reporting Data System (PI-RADS) score [11] ; (4) definition of positive mpMRI as a score ≥3/5 or ≥4/5; and (5) results reported on a per patient basis. In addition, only studies defining csPCa as Gleason ≥7 cancers were selected for the meta-analysis assessing the mpMRI NPV for csPCa. A bivariate random-effects approach was employed using the Midas package in Stata 12 (StataCorp LP, College Station, TX, USA). Since the NPV decreases and the PPV increases as the prevalence increases, post-test probability estimates of NPV and PPV were reported for the given values of the prevalence based on Bayes’ theorem.
For other studies not included in the meta-analysis based on the criteria described above, a narrative synthesis of the data was performed. To explore and define clinical heterogeneity, subgroups were analysed at patient level based on the following variables: biopsy-naïve versus previous negative biopsy; patients with positive versus negative digital rectal examination (DRE); mpMRI performed with an endorectal versus without an endorectal coil; transrectal ultrasound (TRUS) versus template transperineal (TTP) biopsy approach; and ≤16 cores versus >16 cores as the reference standard. Studies reporting mpMRI NPV for patients with a prostate-specific antigen (PSA) level of ≤10 ng/ml were also reported separately.
The study selection process is depicted in the PRISMA flow diagram ( Fig. 1 ). A total of 2980 abstracts were retrieved. After abstract screening and removal of duplicates, 240 articles were eligible for full text screening, of which 48 studies were eligible for inclusion 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 .
Out of the 48 included studies, 42 were single-centre and six were multicentre studies. Thirty-four studies were prospective and six were retrospective, whilst the design of the rest was unclear. RoB assessment using QUADAS-2 was performed for each of the individual studies ( Fig. 2 A and B). Overall, the RoB was highly heterogeneous across studies for all criteria, except for the reference standard domain, in which RoB was low in most studies.
The 48 studies comprised a total of 9613 men who underwent prostate mpMRI followed by biopsy. The study and patient baseline characteristics are presented in Table 1 . The patient population consisted of biopsy-naive men in nine studies, men with at least one previous negative biopsy in 16 studies, and both biopsy-naïve men and men with a history of previous negative biopsy in nine studies. In 14 studies, the biopsy history of the patients was unclear.
Study | Study design | Period | Population | Pt Nb | Mean/median* age (yr) | Mean/median* PSA (ng/ml) | Mean/median* prostate volume (cm 3 ) | Magnetic field strength | MR pulse sequences | Endorectal coil | MR score | Definition of positive MRI | Reference standard |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Hauth (2015) [25] | Prospective | 2011–2013 | FB | 94 | 64 (43–83) | 9 (3–31) | 51 (17–140) | 1.5 T | T2WI/DWI/DCEI/MRSI | No | PI-RADS v1 | ≥3 | 11–13-core TRUS SBx + TBx |
Lamb (2015) [36] | Retrospective | 2013–2013 | FB & PNB | 173 | NR | NR | NR | 1.5 T | T2WI/DWI | NR | NR | NR | 12-core TRUS SBx |
Brock (2015) [15] | Prospective | 2013–2014 | PNB | 168 | 64* (IQR 59–70) | 9.2* (IQR 6.7–13.4) | 55.4* (IQR 42–80) | 3 T | T2WI/DWI/DCEI | No | PI-RADS v1 | NR | 12/24-core TRUS SBx + TBx |
Grenabo Bergdahl (2016) [22] | Prospective | 2013–2014 | FB & PNB | 83 | 69.3* (IQR 69–69.6) | 1.6* (IQR 0.9–2.7) | NR | 3 T | T2WI/DWI/DCEI/MRSI | No | PI-RADS v1 | ≥3 | 10-core TRUS SBx + TBx |
Wang (2015) [58] | Prospective | 2002–2009 | FB & PNB | 586 | 70 (26–91) | 11.11* (0.02–9794) | NR | 1.5 T | T2WI/DWI/DCEI/MRSI | Yes | PI-RADS v1 | ≥3 | TRUS SBx |
Pepe (2015) [41] | Prospective | 2011–2014 | PNB | 100 | 64* | 8.6* (4.2–10) | NR | 3 T | T2WI/DWI/DCEI/MRSI | No | PI-RADS v1 | ≥4 | TPBx + TBx |
Panebianco (2015) [39] | Prospective | 2011–2014 | FB (61.62%) & PNB (38.34%) | 925 (1140 total cohort) |
NR | NR | NR | 3 T | T2WI/DWI/DCEI | Yes | PI-RADS v1 | NR | 14-core TRUS SBx; 45-core sat TPBx + TBx |
Radtke (2015) [46] | Prospective | 2013–2013 | FB (63.3%) & PNB (36.7%) | 294 | 64* (60–71) | 7.3 (6.0) | 47 (37.5) | 3 T | T2WI/DWI/DCEI | No | PI-RADS v1 | PI-RADS ≥2; PI-RADS ≥3; PI-RADS ≥4; PI-RADS = 5; |
24-core TPBx + TBx |
Itatani (2014) [27] | Retrospective | 2004–2007 | NR | 193 | 68.9 (8.4); 70* (47–89) | 11.8 (15.9); 7.9* (1.22–159) | NR | 1.5 T | T2WI/DWI/DCEI | No | 1–5 scale (Likert) | ≥3 | 12–14-core TRUS SBx |
Porpiglia (2014) [44] | Prospective | 2011–2013 | PNB | 170 | 65* (60–70) | 6.9* (5.2–9.8) | 42* (36–48) | 1.5 T | T2WI/DWI/DCEI | Yes | Dichotomous | Positive: at least 2/3 MR seq. with suspicious findings | 18–24-core TRUS SBx (volume dependent) |
Thompson (2014) [56] | Prospective | 2012–2013 | FB (88%) & PNB (12%) | 150 | 62.4* (IQR 55.0–66.4) | 5.6* (IQR 4.5–7.5) | 40* (IQR 30–57) | 1.5 T (47%) & 3 T (53%) | T2WI/DWI/DCEI | No | PI-RADS v1 | ≥3 | Median of 30 TPBx (volume dependent) |
Pokorny (2014) [43] | Prospective | 2012–2013 | FB | 223 | 63* (IQR 57–68) | 5.3* (IQR 4.1–6.6) | 41* (IQR 30–59) | 3 T | T2WI/DWI/DCEI | No | PI-RADS v1 | ≥3 (primary); ≥4 |
12-core TRUS SBx + TBx |
Petrillo (2014) [42] | Prospective | 2009–2010 | NR | 136 | NR | NR | NR | 1.5 T | T2WI/DWI/MRSI | Yes | 1–5 scale (Likert) | ≥3 | 12–16-core TRUS SBx (volume + PSA dependent) |
Javali (2014) [29] | Retrospective | 2002–2011 | NR | 140 | Control: 62.4 (10.5); Study: 62.9 (12.1) | Control: 6.8 (2.3); Study: 6.87 (2.6) | Control: 44 (14.2); Study: 43 (18.4) | 1.5 T | T2WI/MRSI | Yes | Dichotomous | Cit/[Cho + Cr] < 1.2 | 6-core TRUS SBx ( n = 69), 12-core TRUS SBx ( n = 119) |
Abd-Alazeez (2014) [13] | Prospective | 2007–2011 | FB | 129 | 62* (41–82) | 5.8* (1.2–20) | 40* (16–137) | 1.5 & 3 T | T2WI/DWI/DCEI | No | PI-RADS v1 | ≥3 (primary); ≥4 |
20-core TPBx |
Abd-Alazeez (2014) [12] | Retrospective | NR | PNB | 54 | 64* (39–75) | 10* (2–23) | 53* (19–136) | 1.5 & 3 T | T2WI/DWI/DCEI | No | PI-RADS v1 | ≥3 (primary); ≥4 |
≥20-core TPBx + TBx ( n = 15) |
Matsuoka (2014) [37] | Prospective | 2007–2012 | NR | 135 | 67* (50–80) | 7.0* (2.9–19.8) | 25.4* (12.7–90.2) | 1.5 T | T2WI/DWI | No | 1–5 scale (Likert) | ≥3 | 14-core TRUS SBX |
Junker (2013) [30] | Retrospective | 2011–2013 | PNB | 73 | 62 (7.4) | 7.0* (5.1–12.9) | 45* (34–61) | 3 T | T2WI/DWI/DCEI | No | PI-RADS | PI-RADS ≥10 and ≥11 for all PCa PI-RADS ≥13 for significant PCa |
10-core TRUS SBx + TBx |
Busetto (2013) [16] | Prospective | 2010–2012 | PNB | 163 | 66.4 (5.3) | 6.8 (1.6) | NR | 3 T | T2WI/DWI/DCEI/MRSI | Yes | NR | NR | 10-core TRUS SBx + TBx |
Rais-Bahrami (2013) [47] | Prospective | 2007–2012 | NR | 583 | 61.3 (8.4) | 9.9 (13.1) | NR | 3 T | T2WI/DWI/DCEI/MRSI | Yes | 1–4 scale (Likert) | ≥2 ≥3 |
12-core TRUS SBx + TBx |
Kuru (2013) [34] | Prospective | 2010–2011 | FB (51%) & PNB (49%) | 347 | 65.3 (42–82) | 9.85 (0.5–104) | 48.7 (9–180) | 3 T | T2WI/DWI/DCEI | No | 1–3 scale (Likert) | ≥2 | 12–36-core TRUS SBx (volume dependent) + TBx |
Ferda (2013) [20] | Prospective | NR | NR | 164 | (49–74) | (4.2–123) | NR | 3 T | T2WI/DWI/DCEI/MRSI | No | NR | In house | TRUS SBx |
Ganie (2013) [21] | NR | 2007–2009 | PNB | 87 | NR | NR | NR | 1.5 T | T2WI/MRSI | Yes | MRSI Cho/Cit ratio | In house | 6 core TRUS SBx + MRI TBx |
Vinet (2013) [57] | Prospective | 2009–2011 | FB | 69 | NR | 5.2* (3.2–28) | NR | 1.5 T (35 pts) & 3 T (34 pts) | T2WI/DWI/DCEI | No | 1–5 scale (Likert) | ≥3 | 12-core TRUS SBx + TBx |
Numao (2013) [38] | Prospective | 2006–2010 | FB | 351 | 65* (59–70) | 6.3* (4.9–9.1) | 32* (24–42) | 1.5 T | T2WI/DWI/DCEI (no DCEI in 42 pts) | No | 1–5 scale (Likert) | ≥3 | 3D 26-core (12 TRUS SBx + 14 TPBx – 203 pts); 3D 14-core (6 TRUS SBx + 8 TPBx – 102 pts); TPBx 14 core (46 pts) |
Belas (2012) [14] | Prospective | 2010–2011 | FB | 71 | 66* (47–76) | 7* (4–10) | 45* (15–150) | 1.5 T | T2WI/DWI/DCEI | No | TZ: 0–4 scale PZ: 0–10 scale |
TZ: >2 PZ: >6 |
12-core TRUS SBx + TBx |
Ibrahiem (2012) [26] | Prospective | 2008–2009 | FB | 100 | 65.03 (7.13) | 26.3 (24.2) | 60.09 (28.7) | 1.5 T | T2WI/DWI | No | NR | In house | 12-core TRUS SBX |
Sciarra (2012) [51] | Prospective | 2008–2011 | PNB | 84 | 64.09 (46–76) | 7.07 (4.2–15.5) | NR | 3 T | T2WI/DWI/DCEI/MRSI | Yes | NR | NR | 10-core TRUS Bx + TBx |
Portalez (2012) [45] | Prospective | 2011 | PNB | 129 | 64.7 (47–79) | 9.6 (2.7–40) | 51.1 (12–192) | 1.5 T | T2WI/DWI/DCEI | Mixed | 1–5 scale (Likert) PI-RADS |
Likert ≥3 PI-RADS ≥9 |
10–12-core TRUS SBx + TBx |
Watanabe (2012) [59] | Prospective | 2004–2008 | NR | 1448 | 72 (7.5) | NR | NR | 1.5 T | T2WI/DWI | No | NR | ADC value ≤1.35 × 10 −3 mm 2 /s | 8-core TRUS SBx + TBx |
Tamada (2011) [54] | Retrospective | 2006–2009 | NR | 50 | 70 (40–84) | 6.84* (4.06–9.94) | NR | 1.5 T | T2WI/DWI/DCEI | No | NR | In house | 12-core TRUS SBx |
Choi (2011) [18] | NR | 2009–2010 | NR | 51 | 67.16 (56–90) | 14.16 (1.02–38.9) | 42.98 (13.8–77.3) | 3 T | T2WI/DWI | NR | NR | NR | 10–12-core TRUS SBx + TBx |
Iwazawa (2011) [28] | Retrospective | 2008–2009 | NR | 178 | 68.8 (41–86) | 20.51 (4.04–568.5) | NR | 1.5 T | T2WI/DWI/DCEI | NR | 1–4 scale (Likert) | NR | 10–12-core TRUS SBx (TBx included in SBx chart) |
Rouse (2011) [48] | Prospective | 2005–2007 | PNB | 114 | 63.6 (41–83) | 13.4 (0–228) | NR | 1.5 T | T2WI/DWI/DCEI | NR | 1–5 scale (Likert) | ≥3 | TRUS SBx |
Haffner (2011) [23] | Prospective | 2005–2009 | FB | 555 | 64* (47–83) | 6.75* (0.18–100) | 46* (15–200) | 1.5 T | T2WI/DCEI | No | 1–5 scale (Likert) | ≥3 | 10-core TRUS SBx + TBx |
Panebianco (2010) [40] | Prospective | 2007–2009 | PNB | 150 | 61.2 (46–78) | 9.42 (3.91) | 41.17 (7.47) | 1.5 T | T2WI/DCEI/MRSI | Yes | NR | In house | 10-core TRUS SBx (TBx included in SBx chart) |
Roy (2010) [49] | Not specified | 2011–2009 | FB (53%) & PNB (47%) | 103 | 63 (52–78) | 7* | NR | 3 T | T2WI/DWI/DCEI | Yes | NR | NR | 8-core TRUS SBx + TBx |
Testa (2010) [55] | Not specified | 2007 | PNB | 54 | 63.9 (52–76) | 11.4 (3–42) | 59.3 (30–150) | 1.5 T | T2WI/MRSI | Yes | 1–3 scale (Likert) | ≥2 | 12-core TRUS SBx + TBx |
Sciarra (2010) [52] | Prospective | 2007–2009 | PNB | 110 | 63.5 (49–74) | NR | NR | 1.5 T | T2WI/DCEI/MRSI | Yes | NR | In house | 10-core TRUS SBx + TBx |
Kitajima (2010) [31] | Prospective | 2008–2009 | NR | 53 | 69* (56–84) | 11.1* (4.2–112.1) | NR | 3 T | T2WI/DWI/DCEI | No | 1–5 scale (Likert) | ≥3 | 20-core TPBx |
Labanaris (2010) [35] | Prospective | 2004–2008 | PNB | 260 | NR | NR | NR | 1 T | T2WI/DWI/DCEI | Yes | Dichotomous | In house | 18-core TRUS SBx |
Kumar (2009) [32] | NR | NR | NR | 61 | 65.3 (9.3) | 16.5 (0.21–155) | NR | 1.5 T | T2WI/MRSI | Yes | NR | (Cit/(Cho + Cr) ≤ 1.2 | TRUS Bx |
Schmuecking (2009) [50] | NR | NR | FB & PNB | 67 | 68 | 11.5 | NR | 1.5 T | T2WI/DCEI | No | NR | NR | 20-core Bx |
Cheikh (2009) [17] | Retrospective | 2005–2008 | PNB | 93 | 63.2 (52–74) | 9.63 (1.6–40) | NR | 1.5 T | T2WI/DCEI | No | Dichotomous | In house | 12-core TRUS SBx + TBx |
Cirillo (2008) [19] | Prospective | 2004–2006 | PNB | 54 | 65.5 (5.2) | 10.8 (7.5) | NR | 1.5 T | T2WI/MRSI | Yes | Dichotomous | In house | 10-core TRUS SBx + TBx |
Kumar (2007) [33] | Prospective | 2003–2005 | NR | 83 | NR | NR | NR | 1.5 T | T2WI/MRSI | Yes | NR | NR | 12-core TRUS SBx + TBx |
Squillaci (2005) [53] | Prospective | 2004–2005 | NR | 65 | NR | NR | NR | 1.5 T | T2WI/DCEI/MRSI | No | 1–3 scale (Likert) | ≥2 | 10-core TRUS SBx + TBx |
Hara (2005) [24] | Prospective | 2003–2004 | FB | 90 | 67.2 (NR) | NR | NR | 1.5 T | T2WI/DCEI | No | 1–3 scale (Likert) | ≥2 = 3 |
14-core TRUS SBx |
The magnetic field strength was 1, 1.5, and 3 T in one, 28, and 15 studies, respectively. Four studies used both 1.5 and 3 T MR systems. DWI and DCEI were used in 36 and 35 studies, respectively. Nineteen studies also added MRSI. An endorectal coil was used in 18 studies. The definition of positive mpMRI varied across studies. The PI-RADS v1 score was used in 12 studies, a five-level subjective (Likert) score was used in eight studies, and one study reported data based on the two scoring systems. In-house criteria were used in 13 studies for defining positive mpMRI, and five studies used a dichotomous definition. Nine studies did not report on the criteria for positive mpMRI. No study used the PI-RADS v2 score.
Regarding the reference standard, TRUS-guided biopsies were used in 39 studies, TTP biopsies in six studies, and mixed TRUS-guided and TTP biopsies in two studies. In one study, the biopsy approach was unclear. The number of cores per biopsy procedure was ≤16 in 30 studies, >16 in nine studies, and variable among patients in three studies. For six studies, the number of biopsy cores taken was unclear.
At patient level, the median biopsy positivity rate (ie, cancer prevalence) was 50.4% (IQR, 36.4–57.7%) for overall cancer and 32.9% (IQR, 28.1–37.2%) for csPCa ( Table 2 ). The median mpMRI NPV was 82.4% (IQR, 69.0–92.4%) for overall cancer and 88.1% (IQR, 85.7–92.3) for csPCa. NPV significantly decreased when cancer prevalence increased, both for overall cancer ( r = –0.64, p < 0.0001) and csPCa ( r = –0.75, p = 0.032; Fig. 3 ). In addition, NPV was highly dependent on the definition used for csPCa, with differences of up to 21% when several definitions were used in the same dataset [12 13 38 47 48] .
Study | Overall PCa prevalence (%) | Reporting level | Multiparametric MRI performance for PCa detection | Definition of csPCa | csPCa prevalence | Multiparametric MRI performance for csPCa detection | ||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
TN | FN | TP | FP | NPV | PPV | TN | FN | TP | FP | NPV | PPV | |||||
Hauth (2015) [25] | 45.7 | Patient | 6 | 1 | 42 | 45 | 85.7% | 48.3% | Low grade: GS ≤ 6 High grade: GS ≥ 7 |
NR | NR | NR | NR | NR | NR | NR |
Lesion | 59 | 13 | 55 | 73 | 81.9% | 43% | ||||||||||
Lamb (2015) [36] | 65.9 | Patient | 23 | 22 | 92 | 36 | 51.1% | 71.9% | GS ≥ 7 | 50.9% | 31 | 14 | 71 | 57 | 68.9% | 55.5% |
Brock (2015) [15] | 42.3 | Patient | 17 | 7 | 56 | 88 | 70.8% | SBx: 38.8% TBx: 22.2% Duo: 44.4% |
Epstein: GS > 6 and/or max CCL ≥50% | 24.4% | SBx: 21 | SBx: 3 | SBx: 38 TBx: 27 duo: 47 |
SBx: 106 TBx: 117 duo: 97 |
87.5% | SBx: 26.4% TBx: 18.8% duo: 32.6% |
Grenabo Bergdahl (2016) [22] | 33.7 | Patient | 36 | 7 | 19 | 21 | 83.7% | 47.5% | Clinically insignificant PCa: T1c, PSAd < 0.15, GS < 7, ≤2 positive cores, and unilateral cancer | NR | NR | NR | NR | NR | NR | NR |
Wang (2015) [58] | 58 | Patient | 165 | 8 | 332 | 81 | 95.4% | 80.4% | NR | NR | NR | NR | NR | NR | NR | NR |
Pepe (2015) [41] | 37 | Patient | 23 | 8 | 29 | 40 | 74.2% | 42% | GS ≥ 7 or GS 6 with CCL ≥ 50% | NR | NR | NR | NR | NR | 100% | 55.8% |
Panebianco (2015) [39] | 74.7 | Patient | Group A (satBx): 104 | Group A (satBx): 43 | Group A: 186 | Group A: 22 | Group A (satBx): 70.7% | Group A: 89.4% | NR | 60% | Group A: 147 | Group A: 0 | Group A: 183 | Group A: 25 | Group A: 100% | Group A: 88% |
Group B (TRUSGB NR TRUS G satBx): 93 | Group B (TRUSGB NR TRUS G satBx): 37 | Group B: 417 before and 425 after satBx | Group B: 23/440 and 15/440 after satBx. | Group B (TRUSGB–TRUS G satBx): 71.5% | Group B: 94.8% before and 96.6% after satBx | 71.9% | Group B: 130 | Group B: 0 | Group B: 410 |
Group B: 30 | Group B: 100% | Group B: 93.2% | ||||
Radtke (2015) [46] | 51 | Patient | ≥2/5: 80 ≥3: 103 ≥4: 138 = 5: 142 |
≥2/5: 18 ≥3/5: 38 ≥4/5: 78 = 5/5: 126 |
≥2/5: 132 ≥3/5: 112 ≥4/5: 72 = 5/5: 24 |
≥2/5: 64 ≥3/5: 41 ≥4/5: 6 = 5/5: 2 |
≥2/5: 81.6% ≥ 3/5: 73.1% ≥ 4/5: 63.9% = 5/5: 53% |
≥2/5: 67.4% ≥ 3/5: 73.2% ≥ 4/5: 92.3% = 5/5: 92.3% |
GS ≥ 7 | 29.3% | ≥2/5: 91 ≥3/5: 124 ≥4/5: 183 = 5/5: 203 |
≥2/5: 7 ≥3/5: 17 ≥4/5: 33 = 5/5: 65 |
≥2/5: 79 ≥3/5: 69 ≥4/5: 53 = 5/5: 21 |
≥2/5: 117 ≥3/5: 84 ≥4/5: 25 = 5/5: 5 |
≥2/5: 92.2% ≥3/5: 87.9% ≥4/5: 84.7% = 5/5: 75.8% |
≥2/5: 40.3% ≥3/5: 45.1% ≥4/5: 68% = 5/5: 80.7% |
Itatani (2014) [27] | 13 | Patient | 168 | 25 | NR | NR | 87% | NR | (1) PSAd ≥ 0.1 or GP 4/5 or ≥ 3/6 pos cores; max CCL < 50% (2) PSAd ≥ 0.15 or GP 4/5 or max core length invasion < 3 mm (min 6 cores) |
NR | NR | NR | NR | NR | NR | NR |
Porpiglia (2014) [44] | 30.6 | Patient | 107 | 5 | 47 | 11 | 95.5% | 81% | NR | NR | NR | NR | NR | NR | NR | NR |
Thompson (2014) [56] | 61.3 | Patient | 35 | 16 | 76 | 23 | 68.6% | 76.7% | Moderate or high risk Moderate risk: GS 7 (GP4 >5%) and <50% of positive cores or GS 6–7 (GP4 ≤ 5%) and either ≥30% of positive cores or max core length invasion ≥8 mm High risk: GS ≥ 7 (GP4 > 5%); ≥50% + cores or GS ≥ 8 |
34% | 49 | 2 | 49 | 50 | 96% | 49.5% |
Pokorny (2014) [43] | 63.7 | Patient | ≥3/5: 56 ≥4/5: 74 |
≥3/5: 25 ≥4/5: 40 |
≥3/5: 101 ≥4/5: 86 |
≥3/5: 41 ≥4/5: 23 |
≥3/5: 69.1% ≥4/5: 64.9% |
≥3/5: 71.1% ≥4/5: 78.9% |
NR | NR | NR | NR | NR | NR | NR | NR |
Petrillo (2014) [42] | 18.4 | Patient | 56 | 4 | 21 | 55 | 93% | 28% | NR | NR | NR | NR | NR | NR | NR | NR |
Javali (2014) [29] | 16.4 | Patient | 49 | 1 | 22 | 68 | 98% | 24.4% | NR | NR | NR | NR | NR | NR | NR | NR |
Abd-Alazeez (2014) [13] | 54.7 | Lobe | ≥3/5: 33 | ≥3/5: 14 | ≥3/5: 127 | ≥3/5: 84 | ≥3/5: 70% | ≥3/5: 60% | Def 1: GS ≥ 4 + 3 and/or max CCL ≥ 6 mm Def 2: GS ≥ 3 + 4 and/or max CCL ≥ 4 mm Def 3: GS ≥ 4 + 3 Def 4: GS ≥ 3 + 4 Def 5: max CCL ≥ 6 mm Def 6: max CCL ≥ 4 mm |
Def 1: NR Def 2: 44.2% Def 3: 23.2% Def 4: 36% Def 5: 32.9% Def 6: 39.5% |
Def 1: 46 Def 2: 42 Def 3: 47 Def 4: 43 Def 5: 46 Def 6: 43 |
Def 1: 1 Def 2: 5 Def 3: 0 Def 4: 4 Def 5: 1 Def 6: 4 |
Def 1: 45 Def 2: 72 Def 3: 13 Def 4: 50 Def 5: 39 Def 6: 59 |
Def 1: 166 Def2: 139 Def 3: 198 Def 4: 161 Def 5: 172 Def 6: 152 |
Def 1: 98 Def 2: 89 Def 3: 100 Def 4: 92 Def 5: 98 Def 6: 91 |
Def 1: 21 Def 2: 34 Deg 3: 6 Def 4: 24 Def 5: 19 Def 6: 28 |
≥4/5: 87 | ≥3/5: 62 | ≥3/5: 79 | ≥3/5: 30 | ≥3/5: 58% | ≥3/5: 73% | Def 1: 140 Def 2: 124 Def 3: 148 Def 4: 133 Def 5: 141 Def 6: 131 |
Def 1: 9 Def 2: 25 Def 3: 1 Def 4: 16 Def 5: 8 Def 6: 18 |
Def 1: 37 Def 2: 52 Def 3: 12 Def 4: 38 Def 5: 32 Def 6: 45 |
Def 1: 72 Def 2: 57 Def 3: 97 Def 4: 71 Def 5: 77 Def 6: 64 |
Def 1: 94 Def 2: 83 Def 3: 99 Def 4: 89 Def 5: 95 Def 6: 88 |
Def 1: 34 Def 2: 48 Def 3: 11 Def 4: 35 Def 5: 30 Def 6: 42 |
|||||
Abd-Alazeez (2014) [12] | 47.2 | Lobe | ≥3/5: 26 | ≥3/5: 13 | ≥3/5: 38 | ≥3/5: 31 | ≥3/5: 66% | ≥3/5: 55% | Def 1: GS ≥ 4 + 3 and/or max CCL ≥ 6 mm Def 2: GS ≥ 3 + 4 and/or max CCL ≥ 4 mm Def 3: GS ≥ 4 + 3 Def 4: GS ≥ 3 + 4 Def 5: max CCL ≥ 6 mm Def 6: max CCL ≥ 4 mm |
Def 1: 18.5% Def 2: 31.5% Def 3: 4.6% Def 4: 21.3% Def 5: 16.7% Def 6: 25% |
Def 1: 37 Def 2: 31 Def 3: 39 Def 4: 36 Def 5: 37 Def 6: 32 |
Def 1: 2 Def 2: 8 Def 3: 0 Def 4: 3 Def 5: 2 Def 6: 7 |
Def 1: 18 Def 2: 26 Def 3: 5 Def 4: 20 Def 5: 16 Def 6: 20 |
Def 1: 51 Def 2: 43 Def 3: 64 Def 4: 49 Def 5: 53 Def 6: 49 |
Def 1: 95 Def 2: 79 Def 3: 100 Def 4: 92 Def 5: 95 Def 6: 82 |
Def 1: 26 Def 2: 38 Def 3: 7 Def 4: 29 Def 5: 23 Def 6: 29 |
≥4/5: 49 | ≥4/5: 25 | ≥4/5: 26 | ≥4/5: 8 | ≥4/5: 66% | ≥4/5: 76% | Def 1: 70 Def 2: 63 Def 3: 73 Def 4: 68 Def 5: 70 Def 6: 64 |
Def 1: 4 Def 2: 11 Def 3: 1 Def 4: 6 Def 5: 4 Def 6: 10 |
Def 1: 16 Def 2: 23 Def 3: 4 Def 4: 17 Def 5: 14 Def 6: 17 |
Def 1: 18; Def 2: 11 Def 3: 30 Def 4: 17 Def 5: 20 Def 6: 17 |
Def 1: 94 Def 2: 85 Def 3: 99 Def 4: 92 Def 5: 94 Def 6: 86 |
Def 1: 47 Def 2: 67 Def 3: 12 Def 4: 50 Def 5: 41 Def 6: 49 |
|||||
Matsuoka (2014) [37] | 64.8 | Lobe | 46 | 49 | 149 | 26 | 48.4% | 85.1% | NR | NR | NR | NR | NR | NR | NR | NR |
Junker (2013) [30] | 53.4 | Patient | ≥10/15: 21 ≥11/15: 28 |
≥10/15: 4 ≥11/15: 12 |
≥10/15: 35 ≥11/15: 27 |
≥10/15: 13 ≥11/15: 6 |
≥10/15: 84% ≥11/15: 70% |
≥10/15: 72.9% ≥11/15: 81.8% |
GS ≥ 4 + 3 | 13.7% | ≥13: 54 | ≥13: 2 | ≥13: 8 | ≥13: 9 | ≥13: 96.4% | ≥13: 47% |
Busetto (2013) [16] | 41.7 | Patient | 59 | 7 | 61 | 36 | 89% | 63% | NR | NR | NR | NR | NR | NR | NR | NR |
Rais-Bahrami (2013) [47] | 54.2 | Patient | ≥2/4 : 80 | ≥2/4: 275 | ≥2/4: 187 | ≥2/4: 275 | ≥2/4: 66% | ≥2/4: 59% | GS ≥ 7: GS ≥ 8 |
31.7% | NR | NR | NR | NR | GS ≥ 7: 91% GS ≥ 8: 91% |
GS ≥ 7: 38% GS ≥ 8: 18% |
≥3/4: 251 | ≥3/4: 76 | ≥3/4: 16 | ≥3/4: 76 | ≥3/4: 51% | ≥3/4: 82% | NR | NR | NR | NR | GS ≥ 7: 75% GS ≥ 8: 91% |
GS ≥ 7: 67% GS ≥ 8: 41% |
|||||
Kuru (2013) [34] | 57.6 | Patient | 80 | 14 | 67 | 186 | 85.1% | 73.5% | NR | NR | NR | NR | NR | NR | NR | NR |
Ferda (2013) [20] | 51.2 | Patient | 52 | 2 | 82 | 28 | 96.3% | 74.5% | NR | NR | NR | NR | NR | NR | NR | NR |
Ganie (2013) [21] | 74.7 | Patient | 13 | 3 | 62 | 9 | 59.1% | 95.4% | NR | NR | NR | NR | NR | NR | NR | NR |
Vinet (2013) [57] | 49.3 | Patient | ≥3/5: 11 | ≥3/5: 6 | ≥3/5: 28 | ≥3/5: 24 | ≥3/5: 64.7% | ≥3/5: 53.8% | NR | NR | NR | NR | NR | NR | NR | NR |
≥4/5: 22 | ≥4/5: 11 | ≥4/5: 23 | ≥4/5: 13 | ≥4/5: 66.7% | ≥4/5: 63.8% | NR | NR | NR | NR | NR | NR | NR | NR | |||
Numao (2013) [38] | 45 | Patient | 137 | 57 | 101 | 56 | 70.6% | 64.3% | Def 1: GS ≥4 + 3 and/or ≥20% positive cores and/or max CCL ≥5 mm Def 2: GS ≥ 3 + 4 and/or ≥20% + cores and/or max CCL ≥5 mm Def 3: GS ≥ 3 + 4 and/or ≥20% + cores |
Def 1: 33.3% Def 2:37.8% Def 3: 35.8% |
Def 1: 74 Def 2: 65 Def 3: 69 |
Def 1: 83 Def 2: 92 Def 3: 88 |
Def 1: 160 Def 2: 153 Def 3: 156 |
Def 1: 34 Def 2: 41 Def 3: 38 |
Def 1: 82.4% Def 2: 78.8% Def 3: 80.4% |
Def 1: 58.8% Def 2: 58.5% Def 3: 56% |
Belas (2012) [14] | 53.5 | Patient | 22 | 12 | 23 | 13 | 64.7% | 63.8% | NR | NR | NR | NR | NR | NR | NR | NR |
Ibrahiem (2012) [26] | 73.9 | Patient | 14 | 11 | 57 | 10 | 56% | 85.1% | NR | NR | NR | NR | NR | NR | NR | NR |
Sciarra (2012) [51] | 34.5 | Patient | 41 | 4 | 25 | 14 | 91.1% | 64.1% | NR | NR | NR | NR | NR | NR | NR | NR |
Portalez (2012) [45] | 48.1 | Lesion | Likert: 357 | Likert: 50 | Likert: 81 | Likert: 50 | Likert: 95% | Likert: 38% | Max CCL >3 mm and/or GG 4/5 | NR | NR | NR | NR | NR | NR | NR |
PI-RADS: 404 | PI-RADS: 47 | PI-RADS: 34 | PI-RADS: 47 | PI-RADS: 95% | PI-RADS: 58% | |||||||||||
Watanabe (2012) [59] | 48.1 | Patient | 485 | 73 | 624 | 266 | 86.9% | 70.1% | NR | NR | NR | NR | NR | NR | NR | NR |
Tamada (2011) [54] | 70 | Patient | 12 | 6 | 29 | 3 | 67% | 91% | NR | NR | NR | NR | NR | NR | NR | NR |
Region | 277 | 48 | 55 | 20 | 85% | 73% | ||||||||||
Choi (2011) [18] | 70.6 | Patient | 9 | 5 | 31 | 6 | 64.2% | 75.7% | NR | NR | NR | NR | NR | NR | NR | NR |
Iwazawa (2011) [28] | 40.5 | Region | 887 | 86 | 232 | 219 | 91.1% | 51.4% | NR | NR | NR | NR | NR | NR | NR | NR |
Rouse (2011) [48] | 33.7 | Sextant | 145 | 11 | 74 | 22 | 92.9% | 77.1% | GS ≥ 7: Def 1: ≥3 mm Def 2: ≥5 mm |
Def 1: 26.6% Def 2: 26.2% |
Def 1: 153 Def 2: 153 |
Def 1: 3 Def 2: 3 |
Def 1: 64 Def 1: 63 |
Def 1: 32 Def 2: 33 |
Def 1: 98.1% Def 2: 98.1% |
Def 1: 68.1% Def 2: 67% |
59.6 | Patient | 24 | 14 | 54 | 22 | 63.2% | 71.1% | Def 1: 41.2% Def 2: 36.8% |
Def 1: 30 Def 2: 31 |
Def 1: 4 Def 2: 3 |
Def 1: 43 Def 2: 39 |
Def 1: 4 Def 2: 3 |
Def 1: 88.2% Def 2: 91.2% |
Def 1: 53.8% Def 2: 48.8% |
||
Haffner (2011) [23] | 54.4 | Patient | 154 | 50 | 240 | 111 | 75.4% | 68.3% | NR | NR | NR | NR | NR | NR | NR | NR |
Panebianco (2010) [40] | 42.7 | Patient | NR | NR | NR | NR | 95.1% | 88.2% | NR | NR | NR | NR | NR | NR | NR | NR |
Roy (2010) [49] | 55.9 | Patient | NR | NR | NR | NR | 71% | 75% | NR | NR | NR | NR | NR | NR | NR | NR |
Testa (2010) [55] | 40.7 | Patient | NR | NR | NR | NR | 79.3% | 64% | NR | NR | NR | NR | NR | NR | NR | NR |
Sciarra (2010) [52] | 50 | Patient | 61 | 4 | 66 | 9 | 93.8% | 88% | NR | NR | NR | NR | NR | NR | NR | NR |
Kitajima (2010) [31] | 56.6 | Patient | 311 | 19 | 80 | 14 | 92.2% | 85.1% | NR | NR | NR | NR | NR | NR | NR | NR |
Labanaris (2010) [35] | 73.9 | Patient | 17 | 73 | 96 | 74 | 81.11% | 56.47% | NR | NR | NR | NR | NR | NR | NR | NR |
Kumar (2009) [32] | 21.7 | Patient | 39 | 3 | 10 | 8 | 92.8% | 55% | NR | NR | NR | NR | NR | NR | NR | NR |
Schmuecking (2009) [50] | NR | Lobe | NR | NR | NR | NR | 96% | 61% | NR | NR | NR | NR | NR | NR | NR | NR |
Cheikh (2009) [17] | 24.7 | Patient | 36 | 12 | 11 | 34 | 80% | 22.9% | NR | NR | NR | NR | NR | NR | NR | NR |
Cirillo (2008) [19] | 31.5 | Patient | 19 | 0 | 17 | 18 | 100% | 48.6% | NR | NR | NR | NR | NR | NR | NR | NR |
Kumar (2007) [33] | 13.3 | Patient | 39 | 0 | 11 | 33 | 100% | 25% | NR | NR | NR | NR | NR | NR | NR | NR |
Squillaci (2005) [53] | 50.8 | Patient | 29% | 8% | 25% | 3% | 89% | 80% | NR | NR | NR | NR | NR | NR | NR | NR |
Hara (2005) [24] | 41.5 | Patient | ≥2/3: 40 = 3/3: 47 |
≥2/3: 4 = 3/3: 8 |
≥2/3 30 = 3/3: 26 |
≥2/3: 8 = 3/3: 1 |
≥2/3: 90% = 3/3: 85% |
≥2/3: 78.9% = 3/3: 96.3% |
NR | NR | NR | NR | NR | NR | NR | NR |
Cancer prevalence tended to be higher and mpMRI NPV lower in the biopsy-naïve group as compared with the repeat biopsy group, in men with positive DRE as compared with men with negative DRE and when an endorectal coil was not used ( Table 3 ). There were no clear differences in the prevalence and NPV of the other analysed subgroups (TRUS-guided vs TTP biopsy, biopsy procedures with ≤16 cores vs >16 cores; Table 3 ). However, comparisons must be interpreted with care, due to the small number of studies in some subgroups. In patients with a PSA level of ≤10 ng/ml, the median NPV for overall PCa was 86.3% (IQR, 73.3–93.6%) for a median cancer prevalence of 35.4% (IQR, 27.6–42.5%).
Nb of studies | Median PCa prevalence | Median mpMRI NPV | Nb of studies | Median csPCa prevalence | Median mpMRI NPV | |
---|---|---|---|---|---|---|
Biopsy-naïve patients | 8 | 51.4% (45.5–56.7) | 69.9% (64.2–78) | 1 | 35.8% (NA) | 80.4% (NA) |
Repeat biopsy | 14 | 42% (35.1–52.6) | 82.6% (75.5–93.1) | 3 | 24.4% (19.1–32.8) | 88.2% (87.9–92.3) |
TRUS-guided biopsy | 36 | 49.7% (34.3–57.7) | 84.6% (68.6–92.8) | 4 | 28.1% (21.7–36.5) | 89.3% (82.9–92.4) |
TTP biopsy | 4 | 53.8% (47.5–57.8) | 73.6% (72–78.7) | 2 | 31.6% (30.5–32.8) | 92% (89.9–94) |
Biopsy with ≤16 cores | 28 | 48.7% (39.2–54.8) | 81.9% (66.8–89.3) | 5 | 28.1% (21.8–36.5) | 89.3% (82.9–92.4) |
Biopsy with >16 cores | 5 | 56.6% (51–61.3) | 81.1% (73.1–92.2) | 2 | 31.7% (30.5–32.8) | 92% (89.9–93.9) |
Positive DRE | 1 | 73.9% (NA) | 56% (NA) | 0 | – | – |
Negative DRE | 6 | 36% (34.6–46.8) | 82.7% (74.2–93.1) | 0 | – | – |
Endorectal coil | 17 | 41.7% (30.6–55.9) | 92.8% (79.3–95.4) | 1 | 31.7% (NA) | 91% (NA) |
No endorectal coil | 22 | 50.9% (41.7–56.1) | 77.7% (69.5–86.6) | 7 | 34% (26.9–46.1%) | 87.9% (78.2–92.1) |
Eight studies reported NPV at patient level for overall PCa and fulfilled the inclusion criteria for meta-analysis ( Table 4 ) [22 25 38 41 43 46 56 57] .
Study | Prevalence a (%) | Neg MRI (%) | NPV (%) | PPV (%) | Spe (%) | Se (%) | ||
---|---|---|---|---|---|---|---|---|
All PCa | Score ≥ 3/5 | Grenabo Bergdahl (2016) [22] | 31.3 | 66.9 | 83.7 | 47.5 | 63.2 | 73.1 |
Numao (2013) [38] | 45 | 29.4 | 70.6 | 64.3 | 71.0 | 63.9 | ||
Hauth (2015) [25] | 45.7 | 14.3 | 85.7 | 48.3 | 11.8 | 97.7 | ||
Vinet (2013) [57] | 49.3 | 24.6 | 64.7 | 53.8 | 31.4 | 82.4 | ||
Radtke (2015) [46] | 51 | 27 | 73 | 73.2 | 71.5 | 74.7 | ||
Thompson (2014) [56] | 61.3 | 31.4 | 68.6 | 76.8 | 60.3 | 82.6 | ||
Pokorny (2014) [43] | 63.7 | 30.9 | 69.1 | 82.4 | 69.1 | 82.4 | ||
Score ≥ 4/5 | Pepe (2015) [41] | 37 | 31 | 74.2 | 42 | 36.5 | 78.4% | |
Vinet (2013) [57] | 49.3 | 47.8 | 66.7 | 63.9 | 62.9 | 67.6% | ||
Radtke (2015) [46] | 51 | 73.5 | 63.9 | 92.3 | 95.8 | 48% | ||
Gleason ≥7 PCa | Score ≥ 3/5 | Radtke (2015) [46] | 29.3 | 27 | 87.9 | 45.1 | 59.6 | 80.2% |
a Prevalence of overall prostate cancers (10 first lines) or Gleason ≥7 cancers (last line).
PCa = prostate cancer; MRI = magnetic resonance imaging; Neg MRI = proportion of negative magnetic resonance imaging; NPV = negative predictive value; PPV = positive predictive value; Se = sensitivity; Spe = specificity.
Seven studies used a score of ≥3/5 for defining positive mpMRI ( Fig. 4 A and B) [22 25 38 43 46 56 57] . Fig. 4 C shows the conditional probability plot of 1 – NPV and PPV as a function of overall PCa prevalence. Table 5 shows NPV and PPV estimates for the given values of PCa prevalence.
PCaPrev | PPV | NPV |
---|---|---|
0.30 | 0.43 (0.34–0.53) | 0.88 (0.77–0.99) |
0.40 | 0.54 (0.45–0.64) | 0.82 (0.70–0.94) |
0.50 | 0.64 (0.55–0.73) | 0.76 (0.64–0.88) |
0.60 | 0.73 (0.65–0.80) | 0.67 (0.56–0.79) |
0.70 | 0.81 (0.75–0.87) | 0.57 (0.47–0.67) |
0.75 | 0.84 (0.79–0.89) | 0.51 (0.42–0.59) |
Only three studies used a score of ≥4/5 for defining positive mpMRI ( Table 4 ) [41 46 57] , and a formal meta-analysis could not be performed.
Only one study reporting NPV at patient level for Gleason ≥7 cancers met the selection criteria for inclusion in the meta-analysis. It reported NPV and PPV of 87.9% and 45.1%, respectively, for a prevalence of 29.3% ( Table 4 ) [46] .
We observed a large variability in reported NPV. Many factors, such as differences in mpMRI protocols, definition of negative mpMRI, or biopsy protocols, can explain this variability. However, two major causes of variability must be pointed out. First, the cancer prevalence was highly variable, ranging at patient level from 13% to 74.7% for overall PCa, and from 13.7% to 50.9% for csPCa. This variability was observed in both the biopsy-naïve and the repeat biopsy setting. As NPV depends on prevalence, this had a major impact on reported NPV ( Fig. 3 ). Second, the definition of csPCa was highly variable from one series to another, and differences of up to 21% could be observed in NPV when different definitions of csPCa were used in the same dataset [12 13 38 47 48] .
To account for clinical heterogeneity and to further explore the clinical relevance of the results, we carefully selected studies for inclusion in the meta-analysis based on stringent criteria. Particularly, we included only studies that: (1) had biopsy protocols with at least 10 cores, since it is no longer recommended to obtain less than 10 cores per biopsy; (2) used DWI, which is the most informative technique, at least for cancers in the peripheral zone [60] ; and (3) reported mpMRI findings using a five-level score, so that negative findings could be better defined. We accepted studies using a subjective (Likert) scale because experienced readers obtained equivalent [45 61 62] or better [63] results with the Likert score than with the PI-RADS v1 score. Owing to the large variations of NPV induced by differences in definitions of csPCa, we did not include different definitions in the meta-analysis since this would have introduced unacceptable clinical heterogeneity in the results, possibly resulting in erroneous and biased estimates. We, therefore, a priori restricted the definition of csPCa to cancers with a Gleason score of ≥7, given the low lethal potential of Gleason 6 cancers [64] and the lack of consensus among pathologists on the best method to measure biopsy core invasion length [65 66] .
In this more homogeneous group of studies, the prevalence range was still large (31.3–63.7%). As a result, we modelled the evolution of NPV (and PPV) as a function of overall PCa prevalence. Unfortunately, we could not duplicate this for csPCa since only one study reporting NPV for Gleason ≥7 cancers met the inclusion criteria for meta-analysis.
We included only studies that reported the results of systematic/standard biopsy in patients with negative mpMRI and used the systematic/standard biopsy as a reference standard. It is well known that TRUS-guided biopsy harbours both random and systematic errors, as evidenced by the high rates of positivity of immediate repeat biopsy after a first series of negative biopsies [67 68] , and as confirmed recently by the PROMIS trial [69] . Therefore, using TRUS-guided biopsy as a reference standard may have overestimated the NPV of mpMRI. However, studies using radical prostatectomy specimens as a reference standard have already reported mpMRI detection rates in relation to PCa Gleason score and volume [1] . In this review, we intended to address the more pragmatic question as to whether a negative mpMRI could predict a negative subsequent biopsy. This is an important question because if the NPV of mpMRI was sufficiently high in comparison with the reference standard of systematic/standard biopsies, then in practice a negative mpMRI result could indeed avoid the need for prostate biopsy. Therefore, studies reporting only biopsy results when the mpMRI was positive (eg, obtained through MRI-targeted, guided, or fusion biopsies with added systematic biopsies) were not included in this review.
It is now well established that mpMRI is a sensitive tool for detecting aggressive PCa 1 2 3 69] . However several reasons preclude its broad use as a triage test before biopsy.
Firstly, the population referred to prostate biopsy is not standardised. The large range of reported prevalence for overall PCa and csPCa suggests substantial heterogeneity in the way patients are selected for biopsy. Owing to this heterogeneity, we did not provide a pooled estimate for mpMRI NPV. The role of mpMRI as a triage test before prostate biopsy should be evaluated in the broader context of the selection of patients with a suspicion of (aggressive) PCa. In a recent retrospective study of 514 patients, mpMRI NPV for Gleason ≥7 cancers was 91% when the PSA density was ≤0.2 ng/ml/ml, and only 71% when the PSA density was >0.2 ng/ml/ml ( p = 0.003) [70] . In another series of 288 biopsy-naïve patients, no csPCa (Gleason score ≥7 or maximum cancer core length ≥4 mm) was found in 44 patients with a PSA density of <0.15 ng/ml/ml and a PI-RADS v2 score of <3/5 [71] . We believe that such prestratification of the risk of csPCa is an interesting way for rationalising the use of mpMRI before biopsy. Patients found at very low risk would be spared both mpMRI and biopsy. Patients at a low risk—for whom mpMRI would have an NPV high enough to be used as a triage test—could avoid biopsy in case of negative mpMRI. Patients at a higher risk would need biopsy even in case of negative mpMRI. Many tools can be used to risk stratify the population of patients referred to biopsy, ranging from simple parameters such as PSA density to more complicated risk calculators [72 73] . The impact of these tools on the NPV of prebiopsy mpMRI needs to be carefully evaluated, both in the biopsy-naïve and in the repeat biopsy setting. For the moment, it is impossible to make any recommendations on the best way to risk stratify patients before referring them for mpMRI.
Secondly, the large variability in the definition of csPCa precludes any definitive conclusion on the ability of mpMRI to rule out aggressive cancer. The issue of the most appropriate definition of csPCa on biopsy is complex, since biopsy results may accurately reflect neither tumour burden nor aggressiveness. Nonetheless, there is an urgent need to standardise the histological definition(s) of csPCa, to allow meaningful comparisons between studies.
Thirdly, the specificity of mpMRI remains moderate, and there is a substantial proportion of false positives in the lesions scored 3/5 or 4/5 [1 74 75] , even with the new PI-RADS v2 score [76] . In a series of 62 patients with 116 lesions biopsied under magnetic resonance/ultrasound fusion, the overall cancer detection rates for PI-RADS v2 scores of 3/5 and 4/5 were only 15.8% and 29.8%, respectively [77] . In theory, a triage test used to rule out a disease needs to be highly sensitive for this disease. However, if its specificity is too low, it will be clinically useless since most patients will be positive, whether they have the disease or not. Therefore, if mpMRI is to be used as a triage test in the future, there is a need to improve its specificity. This could be achieved by a continuous refinement of scores [78] . Promising results in characterising csPCa have also been reported with a quantitative analysis [79] .
Finally, all published studies were conducted in specialised centres. The broad use of mpMRI as a triage test assumes good interobserver reproducibility. Unfortunately, interobserver reproducibility of existing scoring systems remains moderate [62 63 80] even with the use of the PI-RADS v2 score [80 81] . Studies evaluating on a large scale the reproducibility of mpMRI findings between expert and nonexpert centres are currently lacking.
Three systematic reviews (including two meta-analyses) regarding the role of mpMRI in localised PCa have been published recently 4 5 6 . Crucially, all three reviews focused exclusively on the sensitivity of mpMRI-targeted, guided, or fusion biopsies in diagnosing overall PCa and csPCa, using TRUS-guided prostate biopsies as reference standards. The impact of systematic biopsies on the outcome was not addressed in any of the reviews, within either the index test or the reference standard. Our review had a totally different research question and objective, focusing on NPV of mpMRI to see if a negative mpMRI can avoid the need for a prostate biopsy. As MRI-targeted/guided/fusion biopsies are not relevant if the mpMRI was negative for cancer, it can be argued that the three reviews assessed a different index test altogether. As such, we believe that the findings of this review are novel and unique, and pave the way for further focused clinical studies.
The current study represents the first systematic review addressing the role of mpMRI as a triage test before biopsy. The review elements were developed in conjunction with a multidisciplinary panel of experts (EAU Prostate Cancer Guidelines Panel), which included a patient representative, and the review was performed robustly in accordance with recognised standards. However, it is limited by the major heterogeneity of the existing literature in patient population, study design, and definitions of positive mpMRI and csPCa. It highlighted further areas of research that could help in defining the best use of mpMRI in the early detection of aggressive PCa in the future.
Although mpMRI can detect aggressive PCa with excellent sensitivity, a definitive conclusion on its role as a triage test before prostate biopsy will be possible only when three main issues are addressed. Firstly, because NPV depends on prevalence, and because overall PCa and csPCa prevalence was highly variable in the published series, it becomes mandatory to define the optimal way to pre-evaluate the risk of csPCa in patients with a suspicion of PCa. Depending on the risk category, mpMRI could then be used to obviate biopsies or not. Secondly, there is a need for consensus definitions of csPCa on biopsy findings to allow interstudy comparisons. Thirdly, although efforts have been made to standardise mpMRI technical protocols and interpretation in the past few years [11 60 76] , there is still a crucial need to improve mpMRI specificity and inter-reader reproducibility.
This systematic review was performed under the auspices of:
The European Association of Urology Guidelines Office Board
The European Association of Urology Prostate Cancer Guideline Panel
Author contributions: Olivier Rouvière had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.
Study concept and design: Rouvière, Mottet, Cornford.
Acquisition of data: Rouvière, Moldovan, Van den Broeck, Yuan.
Analysis and interpretation of data: Rouvière, Moldovan, Van den Broeck, Lam.
Drafting of the manuscript: Rouvière, Moldovan, Van den Broeck, Lam.
Critical revision of the manuscript for important intellectual content: Bellmunt, van den Bergh, Bolla, Briers, Van den Broeck, Cornford, Cumberbatch, De Santis, Fossati, Gross, Henry, Joniau, Lam, Matveev, Moldovan, van der Poel, van der Kwast, Rouvière, Schoots, Wiegel, Mottet.
Statistical analysis: None.
Obtaining funding: None.
Administrative, technical, or material support: Yuan, Sylvester, Marconi.
Supervision: None.
Other: None.
Financial disclosures: Olivier Rouvière certifies that all conflicts of interest, including specific financial interests and relationships and affiliations relevant to the subject matter or materials discussed in the manuscript (eg, employment/affiliation, grants or funding, consultancies, honoraria, stock ownership or options, expert testimony, royalties, or patents filed, received, or pending), are the following: Bellmunt is a company consultant for Janssen, Astellas, Pierre Fabre, Genentech, Merck, Ipsen, Pfizer, Novartis, and Sanofi Aventis. He has received research support from Takeda, Novartis, and Sanofi, and received travel grants from Pfizer and Pierre Fabre. Bolla has received company speaker honoraria from Ipsen and Astellas, honoraria or consultation fees from Janssen, and fellowship and travel grants from Janssen, AstraZeneca, and Astellas. Briers has received grant and research support from Ipsen, European Association of Urology, and Bayer; is an ex officio board member for Europa UOMO; is an ethics committee and advisory group member for REQUITE; is a member patient advisory board member for PAGMI; and is a member of SCA and EMA PCWP. Cornford is a company consultant for Astellas, Ipsen, and Ferring. He receives company speaker honoraria from Astellas, Janssen, Ipsen, and Pfizer; participates in trials from Ferring; and receives fellowships and travel grants from Astellas and Janssen. De Santis is a company consultant for GlaxoSmithKline, Janssen, Bayer, Novartis, Pierre Fabre, Astellas, Amgen, Eisai Inc., ESSA, Merck, and Synthon; has received company speaker honoraria from Pfizer, Takeda, Sanofi Aventis, Shionogi, Celgene, and Teva OncoGenex; has participated in trials for Pierre Fabre, Astellas, Exelixis, Bayer, and Roche; has received fellowship and travel grants from Bayer, Novartis, Ferring, Astellas, Sanofi Aventis, and Janssen; has received grant and research support from Pierre Fabre; has received honoraria from AstraZeneca; and is associated with Amgen. Joniau is a company consultant for Astellas, Ipsen, Bayer, Sanofi, and Janssen; has received company speaker honoraria from Astellas, Amgen, Bayer, Sanofi, Janssen, and Ipsen; has participated in trials for Astellas, Janssen, and Bayer; has received fellowship and travel grants from Astellas, Amgen, Bayer, Sanofi, Janssen, Ipsen, and Pfizer; and has received grant and research support from Astellas, Bayer, and Janssen. Matveev has received company speaker honoraria from Sanofi and Astellas, has participated in trials for Astellas, Pfizer and Novartis. Lam is a company consultant for and has received company speaker honoraria from Pfizer, GSK, Astellas, and Ipsen. van der Poel is a company consultant for Intuitive Surgical, has participated in trials for Astellas and Steba Biotech, and has received grant and research support from Astellas. Rouvière is a company consultant for EDAP-TMS, Bracco, and Philips; has received company speaker honoraria from EDAP-TMS, Bracco, and Philips; and has participated in trials for EDAP-TMS and Bracco. Wiegel has received company speaker honoraria from Astellas, Takeda, Hexal, Ipsen, Janssen-Cilac, and Ferring. Mottet has received grant and research support from Takeda Pharmaceutical, Millenium, Astellas, Pierre Fabre, Sanofi, and Pasteur, and has received honoraria or consultation fees from Takeda Pharaceutical, Millenium, Jansen, Astellas, BMS, Bayer, Ipsen, Ferring, Novartis, Nuclétron, Pierre Fabre, Sanofi, and Zeneca. van den Bergh, Van den Broeck, Cumberbatch, Fossati, Gross, Henry, van der Kwast, Sylvester, Yuan, Schoots, Moldovan, and Marconi have nothing to disclose.
Funding/Support and role of the sponsor: None.
A correlation with radical prostatectomy specimens has demonstrated that multiparametric magnetic resonance imaging (mpMRI) has excellent sensitivity in detecting prostate cancer (PCa) with a Gleason score of ≥7 1 2 3 . As a result, prostate mpMRI is increasingly used in patients with a suspicion of PCa to localise abnormal areas before biopsy. A large body of literature has shown that targeted biopsies of suspicious lesions seen on mpMRI (TBx) improved the detection of clinically significant PCa (csPCa), at least in the repeat biopsy setting 4 5 6 . As a result, it is now recommended that an mpMRI is performed before repeat biopsy to allow TBx of suspicious lesions in addition to standard biopsies [7] .
Some authors have recently suggested that, besides improving csPCa detection, mpMRI could also be used as a triage test so that patients with negative mpMRI findings could obviate biopsy. Such a strategy remains highly controversial [8] and depends upon the negative predictive value (NPV) of mpMRI. Therefore, the European Association of Urology Prostate Cancer Guidelines Panel undertook this systematic review and meta-analysis to assess the NPV of mpMRI in patients with a suspicion of PCa and, thus, its potential role in eliminating unnecessary prostate biopsy.
Our primary aim was to systematically evaluate the performance of negative prebiopsy prostate mpMRI in predicting a negative biopsy result for overall PCa and csPCa in biopsy-naïve men and in men with previously negative biopsies. A further objective was to explore and define factors that may contribute to relevant thresholds in order to provide guidance for future studies.
The review was performed according to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) statement [9] . The review protocol was published in PROSPERO database ( http://www.crd.york.ac.uk/PROSPERO; registration number CRD42015021929). Databases searched included the Embase and OVID Medline databases, the Cochrane database of systematic reviews, and the Cochrane Central Register for Clinical Trials, covering from January 1, 2000 to February 13, 2016. Systematic or standard prostate biopsies were used as reference standards, with positive or negative cases of PCa being determined by histopathological examination. The detailed search strategy is presented in Supplement 1.
Included studies focused on men who were assessed for suspected PCa by mpMRI before undergoing prostate biopsy. Studies enrolling both biopsy-naïve men and men who had undergone previous negative biopsies were included. Prebiopsy prostate mpMRI was considered the index test and comprised T2-weighted imaging (T2WI) and at least one functional imaging technique (diffusion-weighted imaging [DWI], dynamic contrast-enhanced imaging [DCEI], or magnetic resonance spectroscopic imaging [MRSI]). For inclusion, studies had to report on false negatives and true negatives, in order to calculate NPV (ie, results of systematic/standard prostate biopsies when the mpMRI was negative). When available, false positive and true positive findings were also noted to calculate the positive predictive value (PPV) and the cancer prevalence. There was restriction neither on the biopsy technique (transrectal or transperineal) nor on the number of biopsy cores. Studies using radical prostatectomy specimens as reference standards were excluded, as were studies evaluating men with histologically proven PCa. Studies with less than 50 participants were excluded. No language restrictions were applied.
Two reviewers (P.C.M. and T.V.D.B.) independently screened all abstracts and full-text articles for eligibility. Disagreement was resolved by consensus or reference to an independent third party (L.M.). All screening was performed using a predefined eligibility form.
Using a data extraction form developed a priori, the same two reviewers independently extracted data concerning study methodology, patient characteristics, technical characteristics of the MR scanners, mpMRI protocol, mpMRI scoring system, definition of positive mpMRI, biopsy protocol, and definition of csPCa. Any discrepancies concerning data extraction were resolved by consensus or reference to an independent arbiter (O.R. or T.B.L.).
To assess the risk of bias (RoB), all included reports were reviewed using the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool for diagnostic accuracy studies [10] .
Outcome data regarding false negative and true negative values of mpMRI before prostate biopsy were recorded as reported by authors. When not available, data were indirectly derived from specificity, sensitivity, and prevalence values reported by authors using an online Bayesian statistics calculator ( http://www.medcalc.com/bayes.html ). Descriptive statistics were used to summarise baseline characteristics and outcomes, including median and interquartile range (IQR) for estimates of NPV across studies. A correlation between mpMRI NPV and a positive biopsy rate was established using the Pearson's correlation coefficient.
A meta-analysis was undertaken to calculate pooled NPV and PPV. To ensure appropriate clinical homogeneity of the studies included in the meta-analysis, we selected only the studies enrolling biopsy-naïve patients and/or patients with a history of negative biopsy, and fulfilling the following criteria that were defined a priori: (1) reference standard consisting of prostate biopsy with at least 10 samples on all patients; (2) mpMRI protocol comprising at least T2WI and DWI; (3) mpMRI results presented as a five-level score, using a subjective Likert scale or the Prostate Imaging Reporting Data System (PI-RADS) score [11] ; (4) definition of positive mpMRI as a score ≥3/5 or ≥4/5; and (5) results reported on a per patient basis. In addition, only studies defining csPCa as Gleason ≥7 cancers were selected for the meta-analysis assessing the mpMRI NPV for csPCa. A bivariate random-effects approach was employed using the Midas package in Stata 12 (StataCorp LP, College Station, TX, USA). Since the NPV decreases and the PPV increases as the prevalence increases, post-test probability estimates of NPV and PPV were reported for the given values of the prevalence based on Bayes’ theorem.
For other studies not included in the meta-analysis based on the criteria described above, a narrative synthesis of the data was performed. To explore and define clinical heterogeneity, subgroups were analysed at patient level based on the following variables: biopsy-naïve versus previous negative biopsy; patients with positive versus negative digital rectal examination (DRE); mpMRI performed with an endorectal versus without an endorectal coil; transrectal ultrasound (TRUS) versus template transperineal (TTP) biopsy approach; and ≤16 cores versus >16 cores as the reference standard. Studies reporting mpMRI NPV for patients with a prostate-specific antigen (PSA) level of ≤10 ng/ml were also reported separately.
The study selection process is depicted in the PRISMA flow diagram ( Fig. 1 ). A total of 2980 abstracts were retrieved. After abstract screening and removal of duplicates, 240 articles were eligible for full text screening, of which 48 studies were eligible for inclusion 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 .
Out of the 48 included studies, 42 were single-centre and six were multicentre studies. Thirty-four studies were prospective and six were retrospective, whilst the design of the rest was unclear. RoB assessment using QUADAS-2 was performed for each of the individual studies ( Fig. 2 A and B). Overall, the RoB was highly heterogeneous across studies for all criteria, except for the reference standard domain, in which RoB was low in most studies.
The 48 studies comprised a total of 9613 men who underwent prostate mpMRI followed by biopsy. The study and patient baseline characteristics are presented in Table 1 . The patient population consisted of biopsy-naive men in nine studies, men with at least one previous negative biopsy in 16 studies, and both biopsy-naïve men and men with a history of previous negative biopsy in nine studies. In 14 studies, the biopsy history of the patients was unclear.
Study | Study design | Period | Population | Pt Nb | Mean/median* age (yr) | Mean/median* PSA (ng/ml) | Mean/median* prostate volume (cm 3 ) | Magnetic field strength | MR pulse sequences | Endorectal coil | MR score | Definition of positive MRI | Reference standard |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Hauth (2015) [25] | Prospective | 2011–2013 | FB | 94 | 64 (43–83) | 9 (3–31) | 51 (17–140) | 1.5 T | T2WI/DWI/DCEI/MRSI | No | PI-RADS v1 | ≥3 | 11–13-core TRUS SBx + TBx |
Lamb (2015) [36] | Retrospective | 2013–2013 | FB & PNB | 173 | NR | NR | NR | 1.5 T | T2WI/DWI | NR | NR | NR | 12-core TRUS SBx |
Brock (2015) [15] | Prospective | 2013–2014 | PNB | 168 | 64* (IQR 59–70) | 9.2* (IQR 6.7–13.4) | 55.4* (IQR 42–80) | 3 T | T2WI/DWI/DCEI | No | PI-RADS v1 | NR | 12/24-core TRUS SBx + TBx |
Grenabo Bergdahl (2016) [22] | Prospective | 2013–2014 | FB & PNB | 83 | 69.3* (IQR 69–69.6) | 1.6* (IQR 0.9–2.7) | NR | 3 T | T2WI/DWI/DCEI/MRSI | No | PI-RADS v1 | ≥3 | 10-core TRUS SBx + TBx |
Wang (2015) [58] | Prospective | 2002–2009 | FB & PNB | 586 | 70 (26–91) | 11.11* (0.02–9794) | NR | 1.5 T | T2WI/DWI/DCEI/MRSI | Yes | PI-RADS v1 | ≥3 | TRUS SBx |
Pepe (2015) [41] | Prospective | 2011–2014 | PNB | 100 | 64* | 8.6* (4.2–10) | NR | 3 T | T2WI/DWI/DCEI/MRSI | No | PI-RADS v1 | ≥4 | TPBx + TBx |
Panebianco (2015) [39] | Prospective | 2011–2014 | FB (61.62%) & PNB (38.34%) | 925 (1140 total cohort) |
NR | NR | NR | 3 T | T2WI/DWI/DCEI | Yes | PI-RADS v1 | NR | 14-core TRUS SBx; 45-core sat TPBx + TBx |
Radtke (2015) [46] | Prospective | 2013–2013 | FB (63.3%) & PNB (36.7%) | 294 | 64* (60–71) | 7.3 (6.0) | 47 (37.5) | 3 T | T2WI/DWI/DCEI | No | PI-RADS v1 | PI-RADS ≥2; PI-RADS ≥3; PI-RADS ≥4; PI-RADS = 5; |
24-core TPBx + TBx |
Itatani (2014) [27] | Retrospective | 2004–2007 | NR | 193 | 68.9 (8.4); 70* (47–89) | 11.8 (15.9); 7.9* (1.22–159) | NR | 1.5 T | T2WI/DWI/DCEI | No | 1–5 scale (Likert) | ≥3 | 12–14-core TRUS SBx |
Porpiglia (2014) [44] | Prospective | 2011–2013 | PNB | 170 | 65* (60–70) | 6.9* (5.2–9.8) | 42* (36–48) | 1.5 T | T2WI/DWI/DCEI | Yes | Dichotomous | Positive: at least 2/3 MR seq. with suspicious findings | 18–24-core TRUS SBx (volume dependent) |
Thompson (2014) [56] | Prospective | 2012–2013 | FB (88%) & PNB (12%) | 150 | 62.4* (IQR 55.0–66.4) | 5.6* (IQR 4.5–7.5) | 40* (IQR 30–57) | 1.5 T (47%) & 3 T (53%) | T2WI/DWI/DCEI | No | PI-RADS v1 | ≥3 | Median of 30 TPBx (volume dependent) |
Pokorny (2014) [43] | Prospective | 2012–2013 | FB | 223 | 63* (IQR 57–68) | 5.3* (IQR 4.1–6.6) | 41* (IQR 30–59) | 3 T | T2WI/DWI/DCEI | No | PI-RADS v1 | ≥3 (primary); ≥4 |
12-core TRUS SBx + TBx |
Petrillo (2014) [42] | Prospective | 2009–2010 | NR | 136 | NR | NR | NR | 1.5 T | T2WI/DWI/MRSI | Yes | 1–5 scale (Likert) | ≥3 | 12–16-core TRUS SBx (volume + PSA dependent) |
Javali (2014) [29] | Retrospective | 2002–2011 | NR | 140 | Control: 62.4 (10.5); Study: 62.9 (12.1) | Control: 6.8 (2.3); Study: 6.87 (2.6) | Control: 44 (14.2); Study: 43 (18.4) | 1.5 T | T2WI/MRSI | Yes | Dichotomous | Cit/[Cho + Cr] < 1.2 | 6-core TRUS SBx ( n = 69), 12-core TRUS SBx ( n = 119) |
Abd-Alazeez (2014) [13] | Prospective | 2007–2011 | FB | 129 | 62* (41–82) | 5.8* (1.2–20) | 40* (16–137) | 1.5 & 3 T | T2WI/DWI/DCEI | No | PI-RADS v1 | ≥3 (primary); ≥4 |
20-core TPBx |
Abd-Alazeez (2014) [12] | Retrospective | NR | PNB | 54 | 64* (39–75) | 10* (2–23) | 53* (19–136) | 1.5 & 3 T | T2WI/DWI/DCEI | No | PI-RADS v1 | ≥3 (primary); ≥4 |
≥20-core TPBx + TBx ( n = 15) |
Matsuoka (2014) [37] | Prospective | 2007–2012 | NR | 135 | 67* (50–80) | 7.0* (2.9–19.8) | 25.4* (12.7–90.2) | 1.5 T | T2WI/DWI | No | 1–5 scale (Likert) | ≥3 | 14-core TRUS SBX |
Junker (2013) [30] | Retrospective | 2011–2013 | PNB | 73 | 62 (7.4) | 7.0* (5.1–12.9) | 45* (34–61) | 3 T | T2WI/DWI/DCEI | No | PI-RADS | PI-RADS ≥10 and ≥11 for all PCa PI-RADS ≥13 for significant PCa |
10-core TRUS SBx + TBx |
Busetto (2013) [16] | Prospective | 2010–2012 | PNB | 163 | 66.4 (5.3) | 6.8 (1.6) | NR | 3 T | T2WI/DWI/DCEI/MRSI | Yes | NR | NR | 10-core TRUS SBx + TBx |
Rais-Bahrami (2013) [47] | Prospective | 2007–2012 | NR | 583 | 61.3 (8.4) | 9.9 (13.1) | NR | 3 T | T2WI/DWI/DCEI/MRSI | Yes | 1–4 scale (Likert) | ≥2 ≥3 |
12-core TRUS SBx + TBx |
Kuru (2013) [34] | Prospective | 2010–2011 | FB (51%) & PNB (49%) | 347 | 65.3 (42–82) | 9.85 (0.5–104) | 48.7 (9–180) | 3 T | T2WI/DWI/DCEI | No | 1–3 scale (Likert) | ≥2 | 12–36-core TRUS SBx (volume dependent) + TBx |
Ferda (2013) [20] | Prospective | NR | NR | 164 | (49–74) | (4.2–123) | NR | 3 T | T2WI/DWI/DCEI/MRSI | No | NR | In house | TRUS SBx |
Ganie (2013) [21] | NR | 2007–2009 | PNB | 87 | NR | NR | NR | 1.5 T | T2WI/MRSI | Yes | MRSI Cho/Cit ratio | In house | 6 core TRUS SBx + MRI TBx |
Vinet (2013) [57] | Prospective | 2009–2011 | FB | 69 | NR | 5.2* (3.2–28) | NR | 1.5 T (35 pts) & 3 T (34 pts) | T2WI/DWI/DCEI | No | 1–5 scale (Likert) | ≥3 | 12-core TRUS SBx + TBx |
Numao (2013) [38] | Prospective | 2006–2010 | FB | 351 | 65* (59–70) | 6.3* (4.9–9.1) | 32* (24–42) | 1.5 T | T2WI/DWI/DCEI (no DCEI in 42 pts) | No | 1–5 scale (Likert) | ≥3 | 3D 26-core (12 TRUS SBx + 14 TPBx – 203 pts); 3D 14-core (6 TRUS SBx + 8 TPBx – 102 pts); TPBx 14 core (46 pts) |
Belas (2012) [14] | Prospective | 2010–2011 | FB | 71 | 66* (47–76) | 7* (4–10) | 45* (15–150) | 1.5 T | T2WI/DWI/DCEI | No | TZ: 0–4 scale PZ: 0–10 scale |
TZ: >2 PZ: >6 |
12-core TRUS SBx + TBx |
Ibrahiem (2012) [26] | Prospective | 2008–2009 | FB | 100 | 65.03 (7.13) | 26.3 (24.2) | 60.09 (28.7) | 1.5 T | T2WI/DWI | No | NR | In house | 12-core TRUS SBX |
Sciarra (2012) [51] | Prospective | 2008–2011 | PNB | 84 | 64.09 (46–76) | 7.07 (4.2–15.5) | NR | 3 T | T2WI/DWI/DCEI/MRSI | Yes | NR | NR | 10-core TRUS Bx + TBx |
Portalez (2012) [45] | Prospective | 2011 | PNB | 129 | 64.7 (47–79) | 9.6 (2.7–40) | 51.1 (12–192) | 1.5 T | T2WI/DWI/DCEI | Mixed | 1–5 scale (Likert) PI-RADS |
Likert ≥3 PI-RADS ≥9 |
10–12-core TRUS SBx + TBx |
Watanabe (2012) [59] | Prospective | 2004–2008 | NR | 1448 | 72 (7.5) | NR | NR | 1.5 T | T2WI/DWI | No | NR | ADC value ≤1.35 × 10 −3 mm 2 /s | 8-core TRUS SBx + TBx |
Tamada (2011) [54] | Retrospective | 2006–2009 | NR | 50 | 70 (40–84) | 6.84* (4.06–9.94) | NR | 1.5 T | T2WI/DWI/DCEI | No | NR | In house | 12-core TRUS SBx |
Choi (2011) [18] | NR | 2009–2010 | NR | 51 | 67.16 (56–90) | 14.16 (1.02–38.9) | 42.98 (13.8–77.3) | 3 T | T2WI/DWI | NR | NR | NR | 10–12-core TRUS SBx + TBx |
Iwazawa (2011) [28] | Retrospective | 2008–2009 | NR | 178 | 68.8 (41–86) | 20.51 (4.04–568.5) | NR | 1.5 T | T2WI/DWI/DCEI | NR | 1–4 scale (Likert) | NR | 10–12-core TRUS SBx (TBx included in SBx chart) |
Rouse (2011) [48] | Prospective | 2005–2007 | PNB | 114 | 63.6 (41–83) | 13.4 (0–228) | NR | 1.5 T | T2WI/DWI/DCEI | NR | 1–5 scale (Likert) | ≥3 | TRUS SBx |
Haffner (2011) [23] | Prospective | 2005–2009 | FB | 555 | 64* (47–83) | 6.75* (0.18–100) | 46* (15–200) | 1.5 T | T2WI/DCEI | No | 1–5 scale (Likert) | ≥3 | 10-core TRUS SBx + TBx |
Panebianco (2010) [40] | Prospective | 2007–2009 | PNB | 150 | 61.2 (46–78) | 9.42 (3.91) | 41.17 (7.47) | 1.5 T | T2WI/DCEI/MRSI | Yes | NR | In house | 10-core TRUS SBx (TBx included in SBx chart) |
Roy (2010) [49] | Not specified | 2011–2009 | FB (53%) & PNB (47%) | 103 | 63 (52–78) | 7* | NR | 3 T | T2WI/DWI/DCEI | Yes | NR | NR | 8-core TRUS SBx + TBx |
Testa (2010) [55] | Not specified | 2007 | PNB | 54 | 63.9 (52–76) | 11.4 (3–42) | 59.3 (30–150) | 1.5 T | T2WI/MRSI | Yes | 1–3 scale (Likert) | ≥2 | 12-core TRUS SBx + TBx |
Sciarra (2010) [52] | Prospective | 2007–2009 | PNB | 110 | 63.5 (49–74) | NR | NR | 1.5 T | T2WI/DCEI/MRSI | Yes | NR | In house | 10-core TRUS SBx + TBx |
Kitajima (2010) [31] | Prospective | 2008–2009 | NR | 53 | 69* (56–84) | 11.1* (4.2–112.1) | NR | 3 T | T2WI/DWI/DCEI | No | 1–5 scale (Likert) | ≥3 | 20-core TPBx |
Labanaris (2010) [35] | Prospective | 2004–2008 | PNB | 260 | NR | NR | NR | 1 T | T2WI/DWI/DCEI | Yes | Dichotomous | In house | 18-core TRUS SBx |
Kumar (2009) [32] | NR | NR | NR | 61 | 65.3 (9.3) | 16.5 (0.21–155) | NR | 1.5 T | T2WI/MRSI | Yes | NR | (Cit/(Cho + Cr) ≤ 1.2 | TRUS Bx |
Schmuecking (2009) [50] | NR | NR | FB & PNB | 67 | 68 | 11.5 | NR | 1.5 T | T2WI/DCEI | No | NR | NR | 20-core Bx |
Cheikh (2009) [17] | Retrospective | 2005–2008 | PNB | 93 | 63.2 (52–74) | 9.63 (1.6–40) | NR | 1.5 T | T2WI/DCEI | No | Dichotomous | In house | 12-core TRUS SBx + TBx |
Cirillo (2008) [19] | Prospective | 2004–2006 | PNB | 54 | 65.5 (5.2) | 10.8 (7.5) | NR | 1.5 T | T2WI/MRSI | Yes | Dichotomous | In house | 10-core TRUS SBx + TBx |
Kumar (2007) [33] | Prospective | 2003–2005 | NR | 83 | NR | NR | NR | 1.5 T | T2WI/MRSI | Yes | NR | NR | 12-core TRUS SBx + TBx |
Squillaci (2005) [53] | Prospective | 2004–2005 | NR | 65 | NR | NR | NR | 1.5 T | T2WI/DCEI/MRSI | No | 1–3 scale (Likert) | ≥2 | 10-core TRUS SBx + TBx |
Hara (2005) [24] | Prospective | 2003–2004 | FB | 90 | 67.2 (NR) | NR | NR | 1.5 T | T2WI/DCEI | No | 1–3 scale (Likert) | ≥2 = 3 |
14-core TRUS SBx |
The magnetic field strength was 1, 1.5, and 3 T in one, 28, and 15 studies, respectively. Four studies used both 1.5 and 3 T MR systems. DWI and DCEI were used in 36 and 35 studies, respectively. Nineteen studies also added MRSI. An endorectal coil was used in 18 studies. The definition of positive mpMRI varied across studies. The PI-RADS v1 score was used in 12 studies, a five-level subjective (Likert) score was used in eight studies, and one study reported data based on the two scoring systems. In-house criteria were used in 13 studies for defining positive mpMRI, and five studies used a dichotomous definition. Nine studies did not report on the criteria for positive mpMRI. No study used the PI-RADS v2 score.
Regarding the reference standard, TRUS-guided biopsies were used in 39 studies, TTP biopsies in six studies, and mixed TRUS-guided and TTP biopsies in two studies. In one study, the biopsy approach was unclear. The number of cores per biopsy procedure was ≤16 in 30 studies, >16 in nine studies, and variable among patients in three studies. For six studies, the number of biopsy cores taken was unclear.
At patient level, the median biopsy positivity rate (ie, cancer prevalence) was 50.4% (IQR, 36.4–57.7%) for overall cancer and 32.9% (IQR, 28.1–37.2%) for csPCa ( Table 2 ). The median mpMRI NPV was 82.4% (IQR, 69.0–92.4%) for overall cancer and 88.1% (IQR, 85.7–92.3) for csPCa. NPV significantly decreased when cancer prevalence increased, both for overall cancer ( r = –0.64, p < 0.0001) and csPCa ( r = –0.75, p = 0.032; Fig. 3 ). In addition, NPV was highly dependent on the definition used for csPCa, with differences of up to 21% when several definitions were used in the same dataset [12 13 38 47 48] .
Study | Overall PCa prevalence (%) | Reporting level | Multiparametric MRI performance for PCa detection | Definition of csPCa | csPCa prevalence | Multiparametric MRI performance for csPCa detection | ||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
TN | FN | TP | FP | NPV | PPV | TN | FN | TP | FP | NPV | PPV | |||||
Hauth (2015) [25] | 45.7 | Patient | 6 | 1 | 42 | 45 | 85.7% | 48.3% | Low grade: GS ≤ 6 High grade: GS ≥ 7 |
NR | NR | NR | NR | NR | NR | NR |
Lesion | 59 | 13 | 55 | 73 | 81.9% | 43% | ||||||||||
Lamb (2015) [36] | 65.9 | Patient | 23 | 22 | 92 | 36 | 51.1% | 71.9% | GS ≥ 7 | 50.9% | 31 | 14 | 71 | 57 | 68.9% | 55.5% |
Brock (2015) [15] | 42.3 | Patient | 17 | 7 | 56 | 88 | 70.8% | SBx: 38.8% TBx: 22.2% Duo: 44.4% |
Epstein: GS > 6 and/or max CCL ≥50% | 24.4% | SBx: 21 | SBx: 3 | SBx: 38 TBx: 27 duo: 47 |
SBx: 106 TBx: 117 duo: 97 |
87.5% | SBx: 26.4% TBx: 18.8% duo: 32.6% |
Grenabo Bergdahl (2016) [22] | 33.7 | Patient | 36 | 7 | 19 | 21 | 83.7% | 47.5% | Clinically insignificant PCa: T1c, PSAd < 0.15, GS < 7, ≤2 positive cores, and unilateral cancer | NR | NR | NR | NR | NR | NR | NR |
Wang (2015) [58] | 58 | Patient | 165 | 8 | 332 | 81 | 95.4% | 80.4% | NR | NR | NR | NR | NR | NR | NR | NR |
Pepe (2015) [41] | 37 | Patient | 23 | 8 | 29 | 40 | 74.2% | 42% | GS ≥ 7 or GS 6 with CCL ≥ 50% | NR | NR | NR | NR | NR | 100% | 55.8% |
Panebianco (2015) [39] | 74.7 | Patient | Group A (satBx): 104 | Group A (satBx): 43 | Group A: 186 | Group A: 22 | Group A (satBx): 70.7% | Group A: 89.4% | NR | 60% | Group A: 147 | Group A: 0 | Group A: 183 | Group A: 25 | Group A: 100% | Group A: 88% |
Group B (TRUSGB NR TRUS G satBx): 93 | Group B (TRUSGB NR TRUS G satBx): 37 | Group B: 417 before and 425 after satBx | Group B: 23/440 and 15/440 after satBx. | Group B (TRUSGB–TRUS G satBx): 71.5% | Group B: 94.8% before and 96.6% after satBx | 71.9% | Group B: 130 | Group B: 0 | Group B: 410 |
Group B: 30 | Group B: 100% | Group B: 93.2% | ||||
Radtke (2015) [46] | 51 | Patient | ≥2/5: 80 ≥3: 103 ≥4: 138 = 5: 142 |
≥2/5: 18 ≥3/5: 38 ≥4/5: 78 = 5/5: 126 |
≥2/5: 132 ≥3/5: 112 ≥4/5: 72 = 5/5: 24 |
≥2/5: 64 ≥3/5: 41 ≥4/5: 6 = 5/5: 2 |
≥2/5: 81.6% ≥ 3/5: 73.1% ≥ 4/5: 63.9% = 5/5: 53% |
≥2/5: 67.4% ≥ 3/5: 73.2% ≥ 4/5: 92.3% = 5/5: 92.3% |
GS ≥ 7 | 29.3% | ≥2/5: 91 ≥3/5: 124 ≥4/5: 183 = 5/5: 203 |
≥2/5: 7 ≥3/5: 17 ≥4/5: 33 = 5/5: 65 |
≥2/5: 79 ≥3/5: 69 ≥4/5: 53 = 5/5: 21 |
≥2/5: 117 ≥3/5: 84 ≥4/5: 25 = 5/5: 5 |
≥2/5: 92.2% ≥3/5: 87.9% ≥4/5: 84.7% = 5/5: 75.8% |
≥2/5: 40.3% ≥3/5: 45.1% ≥4/5: 68% = 5/5: 80.7% |
Itatani (2014) [27] | 13 | Patient | 168 | 25 | NR | NR | 87% | NR | (1) PSAd ≥ 0.1 or GP 4/5 or ≥ 3/6 pos cores; max CCL < 50% (2) PSAd ≥ 0.15 or GP 4/5 or max core length invasion < 3 mm (min 6 cores) |
NR | NR | NR | NR | NR | NR | NR |
Porpiglia (2014) [44] | 30.6 | Patient | 107 | 5 | 47 | 11 | 95.5% | 81% | NR | NR | NR | NR | NR | NR | NR | NR |
Thompson (2014) [56] | 61.3 | Patient | 35 | 16 | 76 | 23 | 68.6% | 76.7% | Moderate or high risk Moderate risk: GS 7 (GP4 >5%) and <50% of positive cores or GS 6–7 (GP4 ≤ 5%) and either ≥30% of positive cores or max core length invasion ≥8 mm High risk: GS ≥ 7 (GP4 > 5%); ≥50% + cores or GS ≥ 8 |
34% | 49 | 2 | 49 | 50 | 96% | 49.5% |
Pokorny (2014) [43] | 63.7 | Patient | ≥3/5: 56 ≥4/5: 74 |
≥3/5: 25 ≥4/5: 40 |
≥3/5: 101 ≥4/5: 86 |
≥3/5: 41 ≥4/5: 23 |
≥3/5: 69.1% ≥4/5: 64.9% |
≥3/5: 71.1% ≥4/5: 78.9% |
NR | NR | NR | NR | NR | NR | NR | NR |
Petrillo (2014) [42] | 18.4 | Patient | 56 | 4 | 21 | 55 | 93% | 28% | NR | NR | NR | NR | NR | NR | NR | NR |
Javali (2014) [29] | 16.4 | Patient | 49 | 1 | 22 | 68 | 98% | 24.4% | NR | NR | NR | NR | NR | NR | NR | NR |
Abd-Alazeez (2014) [13] | 54.7 | Lobe | ≥3/5: 33 | ≥3/5: 14 | ≥3/5: 127 | ≥3/5: 84 | ≥3/5: 70% | ≥3/5: 60% | Def 1: GS ≥ 4 + 3 and/or max CCL ≥ 6 mm Def 2: GS ≥ 3 + 4 and/or max CCL ≥ 4 mm Def 3: GS ≥ 4 + 3 Def 4: GS ≥ 3 + 4 Def 5: max CCL ≥ 6 mm Def 6: max CCL ≥ 4 mm |
Def 1: NR Def 2: 44.2% Def 3: 23.2% Def 4: 36% Def 5: 32.9% Def 6: 39.5% |
Def 1: 46 Def 2: 42 Def 3: 47 Def 4: 43 Def 5: 46 Def 6: 43 |
Def 1: 1 Def 2: 5 Def 3: 0 Def 4: 4 Def 5: 1 Def 6: 4 |
Def 1: 45 Def 2: 72 Def 3: 13 Def 4: 50 Def 5: 39 Def 6: 59 |
Def 1: 166 Def2: 139 Def 3: 198 Def 4: 161 Def 5: 172 Def 6: 152 |
Def 1: 98 Def 2: 89 Def 3: 100 Def 4: 92 Def 5: 98 Def 6: 91 |
Def 1: 21 Def 2: 34 Deg 3: 6 Def 4: 24 Def 5: 19 Def 6: 28 |
≥4/5: 87 | ≥3/5: 62 | ≥3/5: 79 | ≥3/5: 30 | ≥3/5: 58% | ≥3/5: 73% | Def 1: 140 Def 2: 124 Def 3: 148 Def 4: 133 Def 5: 141 Def 6: 131 |
Def 1: 9 Def 2: 25 Def 3: 1 Def 4: 16 Def 5: 8 Def 6: 18 |
Def 1: 37 Def 2: 52 Def 3: 12 Def 4: 38 Def 5: 32 Def 6: 45 |
Def 1: 72 Def 2: 57 Def 3: 97 Def 4: 71 Def 5: 77 Def 6: 64 |
Def 1: 94 Def 2: 83 Def 3: 99 Def 4: 89 Def 5: 95 Def 6: 88 |
Def 1: 34 Def 2: 48 Def 3: 11 Def 4: 35 Def 5: 30 Def 6: 42 |
|||||
Abd-Alazeez (2014) [12] | 47.2 | Lobe | ≥3/5: 26 | ≥3/5: 13 | ≥3/5: 38 | ≥3/5: 31 | ≥3/5: 66% | ≥3/5: 55% | Def 1: GS ≥ 4 + 3 and/or max CCL ≥ 6 mm Def 2: GS ≥ 3 + 4 and/or max CCL ≥ 4 mm Def 3: GS ≥ 4 + 3 Def 4: GS ≥ 3 + 4 Def 5: max CCL ≥ 6 mm Def 6: max CCL ≥ 4 mm |
Def 1: 18.5% Def 2: 31.5% Def 3: 4.6% Def 4: 21.3% Def 5: 16.7% Def 6: 25% |
Def 1: 37 Def 2: 31 Def 3: 39 Def 4: 36 Def 5: 37 Def 6: 32 |
Def 1: 2 Def 2: 8 Def 3: 0 Def 4: 3 Def 5: 2 Def 6: 7 |
Def 1: 18 Def 2: 26 Def 3: 5 Def 4: 20 Def 5: 16 Def 6: 20 |
Def 1: 51 Def 2: 43 Def 3: 64 Def 4: 49 Def 5: 53 Def 6: 49 |
Def 1: 95 Def 2: 79 Def 3: 100 Def 4: 92 Def 5: 95 Def 6: 82 |
Def 1: 26 Def 2: 38 Def 3: 7 Def 4: 29 Def 5: 23 Def 6: 29 |
≥4/5: 49 | ≥4/5: 25 | ≥4/5: 26 | ≥4/5: 8 | ≥4/5: 66% | ≥4/5: 76% | Def 1: 70 Def 2: 63 Def 3: 73 Def 4: 68 Def 5: 70 Def 6: 64 |
Def 1: 4 Def 2: 11 Def 3: 1 Def 4: 6 Def 5: 4 Def 6: 10 |
Def 1: 16 Def 2: 23 Def 3: 4 Def 4: 17 Def 5: 14 Def 6: 17 |
Def 1: 18; Def 2: 11 Def 3: 30 Def 4: 17 Def 5: 20 Def 6: 17 |
Def 1: 94 Def 2: 85 Def 3: 99 Def 4: 92 Def 5: 94 Def 6: 86 |
Def 1: 47 Def 2: 67 Def 3: 12 Def 4: 50 Def 5: 41 Def 6: 49 |
|||||
Matsuoka (2014) [37] | 64.8 | Lobe | 46 | 49 | 149 | 26 | 48.4% | 85.1% | NR | NR | NR | NR | NR | NR | NR | NR |
Junker (2013) [30] | 53.4 | Patient | ≥10/15: 21 ≥11/15: 28 |
≥10/15: 4 ≥11/15: 12 |
≥10/15: 35 ≥11/15: 27 |
≥10/15: 13 ≥11/15: 6 |
≥10/15: 84% ≥11/15: 70% |
≥10/15: 72.9% ≥11/15: 81.8% |
GS ≥ 4 + 3 | 13.7% | ≥13: 54 | ≥13: 2 | ≥13: 8 | ≥13: 9 | ≥13: 96.4% | ≥13: 47% |
Busetto (2013) [16] | 41.7 | Patient | 59 | 7 | 61 | 36 | 89% | 63% | NR | NR | NR | NR | NR | NR | NR | NR |
Rais-Bahrami (2013) [47] | 54.2 | Patient | ≥2/4 : 80 | ≥2/4: 275 | ≥2/4: 187 | ≥2/4: 275 | ≥2/4: 66% | ≥2/4: 59% | GS ≥ 7: GS ≥ 8 |
31.7% | NR | NR | NR | NR | GS ≥ 7: 91% GS ≥ 8: 91% |
GS ≥ 7: 38% GS ≥ 8: 18% |
≥3/4: 251 | ≥3/4: 76 | ≥3/4: 16 | ≥3/4: 76 | ≥3/4: 51% | ≥3/4: 82% | NR | NR | NR | NR | GS ≥ 7: 75% GS ≥ 8: 91% |
GS ≥ 7: 67% GS ≥ 8: 41% |
|||||
Kuru (2013) [34] | 57.6 | Patient | 80 | 14 | 67 | 186 | 85.1% | 73.5% | NR | NR | NR | NR | NR | NR | NR | NR |
Ferda (2013) [20] | 51.2 | Patient | 52 | 2 | 82 | 28 | 96.3% | 74.5% | NR | NR | NR | NR | NR | NR | NR | NR |
Ganie (2013) [21] | 74.7 | Patient | 13 | 3 | 62 | 9 | 59.1% | 95.4% | NR | NR | NR | NR | NR | NR | NR | NR |
Vinet (2013) [57] | 49.3 | Patient | ≥3/5: 11 | ≥3/5: 6 | ≥3/5: 28 | ≥3/5: 24 | ≥3/5: 64.7% | ≥3/5: 53.8% | NR | NR | NR | NR | NR | NR | NR | NR |
≥4/5: 22 | ≥4/5: 11 | ≥4/5: 23 | ≥4/5: 13 | ≥4/5: 66.7% | ≥4/5: 63.8% | NR | NR | NR | NR | NR | NR | NR | NR | |||
Numao (2013) [38] | 45 | Patient | 137 | 57 | 101 | 56 | 70.6% | 64.3% | Def 1: GS ≥4 + 3 and/or ≥20% positive cores and/or max CCL ≥5 mm Def 2: GS ≥ 3 + 4 and/or ≥20% + cores and/or max CCL ≥5 mm Def 3: GS ≥ 3 + 4 and/or ≥20% + cores |
Def 1: 33.3% Def 2:37.8% Def 3: 35.8% |
Def 1: 74 Def 2: 65 Def 3: 69 |
Def 1: 83 Def 2: 92 Def 3: 88 |
Def 1: 160 Def 2: 153 Def 3: 156 |
Def 1: 34 Def 2: 41 Def 3: 38 |
Def 1: 82.4% Def 2: 78.8% Def 3: 80.4% |
Def 1: 58.8% Def 2: 58.5% Def 3: 56% |
Belas (2012) [14] | 53.5 | Patient | 22 | 12 | 23 | 13 | 64.7% | 63.8% | NR | NR | NR | NR | NR | NR | NR | NR |
Ibrahiem (2012) [26] | 73.9 | Patient | 14 | 11 | 57 | 10 | 56% | 85.1% | NR | NR | NR | NR | NR | NR | NR | NR |
Sciarra (2012) [51] | 34.5 | Patient | 41 | 4 | 25 | 14 | 91.1% | 64.1% | NR | NR | NR | NR | NR | NR | NR | NR |
Portalez (2012) [45] | 48.1 | Lesion | Likert: 357 | Likert: 50 | Likert: 81 | Likert: 50 | Likert: 95% | Likert: 38% | Max CCL >3 mm and/or GG 4/5 | NR | NR | NR | NR | NR | NR | NR |
PI-RADS: 404 | PI-RADS: 47 | PI-RADS: 34 | PI-RADS: 47 | PI-RADS: 95% | PI-RADS: 58% | |||||||||||
Watanabe (2012) [59] | 48.1 | Patient | 485 | 73 | 624 | 266 | 86.9% | 70.1% | NR | NR | NR | NR | NR | NR | NR | NR |
Tamada (2011) [54] | 70 | Patient | 12 | 6 | 29 | 3 | 67% | 91% | NR | NR | NR | NR | NR | NR | NR | NR |
Region | 277 | 48 | 55 | 20 | 85% | 73% | ||||||||||
Choi (2011) [18] | 70.6 | Patient | 9 | 5 | 31 | 6 | 64.2% | 75.7% | NR | NR | NR | NR | NR | NR | NR | NR |
Iwazawa (2011) [28] | 40.5 | Region | 887 | 86 | 232 | 219 | 91.1% | 51.4% | NR | NR | NR | NR | NR | NR | NR | NR |
Rouse (2011) [48] | 33.7 | Sextant | 145 | 11 | 74 | 22 | 92.9% | 77.1% | GS ≥ 7: Def 1: ≥3 mm Def 2: ≥5 mm |
Def 1: 26.6% Def 2: 26.2% |
Def 1: 153 Def 2: 153 |
Def 1: 3 Def 2: 3 |
Def 1: 64 Def 1: 63 |
Def 1: 32 Def 2: 33 |
Def 1: 98.1% Def 2: 98.1% |
Def 1: 68.1% Def 2: 67% |
59.6 | Patient | 24 | 14 | 54 | 22 | 63.2% | 71.1% | Def 1: 41.2% Def 2: 36.8% |
Def 1: 30 Def 2: 31 |
Def 1: 4 Def 2: 3 |
Def 1: 43 Def 2: 39 |
Def 1: 4 Def 2: 3 |
Def 1: 88.2% Def 2: 91.2% |
Def 1: 53.8% Def 2: 48.8% |
||
Haffner (2011) [23] | 54.4 | Patient | 154 | 50 | 240 | 111 | 75.4% | 68.3% | NR | NR | NR | NR | NR | NR | NR | NR |
Panebianco (2010) [40] | 42.7 | Patient | NR | NR | NR | NR | 95.1% | 88.2% | NR | NR | NR | NR | NR | NR | NR | NR |
Roy (2010) [49] | 55.9 | Patient | NR | NR | NR | NR | 71% | 75% | NR | NR | NR | NR | NR | NR | NR | NR |
Testa (2010) [55] | 40.7 | Patient | NR | NR | NR | NR | 79.3% | 64% | NR | NR | NR | NR | NR | NR | NR | NR |
Sciarra (2010) [52] | 50 | Patient | 61 | 4 | 66 | 9 | 93.8% | 88% | NR | NR | NR | NR | NR | NR | NR | NR |
Kitajima (2010) [31] | 56.6 | Patient | 311 | 19 | 80 | 14 | 92.2% | 85.1% | NR | NR | NR | NR | NR | NR | NR | NR |
Labanaris (2010) [35] | 73.9 | Patient | 17 | 73 | 96 | 74 | 81.11% | 56.47% | NR | NR | NR | NR | NR | NR | NR | NR |
Kumar (2009) [32] | 21.7 | Patient | 39 | 3 | 10 | 8 | 92.8% | 55% | NR | NR | NR | NR | NR | NR | NR | NR |
Schmuecking (2009) [50] | NR | Lobe | NR | NR | NR | NR | 96% | 61% | NR | NR | NR | NR | NR | NR | NR | NR |
Cheikh (2009) [17] | 24.7 | Patient | 36 | 12 | 11 | 34 | 80% | 22.9% | NR | NR | NR | NR | NR | NR | NR | NR |
Cirillo (2008) [19] | 31.5 | Patient | 19 | 0 | 17 | 18 | 100% | 48.6% | NR | NR | NR | NR | NR | NR | NR | NR |
Kumar (2007) [33] | 13.3 | Patient | 39 | 0 | 11 | 33 | 100% | 25% | NR | NR | NR | NR | NR | NR | NR | NR |
Squillaci (2005) [53] | 50.8 | Patient | 29% | 8% | 25% | 3% | 89% | 80% | NR | NR | NR | NR | NR | NR | NR | NR |
Hara (2005) [24] | 41.5 | Patient | ≥2/3: 40 = 3/3: 47 |
≥2/3: 4 = 3/3: 8 |
≥2/3 30 = 3/3: 26 |
≥2/3: 8 = 3/3: 1 |
≥2/3: 90% = 3/3: 85% |
≥2/3: 78.9% = 3/3: 96.3% |
NR | NR | NR | NR | NR | NR | NR | NR |
Cancer prevalence tended to be higher and mpMRI NPV lower in the biopsy-naïve group as compared with the repeat biopsy group, in men with positive DRE as compared with men with negative DRE and when an endorectal coil was not used ( Table 3 ). There were no clear differences in the prevalence and NPV of the other analysed subgroups (TRUS-guided vs TTP biopsy, biopsy procedures with ≤16 cores vs >16 cores; Table 3 ). However, comparisons must be interpreted with care, due to the small number of studies in some subgroups. In patients with a PSA level of ≤10 ng/ml, the median NPV for overall PCa was 86.3% (IQR, 73.3–93.6%) for a median cancer prevalence of 35.4% (IQR, 27.6–42.5%).
Nb of studies | Median PCa prevalence | Median mpMRI NPV | Nb of studies | Median csPCa prevalence | Median mpMRI NPV | |
---|---|---|---|---|---|---|
Biopsy-naïve patients | 8 | 51.4% (45.5–56.7) | 69.9% (64.2–78) | 1 | 35.8% (NA) | 80.4% (NA) |
Repeat biopsy | 14 | 42% (35.1–52.6) | 82.6% (75.5–93.1) | 3 | 24.4% (19.1–32.8) | 88.2% (87.9–92.3) |
TRUS-guided biopsy | 36 | 49.7% (34.3–57.7) | 84.6% (68.6–92.8) | 4 | 28.1% (21.7–36.5) | 89.3% (82.9–92.4) |
TTP biopsy | 4 | 53.8% (47.5–57.8) | 73.6% (72–78.7) | 2 | 31.6% (30.5–32.8) | 92% (89.9–94) |
Biopsy with ≤16 cores | 28 | 48.7% (39.2–54.8) | 81.9% (66.8–89.3) | 5 | 28.1% (21.8–36.5) | 89.3% (82.9–92.4) |
Biopsy with >16 cores | 5 | 56.6% (51–61.3) | 81.1% (73.1–92.2) | 2 | 31.7% (30.5–32.8) | 92% (89.9–93.9) |
Positive DRE | 1 | 73.9% (NA) | 56% (NA) | 0 | – | – |
Negative DRE | 6 | 36% (34.6–46.8) | 82.7% (74.2–93.1) | 0 | – | – |
Endorectal coil | 17 | 41.7% (30.6–55.9) | 92.8% (79.3–95.4) | 1 | 31.7% (NA) | 91% (NA) |
No endorectal coil | 22 | 50.9% (41.7–56.1) | 77.7% (69.5–86.6) | 7 | 34% (26.9–46.1%) | 87.9% (78.2–92.1) |
Eight studies reported NPV at patient level for overall PCa and fulfilled the inclusion criteria for meta-analysis ( Table 4 ) [22 25 38 41 43 46 56 57] .
Study | Prevalence a (%) | Neg MRI (%) | NPV (%) | PPV (%) | Spe (%) | Se (%) | ||
---|---|---|---|---|---|---|---|---|
All PCa | Score ≥ 3/5 | Grenabo Bergdahl (2016) [22] | 31.3 | 66.9 | 83.7 | 47.5 | 63.2 | 73.1 |
Numao (2013) [38] | 45 | 29.4 | 70.6 | 64.3 | 71.0 | 63.9 | ||
Hauth (2015) [25] | 45.7 | 14.3 | 85.7 | 48.3 | 11.8 | 97.7 | ||
Vinet (2013) [57] | 49.3 | 24.6 | 64.7 | 53.8 | 31.4 | 82.4 | ||
Radtke (2015) [46] | 51 | 27 | 73 | 73.2 | 71.5 | 74.7 | ||
Thompson (2014) [56] | 61.3 | 31.4 | 68.6 | 76.8 | 60.3 | 82.6 | ||
Pokorny (2014) [43] | 63.7 | 30.9 | 69.1 | 82.4 | 69.1 | 82.4 | ||
Score ≥ 4/5 | Pepe (2015) [41] | 37 | 31 | 74.2 | 42 | 36.5 | 78.4% | |
Vinet (2013) [57] | 49.3 | 47.8 | 66.7 | 63.9 | 62.9 | 67.6% | ||
Radtke (2015) [46] | 51 | 73.5 | 63.9 | 92.3 | 95.8 | 48% | ||
Gleason ≥7 PCa | Score ≥ 3/5 | Radtke (2015) [46] | 29.3 | 27 | 87.9 | 45.1 | 59.6 | 80.2% |
a Prevalence of overall prostate cancers (10 first lines) or Gleason ≥7 cancers (last line).
PCa = prostate cancer; MRI = magnetic resonance imaging; Neg MRI = proportion of negative magnetic resonance imaging; NPV = negative predictive value; PPV = positive predictive value; Se = sensitivity; Spe = specificity.
Seven studies used a score of ≥3/5 for defining positive mpMRI ( Fig. 4 A and B) [22 25 38 43 46 56 57] . Fig. 4 C shows the conditional probability plot of 1 – NPV and PPV as a function of overall PCa prevalence. Table 5 shows NPV and PPV estimates for the given values of PCa prevalence.
PCaPrev | PPV | NPV |
---|---|---|
0.30 | 0.43 (0.34–0.53) | 0.88 (0.77–0.99) |
0.40 | 0.54 (0.45–0.64) | 0.82 (0.70–0.94) |
0.50 | 0.64 (0.55–0.73) | 0.76 (0.64–0.88) |
0.60 | 0.73 (0.65–0.80) | 0.67 (0.56–0.79) |
0.70 | 0.81 (0.75–0.87) | 0.57 (0.47–0.67) |
0.75 | 0.84 (0.79–0.89) | 0.51 (0.42–0.59) |
Only three studies used a score of ≥4/5 for defining positive mpMRI ( Table 4 ) [41 46 57] , and a formal meta-analysis could not be performed.
Only one study reporting NPV at patient level for Gleason ≥7 cancers met the selection criteria for inclusion in the meta-analysis. It reported NPV and PPV of 87.9% and 45.1%, respectively, for a prevalence of 29.3% ( Table 4 ) [46] .
We observed a large variability in reported NPV. Many factors, such as differences in mpMRI protocols, definition of negative mpMRI, or biopsy protocols, can explain this variability. However, two major causes of variability must be pointed out. First, the cancer prevalence was highly variable, ranging at patient level from 13% to 74.7% for overall PCa, and from 13.7% to 50.9% for csPCa. This variability was observed in both the biopsy-naïve and the repeat biopsy setting. As NPV depends on prevalence, this had a major impact on reported NPV ( Fig. 3 ). Second, the definition of csPCa was highly variable from one series to another, and differences of up to 21% could be observed in NPV when different definitions of csPCa were used in the same dataset [12 13 38 47 48] .
To account for clinical heterogeneity and to further explore the clinical relevance of the results, we carefully selected studies for inclusion in the meta-analysis based on stringent criteria. Particularly, we included only studies that: (1) had biopsy protocols with at least 10 cores, since it is no longer recommended to obtain less than 10 cores per biopsy; (2) used DWI, which is the most informative technique, at least for cancers in the peripheral zone [60] ; and (3) reported mpMRI findings using a five-level score, so that negative findings could be better defined. We accepted studies using a subjective (Likert) scale because experienced readers obtained equivalent [45 61 62] or better [63] results with the Likert score than with the PI-RADS v1 score. Owing to the large variations of NPV induced by differences in definitions of csPCa, we did not include different definitions in the meta-analysis since this would have introduced unacceptable clinical heterogeneity in the results, possibly resulting in erroneous and biased estimates. We, therefore, a priori restricted the definition of csPCa to cancers with a Gleason score of ≥7, given the low lethal potential of Gleason 6 cancers [64] and the lack of consensus among pathologists on the best method to measure biopsy core invasion length [65 66] .
In this more homogeneous group of studies, the prevalence range was still large (31.3–63.7%). As a result, we modelled the evolution of NPV (and PPV) as a function of overall PCa prevalence. Unfortunately, we could not duplicate this for csPCa since only one study reporting NPV for Gleason ≥7 cancers met the inclusion criteria for meta-analysis.
We included only studies that reported the results of systematic/standard biopsy in patients with negative mpMRI and used the systematic/standard biopsy as a reference standard. It is well known that TRUS-guided biopsy harbours both random and systematic errors, as evidenced by the high rates of positivity of immediate repeat biopsy after a first series of negative biopsies [67 68] , and as confirmed recently by the PROMIS trial [69] . Therefore, using TRUS-guided biopsy as a reference standard may have overestimated the NPV of mpMRI. However, studies using radical prostatectomy specimens as a reference standard have already reported mpMRI detection rates in relation to PCa Gleason score and volume [1] . In this review, we intended to address the more pragmatic question as to whether a negative mpMRI could predict a negative subsequent biopsy. This is an important question because if the NPV of mpMRI was sufficiently high in comparison with the reference standard of systematic/standard biopsies, then in practice a negative mpMRI result could indeed avoid the need for prostate biopsy. Therefore, studies reporting only biopsy results when the mpMRI was positive (eg, obtained through MRI-targeted, guided, or fusion biopsies with added systematic biopsies) were not included in this review.
It is now well established that mpMRI is a sensitive tool for detecting aggressive PCa 1 2 3 69] . However several reasons preclude its broad use as a triage test before biopsy.
Firstly, the population referred to prostate biopsy is not standardised. The large range of reported prevalence for overall PCa and csPCa suggests substantial heterogeneity in the way patients are selected for biopsy. Owing to this heterogeneity, we did not provide a pooled estimate for mpMRI NPV. The role of mpMRI as a triage test before prostate biopsy should be evaluated in the broader context of the selection of patients with a suspicion of (aggressive) PCa. In a recent retrospective study of 514 patients, mpMRI NPV for Gleason ≥7 cancers was 91% when the PSA density was ≤0.2 ng/ml/ml, and only 71% when the PSA density was >0.2 ng/ml/ml ( p = 0.003) [70] . In another series of 288 biopsy-naïve patients, no csPCa (Gleason score ≥7 or maximum cancer core length ≥4 mm) was found in 44 patients with a PSA density of <0.15 ng/ml/ml and a PI-RADS v2 score of <3/5 [71] . We believe that such prestratification of the risk of csPCa is an interesting way for rationalising the use of mpMRI before biopsy. Patients found at very low risk would be spared both mpMRI and biopsy. Patients at a low risk—for whom mpMRI would have an NPV high enough to be used as a triage test—could avoid biopsy in case of negative mpMRI. Patients at a higher risk would need biopsy even in case of negative mpMRI. Many tools can be used to risk stratify the population of patients referred to biopsy, ranging from simple parameters such as PSA density to more complicated risk calculators [72 73] . The impact of these tools on the NPV of prebiopsy mpMRI needs to be carefully evaluated, both in the biopsy-naïve and in the repeat biopsy setting. For the moment, it is impossible to make any recommendations on the best way to risk stratify patients before referring them for mpMRI.
Secondly, the large variability in the definition of csPCa precludes any definitive conclusion on the ability of mpMRI to rule out aggressive cancer. The issue of the most appropriate definition of csPCa on biopsy is complex, since biopsy results may accurately reflect neither tumour burden nor aggressiveness. Nonetheless, there is an urgent need to standardise the histological definition(s) of csPCa, to allow meaningful comparisons between studies.
Thirdly, the specificity of mpMRI remains moderate, and there is a substantial proportion of false positives in the lesions scored 3/5 or 4/5 [1 74 75] , even with the new PI-RADS v2 score [76] . In a series of 62 patients with 116 lesions biopsied under magnetic resonance/ultrasound fusion, the overall cancer detection rates for PI-RADS v2 scores of 3/5 and 4/5 were only 15.8% and 29.8%, respectively [77] . In theory, a triage test used to rule out a disease needs to be highly sensitive for this disease. However, if its specificity is too low, it will be clinically useless since most patients will be positive, whether they have the disease or not. Therefore, if mpMRI is to be used as a triage test in the future, there is a need to improve its specificity. This could be achieved by a continuous refinement of scores [78] . Promising results in characterising csPCa have also been reported with a quantitative analysis [79] .
Finally, all published studies were conducted in specialised centres. The broad use of mpMRI as a triage test assumes good interobserver reproducibility. Unfortunately, interobserver reproducibility of existing scoring systems remains moderate [62 63 80] even with the use of the PI-RADS v2 score [80 81] . Studies evaluating on a large scale the reproducibility of mpMRI findings between expert and nonexpert centres are currently lacking.
Three systematic reviews (including two meta-analyses) regarding the role of mpMRI in localised PCa have been published recently 4 5 6 . Crucially, all three reviews focused exclusively on the sensitivity of mpMRI-targeted, guided, or fusion biopsies in diagnosing overall PCa and csPCa, using TRUS-guided prostate biopsies as reference standards. The impact of systematic biopsies on the outcome was not addressed in any of the reviews, within either the index test or the reference standard. Our review had a totally different research question and objective, focusing on NPV of mpMRI to see if a negative mpMRI can avoid the need for a prostate biopsy. As MRI-targeted/guided/fusion biopsies are not relevant if the mpMRI was negative for cancer, it can be argued that the three reviews assessed a different index test altogether. As such, we believe that the findings of this review are novel and unique, and pave the way for further focused clinical studies.
The current study represents the first systematic review addressing the role of mpMRI as a triage test before biopsy. The review elements were developed in conjunction with a multidisciplinary panel of experts (EAU Prostate Cancer Guidelines Panel), which included a patient representative, and the review was performed robustly in accordance with recognised standards. However, it is limited by the major heterogeneity of the existing literature in patient population, study design, and definitions of positive mpMRI and csPCa. It highlighted further areas of research that could help in defining the best use of mpMRI in the early detection of aggressive PCa in the future.
Although mpMRI can detect aggressive PCa with excellent sensitivity, a definitive conclusion on its role as a triage test before prostate biopsy will be possible only when three main issues are addressed. Firstly, because NPV depends on prevalence, and because overall PCa and csPCa prevalence was highly variable in the published series, it becomes mandatory to define the optimal way to pre-evaluate the risk of csPCa in patients with a suspicion of PCa. Depending on the risk category, mpMRI could then be used to obviate biopsies or not. Secondly, there is a need for consensus definitions of csPCa on biopsy findings to allow interstudy comparisons. Thirdly, although efforts have been made to standardise mpMRI technical protocols and interpretation in the past few years [11 60 76] , there is still a crucial need to improve mpMRI specificity and inter-reader reproducibility.
This systematic review was performed under the auspices of:
The European Association of Urology Guidelines Office Board
The European Association of Urology Prostate Cancer Guideline Panel
Author contributions: Olivier Rouvière had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.
Study concept and design: Rouvière, Mottet, Cornford.
Acquisition of data: Rouvière, Moldovan, Van den Broeck, Yuan.
Analysis and interpretation of data: Rouvière, Moldovan, Van den Broeck, Lam.
Drafting of the manuscript: Rouvière, Moldovan, Van den Broeck, Lam.
Critical revision of the manuscript for important intellectual content: Bellmunt, van den Bergh, Bolla, Briers, Van den Broeck, Cornford, Cumberbatch, De Santis, Fossati, Gross, Henry, Joniau, Lam, Matveev, Moldovan, van der Poel, van der Kwast, Rouvière, Schoots, Wiegel, Mottet.
Statistical analysis: None.
Obtaining funding: None.
Administrative, technical, or material support: Yuan, Sylvester, Marconi.
Supervision: None.
Other: None.
Financial disclosures: Olivier Rouvière certifies that all conflicts of interest, including specific financial interests and relationships and affiliations relevant to the subject matter or materials discussed in the manuscript (eg, employment/affiliation, grants or funding, consultancies, honoraria, stock ownership or options, expert testimony, royalties, or patents filed, received, or pending), are the following: Bellmunt is a company consultant for Janssen, Astellas, Pierre Fabre, Genentech, Merck, Ipsen, Pfizer, Novartis, and Sanofi Aventis. He has received research support from Takeda, Novartis, and Sanofi, and received travel grants from Pfizer and Pierre Fabre. Bolla has received company speaker honoraria from Ipsen and Astellas, honoraria or consultation fees from Janssen, and fellowship and travel grants from Janssen, AstraZeneca, and Astellas. Briers has received grant and research support from Ipsen, European Association of Urology, and Bayer; is an ex officio board member for Europa UOMO; is an ethics committee and advisory group member for REQUITE; is a member patient advisory board member for PAGMI; and is a member of SCA and EMA PCWP. Cornford is a company consultant for Astellas, Ipsen, and Ferring. He receives company speaker honoraria from Astellas, Janssen, Ipsen, and Pfizer; participates in trials from Ferring; and receives fellowships and travel grants from Astellas and Janssen. De Santis is a company consultant for GlaxoSmithKline, Janssen, Bayer, Novartis, Pierre Fabre, Astellas, Amgen, Eisai Inc., ESSA, Merck, and Synthon; has received company speaker honoraria from Pfizer, Takeda, Sanofi Aventis, Shionogi, Celgene, and Teva OncoGenex; has participated in trials for Pierre Fabre, Astellas, Exelixis, Bayer, and Roche; has received fellowship and travel grants from Bayer, Novartis, Ferring, Astellas, Sanofi Aventis, and Janssen; has received grant and research support from Pierre Fabre; has received honoraria from AstraZeneca; and is associated with Amgen. Joniau is a company consultant for Astellas, Ipsen, Bayer, Sanofi, and Janssen; has received company speaker honoraria from Astellas, Amgen, Bayer, Sanofi, Janssen, and Ipsen; has participated in trials for Astellas, Janssen, and Bayer; has received fellowship and travel grants from Astellas, Amgen, Bayer, Sanofi, Janssen, Ipsen, and Pfizer; and has received grant and research support from Astellas, Bayer, and Janssen. Matveev has received company speaker honoraria from Sanofi and Astellas, has participated in trials for Astellas, Pfizer and Novartis. Lam is a company consultant for and has received company speaker honoraria from Pfizer, GSK, Astellas, and Ipsen. van der Poel is a company consultant for Intuitive Surgical, has participated in trials for Astellas and Steba Biotech, and has received grant and research support from Astellas. Rouvière is a company consultant for EDAP-TMS, Bracco, and Philips; has received company speaker honoraria from EDAP-TMS, Bracco, and Philips; and has participated in trials for EDAP-TMS and Bracco. Wiegel has received company speaker honoraria from Astellas, Takeda, Hexal, Ipsen, Janssen-Cilac, and Ferring. Mottet has received grant and research support from Takeda Pharmaceutical, Millenium, Astellas, Pierre Fabre, Sanofi, and Pasteur, and has received honoraria or consultation fees from Takeda Pharaceutical, Millenium, Jansen, Astellas, BMS, Bayer, Ipsen, Ferring, Novartis, Nuclétron, Pierre Fabre, Sanofi, and Zeneca. van den Bergh, Van den Broeck, Cumberbatch, Fossati, Gross, Henry, van der Kwast, Sylvester, Yuan, Schoots, Moldovan, and Marconi have nothing to disclose.
Funding/Support and role of the sponsor: None.
A correlation with radical prostatectomy specimens has demonstrated that multiparametric magnetic resonance imaging (mpMRI) has excellent sensitivity in detecting prostate cancer (PCa) with a Gleason score of ≥7 1 2 3 . As a result, prostate mpMRI is increasingly used in patients with a suspicion of PCa to localise abnormal areas before biopsy. A large body of literature has shown that targeted biopsies of suspicious lesions seen on mpMRI (TBx) improved the detection of clinically significant PCa (csPCa), at least in the repeat biopsy setting 4 5 6 . As a result, it is now recommended that an mpMRI is performed before repeat biopsy to allow TBx of suspicious lesions in addition to standard biopsies [7] .
Some authors have recently suggested that, besides improving csPCa detection, mpMRI could also be used as a triage test so that patients with negative mpMRI findings could obviate biopsy. Such a strategy remains highly controversial [8] and depends upon the negative predictive value (NPV) of mpMRI. Therefore, the European Association of Urology Prostate Cancer Guidelines Panel undertook this systematic review and meta-analysis to assess the NPV of mpMRI in patients with a suspicion of PCa and, thus, its potential role in eliminating unnecessary prostate biopsy.
Our primary aim was to systematically evaluate the performance of negative prebiopsy prostate mpMRI in predicting a negative biopsy result for overall PCa and csPCa in biopsy-naïve men and in men with previously negative biopsies. A further objective was to explore and define factors that may contribute to relevant thresholds in order to provide guidance for future studies.
The review was performed according to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) statement [9] . The review protocol was published in PROSPERO database ( http://www.crd.york.ac.uk/PROSPERO; registration number CRD42015021929). Databases searched included the Embase and OVID Medline databases, the Cochrane database of systematic reviews, and the Cochrane Central Register for Clinical Trials, covering from January 1, 2000 to February 13, 2016. Systematic or standard prostate biopsies were used as reference standards, with positive or negative cases of PCa being determined by histopathological examination. The detailed search strategy is presented in Supplement 1.
Included studies focused on men who were assessed for suspected PCa by mpMRI before undergoing prostate biopsy. Studies enrolling both biopsy-naïve men and men who had undergone previous negative biopsies were included. Prebiopsy prostate mpMRI was considered the index test and comprised T2-weighted imaging (T2WI) and at least one functional imaging technique (diffusion-weighted imaging [DWI], dynamic contrast-enhanced imaging [DCEI], or magnetic resonance spectroscopic imaging [MRSI]). For inclusion, studies had to report on false negatives and true negatives, in order to calculate NPV (ie, results of systematic/standard prostate biopsies when the mpMRI was negative). When available, false positive and true positive findings were also noted to calculate the positive predictive value (PPV) and the cancer prevalence. There was restriction neither on the biopsy technique (transrectal or transperineal) nor on the number of biopsy cores. Studies using radical prostatectomy specimens as reference standards were excluded, as were studies evaluating men with histologically proven PCa. Studies with less than 50 participants were excluded. No language restrictions were applied.
Two reviewers (P.C.M. and T.V.D.B.) independently screened all abstracts and full-text articles for eligibility. Disagreement was resolved by consensus or reference to an independent third party (L.M.). All screening was performed using a predefined eligibility form.
Using a data extraction form developed a priori, the same two reviewers independently extracted data concerning study methodology, patient characteristics, technical characteristics of the MR scanners, mpMRI protocol, mpMRI scoring system, definition of positive mpMRI, biopsy protocol, and definition of csPCa. Any discrepancies concerning data extraction were resolved by consensus or reference to an independent arbiter (O.R. or T.B.L.).
To assess the risk of bias (RoB), all included reports were reviewed using the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool for diagnostic accuracy studies [10] .
Outcome data regarding false negative and true negative values of mpMRI before prostate biopsy were recorded as reported by authors. When not available, data were indirectly derived from specificity, sensitivity, and prevalence values reported by authors using an online Bayesian statistics calculator ( http://www.medcalc.com/bayes.html ). Descriptive statistics were used to summarise baseline characteristics and outcomes, including median and interquartile range (IQR) for estimates of NPV across studies. A correlation between mpMRI NPV and a positive biopsy rate was established using the Pearson's correlation coefficient.
A meta-analysis was undertaken to calculate pooled NPV and PPV. To ensure appropriate clinical homogeneity of the studies included in the meta-analysis, we selected only the studies enrolling biopsy-naïve patients and/or patients with a history of negative biopsy, and fulfilling the following criteria that were defined a priori: (1) reference standard consisting of prostate biopsy with at least 10 samples on all patients; (2) mpMRI protocol comprising at least T2WI and DWI; (3) mpMRI results presented as a five-level score, using a subjective Likert scale or the Prostate Imaging Reporting Data System (PI-RADS) score [11] ; (4) definition of positive mpMRI as a score ≥3/5 or ≥4/5; and (5) results reported on a per patient basis. In addition, only studies defining csPCa as Gleason ≥7 cancers were selected for the meta-analysis assessing the mpMRI NPV for csPCa. A bivariate random-effects approach was employed using the Midas package in Stata 12 (StataCorp LP, College Station, TX, USA). Since the NPV decreases and the PPV increases as the prevalence increases, post-test probability estimates of NPV and PPV were reported for the given values of the prevalence based on Bayes’ theorem.
For other studies not included in the meta-analysis based on the criteria described above, a narrative synthesis of the data was performed. To explore and define clinical heterogeneity, subgroups were analysed at patient level based on the following variables: biopsy-naïve versus previous negative biopsy; patients with positive versus negative digital rectal examination (DRE); mpMRI performed with an endorectal versus without an endorectal coil; transrectal ultrasound (TRUS) versus template transperineal (TTP) biopsy approach; and ≤16 cores versus >16 cores as the reference standard. Studies reporting mpMRI NPV for patients with a prostate-specific antigen (PSA) level of ≤10 ng/ml were also reported separately.
The study selection process is depicted in the PRISMA flow diagram ( Fig. 1 ). A total of 2980 abstracts were retrieved. After abstract screening and removal of duplicates, 240 articles were eligible for full text screening, of which 48 studies were eligible for inclusion 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 .
Out of the 48 included studies, 42 were single-centre and six were multicentre studies. Thirty-four studies were prospective and six were retrospective, whilst the design of the rest was unclear. RoB assessment using QUADAS-2 was performed for each of the individual studies ( Fig. 2 A and B). Overall, the RoB was highly heterogeneous across studies for all criteria, except for the reference standard domain, in which RoB was low in most studies.
The 48 studies comprised a total of 9613 men who underwent prostate mpMRI followed by biopsy. The study and patient baseline characteristics are presented in Table 1 . The patient population consisted of biopsy-naive men in nine studies, men with at least one previous negative biopsy in 16 studies, and both biopsy-naïve men and men with a history of previous negative biopsy in nine studies. In 14 studies, the biopsy history of the patients was unclear.
Study | Study design | Period | Population | Pt Nb | Mean/median* age (yr) | Mean/median* PSA (ng/ml) | Mean/median* prostate volume (cm 3 ) | Magnetic field strength | MR pulse sequences | Endorectal coil | MR score | Definition of positive MRI | Reference standard |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Hauth (2015) [25] | Prospective | 2011–2013 | FB | 94 | 64 (43–83) | 9 (3–31) | 51 (17–140) | 1.5 T | T2WI/DWI/DCEI/MRSI | No | PI-RADS v1 | ≥3 | 11–13-core TRUS SBx + TBx |
Lamb (2015) [36] | Retrospective | 2013–2013 | FB & PNB | 173 | NR | NR | NR | 1.5 T | T2WI/DWI | NR | NR | NR | 12-core TRUS SBx |
Brock (2015) [15] | Prospective | 2013–2014 | PNB | 168 | 64* (IQR 59–70) | 9.2* (IQR 6.7–13.4) | 55.4* (IQR 42–80) | 3 T | T2WI/DWI/DCEI | No | PI-RADS v1 | NR | 12/24-core TRUS SBx + TBx |
Grenabo Bergdahl (2016) [22] | Prospective | 2013–2014 | FB & PNB | 83 | 69.3* (IQR 69–69.6) | 1.6* (IQR 0.9–2.7) | NR | 3 T | T2WI/DWI/DCEI/MRSI | No | PI-RADS v1 | ≥3 | 10-core TRUS SBx + TBx |
Wang (2015) [58] | Prospective | 2002–2009 | FB & PNB | 586 | 70 (26–91) | 11.11* (0.02–9794) | NR | 1.5 T | T2WI/DWI/DCEI/MRSI | Yes | PI-RADS v1 | ≥3 | TRUS SBx |
Pepe (2015) [41] | Prospective | 2011–2014 | PNB | 100 | 64* | 8.6* (4.2–10) | NR | 3 T | T2WI/DWI/DCEI/MRSI | No | PI-RADS v1 | ≥4 | TPBx + TBx |
Panebianco (2015) [39] | Prospective | 2011–2014 | FB (61.62%) & PNB (38.34%) | 925 (1140 total cohort) |
NR | NR | NR | 3 T | T2WI/DWI/DCEI | Yes | PI-RADS v1 | NR | 14-core TRUS SBx; 45-core sat TPBx + TBx |
Radtke (2015) [46] | Prospective | 2013–2013 | FB (63.3%) & PNB (36.7%) | 294 | 64* (60–71) | 7.3 (6.0) | 47 (37.5) | 3 T | T2WI/DWI/DCEI | No | PI-RADS v1 | PI-RADS ≥2; PI-RADS ≥3; PI-RADS ≥4; PI-RADS = 5; |
24-core TPBx + TBx |
Itatani (2014) [27] | Retrospective | 2004–2007 | NR | 193 | 68.9 (8.4); 70* (47–89) | 11.8 (15.9); 7.9* (1.22–159) | NR | 1.5 T | T2WI/DWI/DCEI | No | 1–5 scale (Likert) | ≥3 | 12–14-core TRUS SBx |
Porpiglia (2014) [44] | Prospective | 2011–2013 | PNB | 170 | 65* (60–70) | 6.9* (5.2–9.8) | 42* (36–48) | 1.5 T | T2WI/DWI/DCEI | Yes | Dichotomous | Positive: at least 2/3 MR seq. with suspicious findings | 18–24-core TRUS SBx (volume dependent) |
Thompson (2014) [56] | Prospective | 2012–2013 | FB (88%) & PNB (12%) | 150 | 62.4* (IQR 55.0–66.4) | 5.6* (IQR 4.5–7.5) | 40* (IQR 30–57) | 1.5 T (47%) & 3 T (53%) | T2WI/DWI/DCEI | No | PI-RADS v1 | ≥3 | Median of 30 TPBx (volume dependent) |
Pokorny (2014) [43] | Prospective | 2012–2013 | FB | 223 | 63* (IQR 57–68) | 5.3* (IQR 4.1–6.6) | 41* (IQR 30–59) | 3 T | T2WI/DWI/DCEI | No | PI-RADS v1 | ≥3 (primary); ≥4 |
12-core TRUS SBx + TBx |
Petrillo (2014) [42] | Prospective | 2009–2010 | NR | 136 | NR | NR | NR | 1.5 T | T2WI/DWI/MRSI | Yes | 1–5 scale (Likert) | ≥3 | 12–16-core TRUS SBx (volume + PSA dependent) |
Javali (2014) [29] | Retrospective | 2002–2011 | NR | 140 | Control: 62.4 (10.5); Study: 62.9 (12.1) | Control: 6.8 (2.3); Study: 6.87 (2.6) | Control: 44 (14.2); Study: 43 (18.4) | 1.5 T | T2WI/MRSI | Yes | Dichotomous | Cit/[Cho + Cr] < 1.2 | 6-core TRUS SBx ( n = 69), 12-core TRUS SBx ( n = 119) |
Abd-Alazeez (2014) [13] | Prospective | 2007–2011 | FB | 129 | 62* (41–82) | 5.8* (1.2–20) | 40* (16–137) | 1.5 & 3 T | T2WI/DWI/DCEI | No | PI-RADS v1 | ≥3 (primary); ≥4 |
20-core TPBx |
Abd-Alazeez (2014) [12] | Retrospective | NR | PNB | 54 | 64* (39–75) | 10* (2–23) | 53* (19–136) | 1.5 & 3 T | T2WI/DWI/DCEI | No | PI-RADS v1 | ≥3 (primary); ≥4 |
≥20-core TPBx + TBx ( n = 15) |
Matsuoka (2014) [37] | Prospective | 2007–2012 | NR | 135 | 67* (50–80) | 7.0* (2.9–19.8) | 25.4* (12.7–90.2) | 1.5 T | T2WI/DWI | No | 1–5 scale (Likert) | ≥3 | 14-core TRUS SBX |
Junker (2013) [30] | Retrospective | 2011–2013 | PNB | 73 | 62 (7.4) | 7.0* (5.1–12.9) | 45* (34–61) | 3 T | T2WI/DWI/DCEI | No | PI-RADS | PI-RADS ≥10 and ≥11 for all PCa PI-RADS ≥13 for significant PCa |
10-core TRUS SBx + TBx |
Busetto (2013) [16] | Prospective | 2010–2012 | PNB | 163 | 66.4 (5.3) | 6.8 (1.6) | NR | 3 T | T2WI/DWI/DCEI/MRSI | Yes | NR | NR | 10-core TRUS SBx + TBx |
Rais-Bahrami (2013) [47] | Prospective | 2007–2012 | NR | 583 | 61.3 (8.4) | 9.9 (13.1) | NR | 3 T | T2WI/DWI/DCEI/MRSI | Yes | 1–4 scale (Likert) | ≥2 ≥3 |
12-core TRUS SBx + TBx |
Kuru (2013) [34] | Prospective | 2010–2011 | FB (51%) & PNB (49%) | 347 | 65.3 (42–82) | 9.85 (0.5–104) | 48.7 (9–180) | 3 T | T2WI/DWI/DCEI | No | 1–3 scale (Likert) | ≥2 | 12–36-core TRUS SBx (volume dependent) + TBx |
Ferda (2013) [20] | Prospective | NR | NR | 164 | (49–74) | (4.2–123) | NR | 3 T | T2WI/DWI/DCEI/MRSI | No | NR | In house | TRUS SBx |
Ganie (2013) [21] | NR | 2007–2009 | PNB | 87 | NR | NR | NR | 1.5 T | T2WI/MRSI | Yes | MRSI Cho/Cit ratio | In house | 6 core TRUS SBx + MRI TBx |
Vinet (2013) [57] | Prospective | 2009–2011 | FB | 69 | NR | 5.2* (3.2–28) | NR | 1.5 T (35 pts) & 3 T (34 pts) | T2WI/DWI/DCEI | No | 1–5 scale (Likert) | ≥3 | 12-core TRUS SBx + TBx |
Numao (2013) [38] | Prospective | 2006–2010 | FB | 351 | 65* (59–70) | 6.3* (4.9–9.1) | 32* (24–42) | 1.5 T | T2WI/DWI/DCEI (no DCEI in 42 pts) | No | 1–5 scale (Likert) | ≥3 | 3D 26-core (12 TRUS SBx + 14 TPBx – 203 pts); 3D 14-core (6 TRUS SBx + 8 TPBx – 102 pts); TPBx 14 core (46 pts) |
Belas (2012) [14] | Prospective | 2010–2011 | FB | 71 | 66* (47–76) | 7* (4–10) | 45* (15–150) | 1.5 T | T2WI/DWI/DCEI | No | TZ: 0–4 scale PZ: 0–10 scale |
TZ: >2 PZ: >6 |
12-core TRUS SBx + TBx |
Ibrahiem (2012) [26] | Prospective | 2008–2009 | FB | 100 | 65.03 (7.13) | 26.3 (24.2) | 60.09 (28.7) | 1.5 T | T2WI/DWI | No | NR | In house | 12-core TRUS SBX |
Sciarra (2012) [51] | Prospective | 2008–2011 | PNB | 84 | 64.09 (46–76) | 7.07 (4.2–15.5) | NR | 3 T | T2WI/DWI/DCEI/MRSI | Yes | NR | NR | 10-core TRUS Bx + TBx |
Portalez (2012) [45] | Prospective | 2011 | PNB | 129 | 64.7 (47–79) | 9.6 (2.7–40) | 51.1 (12–192) | 1.5 T | T2WI/DWI/DCEI | Mixed | 1–5 scale (Likert) PI-RADS |
Likert ≥3 PI-RADS ≥9 |
10–12-core TRUS SBx + TBx |
Watanabe (2012) [59] | Prospective | 2004–2008 | NR | 1448 | 72 (7.5) | NR | NR | 1.5 T | T2WI/DWI | No | NR | ADC value ≤1.35 × 10 −3 mm 2 /s | 8-core TRUS SBx + TBx |
Tamada (2011) [54] | Retrospective | 2006–2009 | NR | 50 | 70 (40–84) | 6.84* (4.06–9.94) | NR | 1.5 T | T2WI/DWI/DCEI | No | NR | In house | 12-core TRUS SBx |
Choi (2011) [18] | NR | 2009–2010 | NR | 51 | 67.16 (56–90) | 14.16 (1.02–38.9) | 42.98 (13.8–77.3) | 3 T | T2WI/DWI | NR | NR | NR | 10–12-core TRUS SBx + TBx |
Iwazawa (2011) [28] | Retrospective | 2008–2009 | NR | 178 | 68.8 (41–86) | 20.51 (4.04–568.5) | NR | 1.5 T | T2WI/DWI/DCEI | NR | 1–4 scale (Likert) | NR | 10–12-core TRUS SBx (TBx included in SBx chart) |
Rouse (2011) [48] | Prospective | 2005–2007 | PNB | 114 | 63.6 (41–83) | 13.4 (0–228) | NR | 1.5 T | T2WI/DWI/DCEI | NR | 1–5 scale (Likert) | ≥3 | TRUS SBx |
Haffner (2011) [23] | Prospective | 2005–2009 | FB | 555 | 64* (47–83) | 6.75* (0.18–100) | 46* (15–200) | 1.5 T | T2WI/DCEI | No | 1–5 scale (Likert) | ≥3 | 10-core TRUS SBx + TBx |
Panebianco (2010) [40] | Prospective | 2007–2009 | PNB | 150 | 61.2 (46–78) | 9.42 (3.91) | 41.17 (7.47) | 1.5 T | T2WI/DCEI/MRSI | Yes | NR | In house | 10-core TRUS SBx (TBx included in SBx chart) |
Roy (2010) [49] | Not specified | 2011–2009 | FB (53%) & PNB (47%) | 103 | 63 (52–78) | 7* | NR | 3 T | T2WI/DWI/DCEI | Yes | NR | NR | 8-core TRUS SBx + TBx |
Testa (2010) [55] | Not specified | 2007 | PNB | 54 | 63.9 (52–76) | 11.4 (3–42) | 59.3 (30–150) | 1.5 T | T2WI/MRSI | Yes | 1–3 scale (Likert) | ≥2 | 12-core TRUS SBx + TBx |
Sciarra (2010) [52] | Prospective | 2007–2009 | PNB | 110 | 63.5 (49–74) | NR | NR | 1.5 T | T2WI/DCEI/MRSI | Yes | NR | In house | 10-core TRUS SBx + TBx |
Kitajima (2010) [31] | Prospective | 2008–2009 | NR | 53 | 69* (56–84) | 11.1* (4.2–112.1) | NR | 3 T | T2WI/DWI/DCEI | No | 1–5 scale (Likert) | ≥3 | 20-core TPBx |
Labanaris (2010) [35] | Prospective | 2004–2008 | PNB | 260 | NR | NR | NR | 1 T | T2WI/DWI/DCEI | Yes | Dichotomous | In house | 18-core TRUS SBx |
Kumar (2009) [32] | NR | NR | NR | 61 | 65.3 (9.3) | 16.5 (0.21–155) | NR | 1.5 T | T2WI/MRSI | Yes | NR | (Cit/(Cho + Cr) ≤ 1.2 | TRUS Bx |
Schmuecking (2009) [50] | NR | NR | FB & PNB | 67 | 68 | 11.5 | NR | 1.5 T | T2WI/DCEI | No | NR | NR | 20-core Bx |
Cheikh (2009) [17] | Retrospective | 2005–2008 | PNB | 93 | 63.2 (52–74) | 9.63 (1.6–40) | NR | 1.5 T | T2WI/DCEI | No | Dichotomous | In house | 12-core TRUS SBx + TBx |
Cirillo (2008) [19] | Prospective | 2004–2006 | PNB | 54 | 65.5 (5.2) | 10.8 (7.5) | NR | 1.5 T | T2WI/MRSI | Yes | Dichotomous | In house | 10-core TRUS SBx + TBx |
Kumar (2007) [33] | Prospective | 2003–2005 | NR | 83 | NR | NR | NR | 1.5 T | T2WI/MRSI | Yes | NR | NR | 12-core TRUS SBx + TBx |
Squillaci (2005) [53] | Prospective | 2004–2005 | NR | 65 | NR | NR | NR | 1.5 T | T2WI/DCEI/MRSI | No | 1–3 scale (Likert) | ≥2 | 10-core TRUS SBx + TBx |
Hara (2005) [24] | Prospective | 2003–2004 | FB | 90 | 67.2 (NR) | NR | NR | 1.5 T | T2WI/DCEI | No | 1–3 scale (Likert) | ≥2 = 3 |
14-core TRUS SBx |
The magnetic field strength was 1, 1.5, and 3 T in one, 28, and 15 studies, respectively. Four studies used both 1.5 and 3 T MR systems. DWI and DCEI were used in 36 and 35 studies, respectively. Nineteen studies also added MRSI. An endorectal coil was used in 18 studies. The definition of positive mpMRI varied across studies. The PI-RADS v1 score was used in 12 studies, a five-level subjective (Likert) score was used in eight studies, and one study reported data based on the two scoring systems. In-house criteria were used in 13 studies for defining positive mpMRI, and five studies used a dichotomous definition. Nine studies did not report on the criteria for positive mpMRI. No study used the PI-RADS v2 score.
Regarding the reference standard, TRUS-guided biopsies were used in 39 studies, TTP biopsies in six studies, and mixed TRUS-guided and TTP biopsies in two studies. In one study, the biopsy approach was unclear. The number of cores per biopsy procedure was ≤16 in 30 studies, >16 in nine studies, and variable among patients in three studies. For six studies, the number of biopsy cores taken was unclear.
At patient level, the median biopsy positivity rate (ie, cancer prevalence) was 50.4% (IQR, 36.4–57.7%) for overall cancer and 32.9% (IQR, 28.1–37.2%) for csPCa ( Table 2 ). The median mpMRI NPV was 82.4% (IQR, 69.0–92.4%) for overall cancer and 88.1% (IQR, 85.7–92.3) for csPCa. NPV significantly decreased when cancer prevalence increased, both for overall cancer ( r = –0.64, p < 0.0001) and csPCa ( r = –0.75, p = 0.032; Fig. 3 ). In addition, NPV was highly dependent on the definition used for csPCa, with differences of up to 21% when several definitions were used in the same dataset [12 13 38 47 48] .
Study | Overall PCa prevalence (%) | Reporting level | Multiparametric MRI performance for PCa detection | Definition of csPCa | csPCa prevalence | Multiparametric MRI performance for csPCa detection | ||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
TN | FN | TP | FP | NPV | PPV | TN | FN | TP | FP | NPV | PPV | |||||
Hauth (2015) [25] | 45.7 | Patient | 6 | 1 | 42 | 45 | 85.7% | 48.3% | Low grade: GS ≤ 6 High grade: GS ≥ 7 |
NR | NR | NR | NR | NR | NR | NR |
Lesion | 59 | 13 | 55 | 73 | 81.9% | 43% | ||||||||||
Lamb (2015) [36] | 65.9 | Patient | 23 | 22 | 92 | 36 | 51.1% | 71.9% | GS ≥ 7 | 50.9% | 31 | 14 | 71 | 57 | 68.9% | 55.5% |
Brock (2015) [15] | 42.3 | Patient | 17 | 7 | 56 | 88 | 70.8% | SBx: 38.8% TBx: 22.2% Duo: 44.4% |
Epstein: GS > 6 and/or max CCL ≥50% | 24.4% | SBx: 21 | SBx: 3 | SBx: 38 TBx: 27 duo: 47 |
SBx: 106 TBx: 117 duo: 97 |
87.5% | SBx: 26.4% TBx: 18.8% duo: 32.6% |
Grenabo Bergdahl (2016) [22] | 33.7 | Patient | 36 | 7 | 19 | 21 | 83.7% | 47.5% | Clinically insignificant PCa: T1c, PSAd < 0.15, GS < 7, ≤2 positive cores, and unilateral cancer | NR | NR | NR | NR | NR | NR | NR |
Wang (2015) [58] | 58 | Patient | 165 | 8 | 332 | 81 | 95.4% | 80.4% | NR | NR | NR | NR | NR | NR | NR | NR |
Pepe (2015) [41] | 37 | Patient | 23 | 8 | 29 | 40 | 74.2% | 42% | GS ≥ 7 or GS 6 with CCL ≥ 50% | NR | NR | NR | NR | NR | 100% | 55.8% |
Panebianco (2015) [39] | 74.7 | Patient | Group A (satBx): 104 | Group A (satBx): 43 | Group A: 186 | Group A: 22 | Group A (satBx): 70.7% | Group A: 89.4% | NR | 60% | Group A: 147 | Group A: 0 | Group A: 183 | Group A: 25 | Group A: 100% | Group A: 88% |
Group B (TRUSGB NR TRUS G satBx): 93 | Group B (TRUSGB NR TRUS G satBx): 37 | Group B: 417 before and 425 after satBx | Group B: 23/440 and 15/440 after satBx. | Group B (TRUSGB–TRUS G satBx): 71.5% | Group B: 94.8% before and 96.6% after satBx | 71.9% | Group B: 130 | Group B: 0 | Group B: 410 |
Group B: 30 | Group B: 100% | Group B: 93.2% | ||||
Radtke (2015) [46] | 51 | Patient | ≥2/5: 80 ≥3: 103 ≥4: 138 = 5: 142 |
≥2/5: 18 ≥3/5: 38 ≥4/5: 78 = 5/5: 126 |
≥2/5: 132 ≥3/5: 112 ≥4/5: 72 = 5/5: 24 |
≥2/5: 64 ≥3/5: 41 ≥4/5: 6 = 5/5: 2 |
≥2/5: 81.6% ≥ 3/5: 73.1% ≥ 4/5: 63.9% = 5/5: 53% |
≥2/5: 67.4% ≥ 3/5: 73.2% ≥ 4/5: 92.3% = 5/5: 92.3% |
GS ≥ 7 | 29.3% | ≥2/5: 91 ≥3/5: 124 ≥4/5: 183 = 5/5: 203 |
≥2/5: 7 ≥3/5: 17 ≥4/5: 33 = 5/5: 65 |
≥2/5: 79 ≥3/5: 69 ≥4/5: 53 = 5/5: 21 |
≥2/5: 117 ≥3/5: 84 ≥4/5: 25 = 5/5: 5 |
≥2/5: 92.2% ≥3/5: 87.9% ≥4/5: 84.7% = 5/5: 75.8% |
≥2/5: 40.3% ≥3/5: 45.1% ≥4/5: 68% = 5/5: 80.7% |
Itatani (2014) [27] | 13 | Patient | 168 | 25 | NR | NR | 87% | NR | (1) PSAd ≥ 0.1 or GP 4/5 or ≥ 3/6 pos cores; max CCL < 50% (2) PSAd ≥ 0.15 or GP 4/5 or max core length invasion < 3 mm (min 6 cores) |
NR | NR | NR | NR | NR | NR | NR |
Porpiglia (2014) [44] | 30.6 | Patient | 107 | 5 | 47 | 11 | 95.5% | 81% | NR | NR | NR | NR | NR | NR | NR | NR |
Thompson (2014) [56] | 61.3 | Patient | 35 | 16 | 76 | 23 | 68.6% | 76.7% | Moderate or high risk Moderate risk: GS 7 (GP4 >5%) and <50% of positive cores or GS 6–7 (GP4 ≤ 5%) and either ≥30% of positive cores or max core length invasion ≥8 mm High risk: GS ≥ 7 (GP4 > 5%); ≥50% + cores or GS ≥ 8 |
34% | 49 | 2 | 49 | 50 | 96% | 49.5% |
Pokorny (2014) [43] | 63.7 | Patient | ≥3/5: 56 ≥4/5: 74 |
≥3/5: 25 ≥4/5: 40 |
≥3/5: 101 ≥4/5: 86 |
≥3/5: 41 ≥4/5: 23 |
≥3/5: 69.1% ≥4/5: 64.9% |
≥3/5: 71.1% ≥4/5: 78.9% |
NR | NR | NR | NR | NR | NR | NR | NR |
Petrillo (2014) [42] | 18.4 | Patient | 56 | 4 | 21 | 55 | 93% | 28% | NR | NR | NR | NR | NR | NR | NR | NR |
Javali (2014) [29] | 16.4 | Patient | 49 | 1 | 22 | 68 | 98% | 24.4% | NR | NR | NR | NR | NR | NR | NR | NR |
Abd-Alazeez (2014) [13] | 54.7 | Lobe | ≥3/5: 33 | ≥3/5: 14 | ≥3/5: 127 | ≥3/5: 84 | ≥3/5: 70% | ≥3/5: 60% | Def 1: GS ≥ 4 + 3 and/or max CCL ≥ 6 mm Def 2: GS ≥ 3 + 4 and/or max CCL ≥ 4 mm Def 3: GS ≥ 4 + 3 Def 4: GS ≥ 3 + 4 Def 5: max CCL ≥ 6 mm Def 6: max CCL ≥ 4 mm |
Def 1: NR Def 2: 44.2% Def 3: 23.2% Def 4: 36% Def 5: 32.9% Def 6: 39.5% |
Def 1: 46 Def 2: 42 Def 3: 47 Def 4: 43 Def 5: 46 Def 6: 43 |
Def 1: 1 Def 2: 5 Def 3: 0 Def 4: 4 Def 5: 1 Def 6: 4 |
Def 1: 45 Def 2: 72 Def 3: 13 Def 4: 50 Def 5: 39 Def 6: 59 |
Def 1: 166 Def2: 139 Def 3: 198 Def 4: 161 Def 5: 172 Def 6: 152 |
Def 1: 98 Def 2: 89 Def 3: 100 Def 4: 92 Def 5: 98 Def 6: 91 |
Def 1: 21 Def 2: 34 Deg 3: 6 Def 4: 24 Def 5: 19 Def 6: 28 |
≥4/5: 87 | ≥3/5: 62 | ≥3/5: 79 | ≥3/5: 30 | ≥3/5: 58% | ≥3/5: 73% | Def 1: 140 Def 2: 124 Def 3: 148 Def 4: 133 Def 5: 141 Def 6: 131 |
Def 1: 9 Def 2: 25 Def 3: 1 Def 4: 16 Def 5: 8 Def 6: 18 |
Def 1: 37 Def 2: 52 Def 3: 12 Def 4: 38 Def 5: 32 Def 6: 45 |
Def 1: 72 Def 2: 57 Def 3: 97 Def 4: 71 Def 5: 77 Def 6: 64 |
Def 1: 94 Def 2: 83 Def 3: 99 Def 4: 89 Def 5: 95 Def 6: 88 |
Def 1: 34 Def 2: 48 Def 3: 11 Def 4: 35 Def 5: 30 Def 6: 42 |
|||||
Abd-Alazeez (2014) [12] | 47.2 | Lobe | ≥3/5: 26 | ≥3/5: 13 | ≥3/5: 38 | ≥3/5: 31 | ≥3/5: 66% | ≥3/5: 55% | Def 1: GS ≥ 4 + 3 and/or max CCL ≥ 6 mm Def 2: GS ≥ 3 + 4 and/or max CCL ≥ 4 mm Def 3: GS ≥ 4 + 3 Def 4: GS ≥ 3 + 4 Def 5: max CCL ≥ 6 mm Def 6: max CCL ≥ 4 mm |
Def 1: 18.5% Def 2: 31.5% Def 3: 4.6% Def 4: 21.3% Def 5: 16.7% Def 6: 25% |
Def 1: 37 Def 2: 31 Def 3: 39 Def 4: 36 Def 5: 37 Def 6: 32 |
Def 1: 2 Def 2: 8 Def 3: 0 Def 4: 3 Def 5: 2 Def 6: 7 |
Def 1: 18 Def 2: 26 Def 3: 5 Def 4: 20 Def 5: 16 Def 6: 20 |
Def 1: 51 Def 2: 43 Def 3: 64 Def 4: 49 Def 5: 53 Def 6: 49 |
Def 1: 95 Def 2: 79 Def 3: 100 Def 4: 92 Def 5: 95 Def 6: 82 |
Def 1: 26 Def 2: 38 Def 3: 7 Def 4: 29 Def 5: 23 Def 6: 29 |
≥4/5: 49 | ≥4/5: 25 | ≥4/5: 26 | ≥4/5: 8 | ≥4/5: 66% | ≥4/5: 76% | Def 1: 70 Def 2: 63 Def 3: 73 Def 4: 68 Def 5: 70 Def 6: 64 |
Def 1: 4 Def 2: 11 Def 3: 1 Def 4: 6 Def 5: 4 Def 6: 10 |
Def 1: 16 Def 2: 23 Def 3: 4 Def 4: 17 Def 5: 14 Def 6: 17 |
Def 1: 18; Def 2: 11 Def 3: 30 Def 4: 17 Def 5: 20 Def 6: 17 |
Def 1: 94 Def 2: 85 Def 3: 99 Def 4: 92 Def 5: 94 Def 6: 86 |
Def 1: 47 Def 2: 67 Def 3: 12 Def 4: 50 Def 5: 41 Def 6: 49 |
|||||
Matsuoka (2014) [37] | 64.8 | Lobe | 46 | 49 | 149 | 26 | 48.4% | 85.1% | NR | NR | NR | NR | NR | NR | NR | NR |
Junker (2013) [30] | 53.4 | Patient | ≥10/15: 21 ≥11/15: 28 |
≥10/15: 4 ≥11/15: 12 |
≥10/15: 35 ≥11/15: 27 |
≥10/15: 13 ≥11/15: 6 |
≥10/15: 84% ≥11/15: 70% |
≥10/15: 72.9% ≥11/15: 81.8% |
GS ≥ 4 + 3 | 13.7% | ≥13: 54 | ≥13: 2 | ≥13: 8 | ≥13: 9 | ≥13: 96.4% | ≥13: 47% |
Busetto (2013) [16] | 41.7 | Patient | 59 | 7 | 61 | 36 | 89% | 63% | NR | NR | NR | NR | NR | NR | NR | NR |
Rais-Bahrami (2013) [47] | 54.2 | Patient | ≥2/4 : 80 | ≥2/4: 275 | ≥2/4: 187 | ≥2/4: 275 | ≥2/4: 66% | ≥2/4: 59% | GS ≥ 7: GS ≥ 8 |
31.7% | NR | NR | NR | NR | GS ≥ 7: 91% GS ≥ 8: 91% |
GS ≥ 7: 38% GS ≥ 8: 18% |
≥3/4: 251 | ≥3/4: 76 | ≥3/4: 16 | ≥3/4: 76 | ≥3/4: 51% | ≥3/4: 82% | NR | NR | NR | NR | GS ≥ 7: 75% GS ≥ 8: 91% |
GS ≥ 7: 67% GS ≥ 8: 41% |
|||||
Kuru (2013) [34] | 57.6 | Patient | 80 | 14 | 67 | 186 | 85.1% | 73.5% | NR | NR | NR | NR | NR | NR | NR | NR |
Ferda (2013) [20] | 51.2 | Patient | 52 | 2 | 82 | 28 | 96.3% | 74.5% | NR | NR | NR | NR | NR | NR | NR | NR |
Ganie (2013) [21] | 74.7 | Patient | 13 | 3 | 62 | 9 | 59.1% | 95.4% | NR | NR | NR | NR | NR | NR | NR | NR |
Vinet (2013) [57] | 49.3 | Patient | ≥3/5: 11 | ≥3/5: 6 | ≥3/5: 28 | ≥3/5: 24 | ≥3/5: 64.7% | ≥3/5: 53.8% | NR | NR | NR | NR | NR | NR | NR | NR |
≥4/5: 22 | ≥4/5: 11 | ≥4/5: 23 | ≥4/5: 13 | ≥4/5: 66.7% | ≥4/5: 63.8% | NR | NR | NR | NR | NR | NR | NR | NR | |||
Numao (2013) [38] | 45 | Patient | 137 | 57 | 101 | 56 | 70.6% | 64.3% | Def 1: GS ≥4 + 3 and/or ≥20% positive cores and/or max CCL ≥5 mm Def 2: GS ≥ 3 + 4 and/or ≥20% + cores and/or max CCL ≥5 mm Def 3: GS ≥ 3 + 4 and/or ≥20% + cores |
Def 1: 33.3% Def 2:37.8% Def 3: 35.8% |
Def 1: 74 Def 2: 65 Def 3: 69 |
Def 1: 83 Def 2: 92 Def 3: 88 |
Def 1: 160 Def 2: 153 Def 3: 156 |
Def 1: 34 Def 2: 41 Def 3: 38 |
Def 1: 82.4% Def 2: 78.8% Def 3: 80.4% |
Def 1: 58.8% Def 2: 58.5% Def 3: 56% |
Belas (2012) [14] | 53.5 | Patient | 22 | 12 | 23 | 13 | 64.7% | 63.8% | NR | NR | NR | NR | NR | NR | NR | NR |
Ibrahiem (2012) [26] | 73.9 | Patient | 14 | 11 | 57 | 10 | 56% | 85.1% | NR | NR | NR | NR | NR | NR | NR | NR |
Sciarra (2012) [51] | 34.5 | Patient | 41 | 4 | 25 | 14 | 91.1% | 64.1% | NR | NR | NR | NR | NR | NR | NR | NR |
Portalez (2012) [45] | 48.1 | Lesion | Likert: 357 | Likert: 50 | Likert: 81 | Likert: 50 | Likert: 95% | Likert: 38% | Max CCL >3 mm and/or GG 4/5 | NR | NR | NR | NR | NR | NR | NR |
PI-RADS: 404 | PI-RADS: 47 | PI-RADS: 34 | PI-RADS: 47 | PI-RADS: 95% | PI-RADS: 58% | |||||||||||
Watanabe (2012) [59] | 48.1 | Patient | 485 | 73 | 624 | 266 | 86.9% | 70.1% | NR | NR | NR | NR | NR | NR | NR | NR |
Tamada (2011) [54] | 70 | Patient | 12 | 6 | 29 | 3 | 67% | 91% | NR | NR | NR | NR | NR | NR | NR | NR |
Region | 277 | 48 | 55 | 20 | 85% | 73% | ||||||||||
Choi (2011) [18] | 70.6 | Patient | 9 | 5 | 31 | 6 | 64.2% | 75.7% | NR | NR | NR | NR | NR | NR | NR | NR |
Iwazawa (2011) [28] | 40.5 | Region | 887 | 86 | 232 | 219 | 91.1% | 51.4% | NR | NR | NR | NR | NR | NR | NR | NR |
Rouse (2011) [48] | 33.7 | Sextant | 145 | 11 | 74 | 22 | 92.9% | 77.1% | GS ≥ 7: Def 1: ≥3 mm Def 2: ≥5 mm |
Def 1: 26.6% Def 2: 26.2% |
Def 1: 153 Def 2: 153 |
Def 1: 3 Def 2: 3 |
Def 1: 64 Def 1: 63 |
Def 1: 32 Def 2: 33 |
Def 1: 98.1% Def 2: 98.1% |
Def 1: 68.1% Def 2: 67% |
59.6 | Patient | 24 | 14 | 54 | 22 | 63.2% | 71.1% | Def 1: 41.2% Def 2: 36.8% |
Def 1: 30 Def 2: 31 |
Def 1: 4 Def 2: 3 |
Def 1: 43 Def 2: 39 |
Def 1: 4 Def 2: 3 |
Def 1: 88.2% Def 2: 91.2% |
Def 1: 53.8% Def 2: 48.8% |
||
Haffner (2011) [23] | 54.4 | Patient | 154 | 50 | 240 | 111 | 75.4% | 68.3% | NR | NR | NR | NR | NR | NR | NR | NR |
Panebianco (2010) [40] | 42.7 | Patient | NR | NR | NR | NR | 95.1% | 88.2% | NR | NR | NR | NR | NR | NR | NR | NR |
Roy (2010) [49] | 55.9 | Patient | NR | NR | NR | NR | 71% | 75% | NR | NR | NR | NR | NR | NR | NR | NR |
Testa (2010) [55] | 40.7 | Patient | NR | NR | NR | NR | 79.3% | 64% | NR | NR | NR | NR | NR | NR | NR | NR |
Sciarra (2010) [52] | 50 | Patient | 61 | 4 | 66 | 9 | 93.8% | 88% | NR | NR | NR | NR | NR | NR | NR | NR |
Kitajima (2010) [31] | 56.6 | Patient | 311 | 19 | 80 | 14 | 92.2% | 85.1% | NR | NR | NR | NR | NR | NR | NR | NR |
Labanaris (2010) [35] | 73.9 | Patient | 17 | 73 | 96 | 74 | 81.11% | 56.47% | NR | NR | NR | NR | NR | NR | NR | NR |
Kumar (2009) [32] | 21.7 | Patient | 39 | 3 | 10 | 8 | 92.8% | 55% | NR | NR | NR | NR | NR | NR | NR | NR |
Schmuecking (2009) [50] | NR | Lobe | NR | NR | NR | NR | 96% | 61% | NR | NR | NR | NR | NR | NR | NR | NR |
Cheikh (2009) [17] | 24.7 | Patient | 36 | 12 | 11 | 34 | 80% | 22.9% | NR | NR | NR | NR | NR | NR | NR | NR |
Cirillo (2008) [19] | 31.5 | Patient | 19 | 0 | 17 | 18 | 100% | 48.6% | NR | NR | NR | NR | NR | NR | NR | NR |
Kumar (2007) [33] | 13.3 | Patient | 39 | 0 | 11 | 33 | 100% | 25% | NR | NR | NR | NR | NR | NR | NR | NR |
Squillaci (2005) [53] | 50.8 | Patient | 29% | 8% | 25% | 3% | 89% | 80% | NR | NR | NR | NR | NR | NR | NR | NR |
Hara (2005) [24] | 41.5 | Patient | ≥2/3: 40 = 3/3: 47 |
≥2/3: 4 = 3/3: 8 |
≥2/3 30 = 3/3: 26 |
≥2/3: 8 = 3/3: 1 |
≥2/3: 90% = 3/3: 85% |
≥2/3: 78.9% = 3/3: 96.3% |
NR | NR | NR | NR | NR | NR | NR | NR |
Cancer prevalence tended to be higher and mpMRI NPV lower in the biopsy-naïve group as compared with the repeat biopsy group, in men with positive DRE as compared with men with negative DRE and when an endorectal coil was not used ( Table 3 ). There were no clear differences in the prevalence and NPV of the other analysed subgroups (TRUS-guided vs TTP biopsy, biopsy procedures with ≤16 cores vs >16 cores; Table 3 ). However, comparisons must be interpreted with care, due to the small number of studies in some subgroups. In patients with a PSA level of ≤10 ng/ml, the median NPV for overall PCa was 86.3% (IQR, 73.3–93.6%) for a median cancer prevalence of 35.4% (IQR, 27.6–42.5%).
Nb of studies | Median PCa prevalence | Median mpMRI NPV | Nb of studies | Median csPCa prevalence | Median mpMRI NPV | |
---|---|---|---|---|---|---|
Biopsy-naïve patients | 8 | 51.4% (45.5–56.7) | 69.9% (64.2–78) | 1 | 35.8% (NA) | 80.4% (NA) |
Repeat biopsy | 14 | 42% (35.1–52.6) | 82.6% (75.5–93.1) | 3 | 24.4% (19.1–32.8) | 88.2% (87.9–92.3) |
TRUS-guided biopsy | 36 | 49.7% (34.3–57.7) | 84.6% (68.6–92.8) | 4 | 28.1% (21.7–36.5) | 89.3% (82.9–92.4) |
TTP biopsy | 4 | 53.8% (47.5–57.8) | 73.6% (72–78.7) | 2 | 31.6% (30.5–32.8) | 92% (89.9–94) |
Biopsy with ≤16 cores | 28 | 48.7% (39.2–54.8) | 81.9% (66.8–89.3) | 5 | 28.1% (21.8–36.5) | 89.3% (82.9–92.4) |
Biopsy with >16 cores | 5 | 56.6% (51–61.3) | 81.1% (73.1–92.2) | 2 | 31.7% (30.5–32.8) | 92% (89.9–93.9) |
Positive DRE | 1 | 73.9% (NA) | 56% (NA) | 0 | – | – |
Negative DRE | 6 | 36% (34.6–46.8) | 82.7% (74.2–93.1) | 0 | – | – |
Endorectal coil | 17 | 41.7% (30.6–55.9) | 92.8% (79.3–95.4) | 1 | 31.7% (NA) | 91% (NA) |
No endorectal coil | 22 | 50.9% (41.7–56.1) | 77.7% (69.5–86.6) | 7 | 34% (26.9–46.1%) | 87.9% (78.2–92.1) |
Eight studies reported NPV at patient level for overall PCa and fulfilled the inclusion criteria for meta-analysis ( Table 4 ) [22 25 38 41 43 46 56 57] .
Study | Prevalence a (%) | Neg MRI (%) | NPV (%) | PPV (%) | Spe (%) | Se (%) | ||
---|---|---|---|---|---|---|---|---|
All PCa | Score ≥ 3/5 | Grenabo Bergdahl (2016) [22] | 31.3 | 66.9 | 83.7 | 47.5 | 63.2 | 73.1 |
Numao (2013) [38] | 45 | 29.4 | 70.6 | 64.3 | 71.0 | 63.9 | ||
Hauth (2015) [25] | 45.7 | 14.3 | 85.7 | 48.3 | 11.8 | 97.7 | ||
Vinet (2013) [57] | 49.3 | 24.6 | 64.7 | 53.8 | 31.4 | 82.4 | ||
Radtke (2015) [46] | 51 | 27 | 73 | 73.2 | 71.5 | 74.7 | ||
Thompson (2014) [56] | 61.3 | 31.4 | 68.6 | 76.8 | 60.3 | 82.6 | ||
Pokorny (2014) [43] | 63.7 | 30.9 | 69.1 | 82.4 | 69.1 | 82.4 | ||
Score ≥ 4/5 | Pepe (2015) [41] | 37 | 31 | 74.2 | 42 | 36.5 | 78.4% | |
Vinet (2013) [57] | 49.3 | 47.8 | 66.7 | 63.9 | 62.9 | 67.6% | ||
Radtke (2015) [46] | 51 | 73.5 | 63.9 | 92.3 | 95.8 | 48% | ||
Gleason ≥7 PCa | Score ≥ 3/5 | Radtke (2015) [46] | 29.3 | 27 | 87.9 | 45.1 | 59.6 | 80.2% |
a Prevalence of overall prostate cancers (10 first lines) or Gleason ≥7 cancers (last line).
PCa = prostate cancer; MRI = magnetic resonance imaging; Neg MRI = proportion of negative magnetic resonance imaging; NPV = negative predictive value; PPV = positive predictive value; Se = sensitivity; Spe = specificity.
Seven studies used a score of ≥3/5 for defining positive mpMRI ( Fig. 4 A and B) [22 25 38 43 46 56 57] . Fig. 4 C shows the conditional probability plot of 1 – NPV and PPV as a function of overall PCa prevalence. Table 5 shows NPV and PPV estimates for the given values of PCa prevalence.
PCaPrev | PPV | NPV |
---|---|---|
0.30 | 0.43 (0.34–0.53) | 0.88 (0.77–0.99) |
0.40 | 0.54 (0.45–0.64) | 0.82 (0.70–0.94) |
0.50 | 0.64 (0.55–0.73) | 0.76 (0.64–0.88) |
0.60 | 0.73 (0.65–0.80) | 0.67 (0.56–0.79) |
0.70 | 0.81 (0.75–0.87) | 0.57 (0.47–0.67) |
0.75 | 0.84 (0.79–0.89) | 0.51 (0.42–0.59) |
Only three studies used a score of ≥4/5 for defining positive mpMRI ( Table 4 ) [41 46 57] , and a formal meta-analysis could not be performed.
Only one study reporting NPV at patient level for Gleason ≥7 cancers met the selection criteria for inclusion in the meta-analysis. It reported NPV and PPV of 87.9% and 45.1%, respectively, for a prevalence of 29.3% ( Table 4 ) [46] .
We observed a large variability in reported NPV. Many factors, such as differences in mpMRI protocols, definition of negative mpMRI, or biopsy protocols, can explain this variability. However, two major causes of variability must be pointed out. First, the cancer prevalence was highly variable, ranging at patient level from 13% to 74.7% for overall PCa, and from 13.7% to 50.9% for csPCa. This variability was observed in both the biopsy-naïve and the repeat biopsy setting. As NPV depends on prevalence, this had a major impact on reported NPV ( Fig. 3 ). Second, the definition of csPCa was highly variable from one series to another, and differences of up to 21% could be observed in NPV when different definitions of csPCa were used in the same dataset [12 13 38 47 48] .
To account for clinical heterogeneity and to further explore the clinical relevance of the results, we carefully selected studies for inclusion in the meta-analysis based on stringent criteria. Particularly, we included only studies that: (1) had biopsy protocols with at least 10 cores, since it is no longer recommended to obtain less than 10 cores per biopsy; (2) used DWI, which is the most informative technique, at least for cancers in the peripheral zone [60] ; and (3) reported mpMRI findings using a five-level score, so that negative findings could be better defined. We accepted studies using a subjective (Likert) scale because experienced readers obtained equivalent [45 61 62] or better [63] results with the Likert score than with the PI-RADS v1 score. Owing to the large variations of NPV induced by differences in definitions of csPCa, we did not include different definitions in the meta-analysis since this would have introduced unacceptable clinical heterogeneity in the results, possibly resulting in erroneous and biased estimates. We, therefore, a priori restricted the definition of csPCa to cancers with a Gleason score of ≥7, given the low lethal potential of Gleason 6 cancers [64] and the lack of consensus among pathologists on the best method to measure biopsy core invasion length [65 66] .
In this more homogeneous group of studies, the prevalence range was still large (31.3–63.7%). As a result, we modelled the evolution of NPV (and PPV) as a function of overall PCa prevalence. Unfortunately, we could not duplicate this for csPCa since only one study reporting NPV for Gleason ≥7 cancers met the inclusion criteria for meta-analysis.
We included only studies that reported the results of systematic/standard biopsy in patients with negative mpMRI and used the systematic/standard biopsy as a reference standard. It is well known that TRUS-guided biopsy harbours both random and systematic errors, as evidenced by the high rates of positivity of immediate repeat biopsy after a first series of negative biopsies [67 68] , and as confirmed recently by the PROMIS trial [69] . Therefore, using TRUS-guided biopsy as a reference standard may have overestimated the NPV of mpMRI. However, studies using radical prostatectomy specimens as a reference standard have already reported mpMRI detection rates in relation to PCa Gleason score and volume [1] . In this review, we intended to address the more pragmatic question as to whether a negative mpMRI could predict a negative subsequent biopsy. This is an important question because if the NPV of mpMRI was sufficiently high in comparison with the reference standard of systematic/standard biopsies, then in practice a negative mpMRI result could indeed avoid the need for prostate biopsy. Therefore, studies reporting only biopsy results when the mpMRI was positive (eg, obtained through MRI-targeted, guided, or fusion biopsies with added systematic biopsies) were not included in this review.
It is now well established that mpMRI is a sensitive tool for detecting aggressive PCa 1 2 3 69] . However several reasons preclude its broad use as a triage test before biopsy.
Firstly, the population referred to prostate biopsy is not standardised. The large range of reported prevalence for overall PCa and csPCa suggests substantial heterogeneity in the way patients are selected for biopsy. Owing to this heterogeneity, we did not provide a pooled estimate for mpMRI NPV. The role of mpMRI as a triage test before prostate biopsy should be evaluated in the broader context of the selection of patients with a suspicion of (aggressive) PCa. In a recent retrospective study of 514 patients, mpMRI NPV for Gleason ≥7 cancers was 91% when the PSA density was ≤0.2 ng/ml/ml, and only 71% when the PSA density was >0.2 ng/ml/ml ( p = 0.003) [70] . In another series of 288 biopsy-naïve patients, no csPCa (Gleason score ≥7 or maximum cancer core length ≥4 mm) was found in 44 patients with a PSA density of <0.15 ng/ml/ml and a PI-RADS v2 score of <3/5 [71] . We believe that such prestratification of the risk of csPCa is an interesting way for rationalising the use of mpMRI before biopsy. Patients found at very low risk would be spared both mpMRI and biopsy. Patients at a low risk—for whom mpMRI would have an NPV high enough to be used as a triage test—could avoid biopsy in case of negative mpMRI. Patients at a higher risk would need biopsy even in case of negative mpMRI. Many tools can be used to risk stratify the population of patients referred to biopsy, ranging from simple parameters such as PSA density to more complicated risk calculators [72 73] . The impact of these tools on the NPV of prebiopsy mpMRI needs to be carefully evaluated, both in the biopsy-naïve and in the repeat biopsy setting. For the moment, it is impossible to make any recommendations on the best way to risk stratify patients before referring them for mpMRI.
Secondly, the large variability in the definition of csPCa precludes any definitive conclusion on the ability of mpMRI to rule out aggressive cancer. The issue of the most appropriate definition of csPCa on biopsy is complex, since biopsy results may accurately reflect neither tumour burden nor aggressiveness. Nonetheless, there is an urgent need to standardise the histological definition(s) of csPCa, to allow meaningful comparisons between studies.
Thirdly, the specificity of mpMRI remains moderate, and there is a substantial proportion of false positives in the lesions scored 3/5 or 4/5 [1 74 75] , even with the new PI-RADS v2 score [76] . In a series of 62 patients with 116 lesions biopsied under magnetic resonance/ultrasound fusion, the overall cancer detection rates for PI-RADS v2 scores of 3/5 and 4/5 were only 15.8% and 29.8%, respectively [77] . In theory, a triage test used to rule out a disease needs to be highly sensitive for this disease. However, if its specificity is too low, it will be clinically useless since most patients will be positive, whether they have the disease or not. Therefore, if mpMRI is to be used as a triage test in the future, there is a need to improve its specificity. This could be achieved by a continuous refinement of scores [78] . Promising results in characterising csPCa have also been reported with a quantitative analysis [79] .
Finally, all published studies were conducted in specialised centres. The broad use of mpMRI as a triage test assumes good interobserver reproducibility. Unfortunately, interobserver reproducibility of existing scoring systems remains moderate [62 63 80] even with the use of the PI-RADS v2 score [80 81] . Studies evaluating on a large scale the reproducibility of mpMRI findings between expert and nonexpert centres are currently lacking.
Three systematic reviews (including two meta-analyses) regarding the role of mpMRI in localised PCa have been published recently 4 5 6 . Crucially, all three reviews focused exclusively on the sensitivity of mpMRI-targeted, guided, or fusion biopsies in diagnosing overall PCa and csPCa, using TRUS-guided prostate biopsies as reference standards. The impact of systematic biopsies on the outcome was not addressed in any of the reviews, within either the index test or the reference standard. Our review had a totally different research question and objective, focusing on NPV of mpMRI to see if a negative mpMRI can avoid the need for a prostate biopsy. As MRI-targeted/guided/fusion biopsies are not relevant if the mpMRI was negative for cancer, it can be argued that the three reviews assessed a different index test altogether. As such, we believe that the findings of this review are novel and unique, and pave the way for further focused clinical studies.
The current study represents the first systematic review addressing the role of mpMRI as a triage test before biopsy. The review elements were developed in conjunction with a multidisciplinary panel of experts (EAU Prostate Cancer Guidelines Panel), which included a patient representative, and the review was performed robustly in accordance with recognised standards. However, it is limited by the major heterogeneity of the existing literature in patient population, study design, and definitions of positive mpMRI and csPCa. It highlighted further areas of research that could help in defining the best use of mpMRI in the early detection of aggressive PCa in the future.
Although mpMRI can detect aggressive PCa with excellent sensitivity, a definitive conclusion on its role as a triage test before prostate biopsy will be possible only when three main issues are addressed. Firstly, because NPV depends on prevalence, and because overall PCa and csPCa prevalence was highly variable in the published series, it becomes mandatory to define the optimal way to pre-evaluate the risk of csPCa in patients with a suspicion of PCa. Depending on the risk category, mpMRI could then be used to obviate biopsies or not. Secondly, there is a need for consensus definitions of csPCa on biopsy findings to allow interstudy comparisons. Thirdly, although efforts have been made to standardise mpMRI technical protocols and interpretation in the past few years [11 60 76] , there is still a crucial need to improve mpMRI specificity and inter-reader reproducibility.
This systematic review was performed under the auspices of:
The European Association of Urology Guidelines Office Board
The European Association of Urology Prostate Cancer Guideline Panel
Author contributions: Olivier Rouvière had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.
Study concept and design: Rouvière, Mottet, Cornford.
Acquisition of data: Rouvière, Moldovan, Van den Broeck, Yuan.
Analysis and interpretation of data: Rouvière, Moldovan, Van den Broeck, Lam.
Drafting of the manuscript: Rouvière, Moldovan, Van den Broeck, Lam.
Critical revision of the manuscript for important intellectual content: Bellmunt, van den Bergh, Bolla, Briers, Van den Broeck, Cornford, Cumberbatch, De Santis, Fossati, Gross, Henry, Joniau, Lam, Matveev, Moldovan, van der Poel, van der Kwast, Rouvière, Schoots, Wiegel, Mottet.
Statistical analysis: None.
Obtaining funding: None.
Administrative, technical, or material support: Yuan, Sylvester, Marconi.
Supervision: None.
Other: None.
Financial disclosures: Olivier Rouvière certifies that all conflicts of interest, including specific financial interests and relationships and affiliations relevant to the subject matter or materials discussed in the manuscript (eg, employment/affiliation, grants or funding, consultancies, honoraria, stock ownership or options, expert testimony, royalties, or patents filed, received, or pending), are the following: Bellmunt is a company consultant for Janssen, Astellas, Pierre Fabre, Genentech, Merck, Ipsen, Pfizer, Novartis, and Sanofi Aventis. He has received research support from Takeda, Novartis, and Sanofi, and received travel grants from Pfizer and Pierre Fabre. Bolla has received company speaker honoraria from Ipsen and Astellas, honoraria or consultation fees from Janssen, and fellowship and travel grants from Janssen, AstraZeneca, and Astellas. Briers has received grant and research support from Ipsen, European Association of Urology, and Bayer; is an ex officio board member for Europa UOMO; is an ethics committee and advisory group member for REQUITE; is a member patient advisory board member for PAGMI; and is a member of SCA and EMA PCWP. Cornford is a company consultant for Astellas, Ipsen, and Ferring. He receives company speaker honoraria from Astellas, Janssen, Ipsen, and Pfizer; participates in trials from Ferring; and receives fellowships and travel grants from Astellas and Janssen. De Santis is a company consultant for GlaxoSmithKline, Janssen, Bayer, Novartis, Pierre Fabre, Astellas, Amgen, Eisai Inc., ESSA, Merck, and Synthon; has received company speaker honoraria from Pfizer, Takeda, Sanofi Aventis, Shionogi, Celgene, and Teva OncoGenex; has participated in trials for Pierre Fabre, Astellas, Exelixis, Bayer, and Roche; has received fellowship and travel grants from Bayer, Novartis, Ferring, Astellas, Sanofi Aventis, and Janssen; has received grant and research support from Pierre Fabre; has received honoraria from AstraZeneca; and is associated with Amgen. Joniau is a company consultant for Astellas, Ipsen, Bayer, Sanofi, and Janssen; has received company speaker honoraria from Astellas, Amgen, Bayer, Sanofi, Janssen, and Ipsen; has participated in trials for Astellas, Janssen, and Bayer; has received fellowship and travel grants from Astellas, Amgen, Bayer, Sanofi, Janssen, Ipsen, and Pfizer; and has received grant and research support from Astellas, Bayer, and Janssen. Matveev has received company speaker honoraria from Sanofi and Astellas, has participated in trials for Astellas, Pfizer and Novartis. Lam is a company consultant for and has received company speaker honoraria from Pfizer, GSK, Astellas, and Ipsen. van der Poel is a company consultant for Intuitive Surgical, has participated in trials for Astellas and Steba Biotech, and has received grant and research support from Astellas. Rouvière is a company consultant for EDAP-TMS, Bracco, and Philips; has received company speaker honoraria from EDAP-TMS, Bracco, and Philips; and has participated in trials for EDAP-TMS and Bracco. Wiegel has received company speaker honoraria from Astellas, Takeda, Hexal, Ipsen, Janssen-Cilac, and Ferring. Mottet has received grant and research support from Takeda Pharmaceutical, Millenium, Astellas, Pierre Fabre, Sanofi, and Pasteur, and has received honoraria or consultation fees from Takeda Pharaceutical, Millenium, Jansen, Astellas, BMS, Bayer, Ipsen, Ferring, Novartis, Nuclétron, Pierre Fabre, Sanofi, and Zeneca. van den Bergh, Van den Broeck, Cumberbatch, Fossati, Gross, Henry, van der Kwast, Sylvester, Yuan, Schoots, Moldovan, and Marconi have nothing to disclose.
Funding/Support and role of the sponsor: None.
A correlation with radical prostatectomy specimens has demonstrated that multiparametric magnetic resonance imaging (mpMRI) has excellent sensitivity in detecting prostate cancer (PCa) with a Gleason score of ≥7 1 2 3 . As a result, prostate mpMRI is increasingly used in patients with a suspicion of PCa to localise abnormal areas before biopsy. A large body of literature has shown that targeted biopsies of suspicious lesions seen on mpMRI (TBx) improved the detection of clinically significant PCa (csPCa), at least in the repeat biopsy setting 4 5 6 . As a result, it is now recommended that an mpMRI is performed before repeat biopsy to allow TBx of suspicious lesions in addition to standard biopsies [7] .
Some authors have recently suggested that, besides improving csPCa detection, mpMRI could also be used as a triage test so that patients with negative mpMRI findings could obviate biopsy. Such a strategy remains highly controversial [8] and depends upon the negative predictive value (NPV) of mpMRI. Therefore, the European Association of Urology Prostate Cancer Guidelines Panel undertook this systematic review and meta-analysis to assess the NPV of mpMRI in patients with a suspicion of PCa and, thus, its potential role in eliminating unnecessary prostate biopsy.
Our primary aim was to systematically evaluate the performance of negative prebiopsy prostate mpMRI in predicting a negative biopsy result for overall PCa and csPCa in biopsy-naïve men and in men with previously negative biopsies. A further objective was to explore and define factors that may contribute to relevant thresholds in order to provide guidance for future studies.
The review was performed according to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) statement [9] . The review protocol was published in PROSPERO database ( http://www.crd.york.ac.uk/PROSPERO; registration number CRD42015021929). Databases searched included the Embase and OVID Medline databases, the Cochrane database of systematic reviews, and the Cochrane Central Register for Clinical Trials, covering from January 1, 2000 to February 13, 2016. Systematic or standard prostate biopsies were used as reference standards, with positive or negative cases of PCa being determined by histopathological examination. The detailed search strategy is presented in Supplement 1.
Included studies focused on men who were assessed for suspected PCa by mpMRI before undergoing prostate biopsy. Studies enrolling both biopsy-naïve men and men who had undergone previous negative biopsies were included. Prebiopsy prostate mpMRI was considered the index test and comprised T2-weighted imaging (T2WI) and at least one functional imaging technique (diffusion-weighted imaging [DWI], dynamic contrast-enhanced imaging [DCEI], or magnetic resonance spectroscopic imaging [MRSI]). For inclusion, studies had to report on false negatives and true negatives, in order to calculate NPV (ie, results of systematic/standard prostate biopsies when the mpMRI was negative). When available, false positive and true positive findings were also noted to calculate the positive predictive value (PPV) and the cancer prevalence. There was restriction neither on the biopsy technique (transrectal or transperineal) nor on the number of biopsy cores. Studies using radical prostatectomy specimens as reference standards were excluded, as were studies evaluating men with histologically proven PCa. Studies with less than 50 participants were excluded. No language restrictions were applied.
Two reviewers (P.C.M. and T.V.D.B.) independently screened all abstracts and full-text articles for eligibility. Disagreement was resolved by consensus or reference to an independent third party (L.M.). All screening was performed using a predefined eligibility form.
Using a data extraction form developed a priori, the same two reviewers independently extracted data concerning study methodology, patient characteristics, technical characteristics of the MR scanners, mpMRI protocol, mpMRI scoring system, definition of positive mpMRI, biopsy protocol, and definition of csPCa. Any discrepancies concerning data extraction were resolved by consensus or reference to an independent arbiter (O.R. or T.B.L.).
To assess the risk of bias (RoB), all included reports were reviewed using the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool for diagnostic accuracy studies [10] .
Outcome data regarding false negative and true negative values of mpMRI before prostate biopsy were recorded as reported by authors. When not available, data were indirectly derived from specificity, sensitivity, and prevalence values reported by authors using an online Bayesian statistics calculator ( http://www.medcalc.com/bayes.html ). Descriptive statistics were used to summarise baseline characteristics and outcomes, including median and interquartile range (IQR) for estimates of NPV across studies. A correlation between mpMRI NPV and a positive biopsy rate was established using the Pearson's correlation coefficient.
A meta-analysis was undertaken to calculate pooled NPV and PPV. To ensure appropriate clinical homogeneity of the studies included in the meta-analysis, we selected only the studies enrolling biopsy-naïve patients and/or patients with a history of negative biopsy, and fulfilling the following criteria that were defined a priori: (1) reference standard consisting of prostate biopsy with at least 10 samples on all patients; (2) mpMRI protocol comprising at least T2WI and DWI; (3) mpMRI results presented as a five-level score, using a subjective Likert scale or the Prostate Imaging Reporting Data System (PI-RADS) score [11] ; (4) definition of positive mpMRI as a score ≥3/5 or ≥4/5; and (5) results reported on a per patient basis. In addition, only studies defining csPCa as Gleason ≥7 cancers were selected for the meta-analysis assessing the mpMRI NPV for csPCa. A bivariate random-effects approach was employed using the Midas package in Stata 12 (StataCorp LP, College Station, TX, USA). Since the NPV decreases and the PPV increases as the prevalence increases, post-test probability estimates of NPV and PPV were reported for the given values of the prevalence based on Bayes’ theorem.
For other studies not included in the meta-analysis based on the criteria described above, a narrative synthesis of the data was performed. To explore and define clinical heterogeneity, subgroups were analysed at patient level based on the following variables: biopsy-naïve versus previous negative biopsy; patients with positive versus negative digital rectal examination (DRE); mpMRI performed with an endorectal versus without an endorectal coil; transrectal ultrasound (TRUS) versus template transperineal (TTP) biopsy approach; and ≤16 cores versus >16 cores as the reference standard. Studies reporting mpMRI NPV for patients with a prostate-specific antigen (PSA) level of ≤10 ng/ml were also reported separately.
The study selection process is depicted in the PRISMA flow diagram ( Fig. 1 ). A total of 2980 abstracts were retrieved. After abstract screening and removal of duplicates, 240 articles were eligible for full text screening, of which 48 studies were eligible for inclusion 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 .
Out of the 48 included studies, 42 were single-centre and six were multicentre studies. Thirty-four studies were prospective and six were retrospective, whilst the design of the rest was unclear. RoB assessment using QUADAS-2 was performed for each of the individual studies ( Fig. 2 A and B). Overall, the RoB was highly heterogeneous across studies for all criteria, except for the reference standard domain, in which RoB was low in most studies.
The 48 studies comprised a total of 9613 men who underwent prostate mpMRI followed by biopsy. The study and patient baseline characteristics are presented in Table 1 . The patient population consisted of biopsy-naive men in nine studies, men with at least one previous negative biopsy in 16 studies, and both biopsy-naïve men and men with a history of previous negative biopsy in nine studies. In 14 studies, the biopsy history of the patients was unclear.
Study | Study design | Period | Population | Pt Nb | Mean/median* age (yr) | Mean/median* PSA (ng/ml) | Mean/median* prostate volume (cm 3 ) | Magnetic field strength | MR pulse sequences | Endorectal coil | MR score | Definition of positive MRI | Reference standard |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Hauth (2015) [25] | Prospective | 2011–2013 | FB | 94 | 64 (43–83) | 9 (3–31) | 51 (17–140) | 1.5 T | T2WI/DWI/DCEI/MRSI | No | PI-RADS v1 | ≥3 | 11–13-core TRUS SBx + TBx |
Lamb (2015) [36] | Retrospective | 2013–2013 | FB & PNB | 173 | NR | NR | NR | 1.5 T | T2WI/DWI | NR | NR | NR | 12-core TRUS SBx |
Brock (2015) [15] | Prospective | 2013–2014 | PNB | 168 | 64* (IQR 59–70) | 9.2* (IQR 6.7–13.4) | 55.4* (IQR 42–80) | 3 T | T2WI/DWI/DCEI | No | PI-RADS v1 | NR | 12/24-core TRUS SBx + TBx |
Grenabo Bergdahl (2016) [22] | Prospective | 2013–2014 | FB & PNB | 83 | 69.3* (IQR 69–69.6) | 1.6* (IQR 0.9–2.7) | NR | 3 T | T2WI/DWI/DCEI/MRSI | No | PI-RADS v1 | ≥3 | 10-core TRUS SBx + TBx |
Wang (2015) [58] | Prospective | 2002–2009 | FB & PNB | 586 | 70 (26–91) | 11.11* (0.02–9794) | NR | 1.5 T | T2WI/DWI/DCEI/MRSI | Yes | PI-RADS v1 | ≥3 | TRUS SBx |
Pepe (2015) [41] | Prospective | 2011–2014 | PNB | 100 | 64* | 8.6* (4.2–10) | NR | 3 T | T2WI/DWI/DCEI/MRSI | No | PI-RADS v1 | ≥4 | TPBx + TBx |
Panebianco (2015) [39] | Prospective | 2011–2014 | FB (61.62%) & PNB (38.34%) | 925 (1140 total cohort) |
NR | NR | NR | 3 T | T2WI/DWI/DCEI | Yes | PI-RADS v1 | NR | 14-core TRUS SBx; 45-core sat TPBx + TBx |
Radtke (2015) [46] | Prospective | 2013–2013 | FB (63.3%) & PNB (36.7%) | 294 | 64* (60–71) | 7.3 (6.0) | 47 (37.5) | 3 T | T2WI/DWI/DCEI | No | PI-RADS v1 | PI-RADS ≥2; PI-RADS ≥3; PI-RADS ≥4; PI-RADS = 5; |
24-core TPBx + TBx |
Itatani (2014) [27] | Retrospective | 2004–2007 | NR | 193 | 68.9 (8.4); 70* (47–89) | 11.8 (15.9); 7.9* (1.22–159) | NR | 1.5 T | T2WI/DWI/DCEI | No | 1–5 scale (Likert) | ≥3 | 12–14-core TRUS SBx |
Porpiglia (2014) [44] | Prospective | 2011–2013 | PNB | 170 | 65* (60–70) | 6.9* (5.2–9.8) | 42* (36–48) | 1.5 T | T2WI/DWI/DCEI | Yes | Dichotomous | Positive: at least 2/3 MR seq. with suspicious findings | 18–24-core TRUS SBx (volume dependent) |
Thompson (2014) [56] | Prospective | 2012–2013 | FB (88%) & PNB (12%) | 150 | 62.4* (IQR 55.0–66.4) | 5.6* (IQR 4.5–7.5) | 40* (IQR 30–57) | 1.5 T (47%) & 3 T (53%) | T2WI/DWI/DCEI | No | PI-RADS v1 | ≥3 | Median of 30 TPBx (volume dependent) |
Pokorny (2014) [43] | Prospective | 2012–2013 | FB | 223 | 63* (IQR 57–68) | 5.3* (IQR 4.1–6.6) | 41* (IQR 30–59) | 3 T | T2WI/DWI/DCEI | No | PI-RADS v1 | ≥3 (primary); ≥4 |
12-core TRUS SBx + TBx |
Petrillo (2014) [42] | Prospective | 2009–2010 | NR | 136 | NR | NR | NR | 1.5 T | T2WI/DWI/MRSI | Yes | 1–5 scale (Likert) | ≥3 | 12–16-core TRUS SBx (volume + PSA dependent) |
Javali (2014) [29] | Retrospective | 2002–2011 | NR | 140 | Control: 62.4 (10.5); Study: 62.9 (12.1) | Control: 6.8 (2.3); Study: 6.87 (2.6) | Control: 44 (14.2); Study: 43 (18.4) | 1.5 T | T2WI/MRSI | Yes | Dichotomous | Cit/[Cho + Cr] < 1.2 | 6-core TRUS SBx ( n = 69), 12-core TRUS SBx ( n = 119) |
Abd-Alazeez (2014) [13] | Prospective | 2007–2011 | FB | 129 | 62* (41–82) | 5.8* (1.2–20) | 40* (16–137) | 1.5 & 3 T | T2WI/DWI/DCEI | No | PI-RADS v1 | ≥3 (primary); ≥4 |
20-core TPBx |
Abd-Alazeez (2014) [12] | Retrospective | NR | PNB | 54 | 64* (39–75) | 10* (2–23) | 53* (19–136) | 1.5 & 3 T | T2WI/DWI/DCEI | No | PI-RADS v1 | ≥3 (primary); ≥4 |
≥20-core TPBx + TBx ( n = 15) |
Matsuoka (2014) [37] | Prospective | 2007–2012 | NR | 135 | 67* (50–80) | 7.0* (2.9–19.8) | 25.4* (12.7–90.2) | 1.5 T | T2WI/DWI | No | 1–5 scale (Likert) | ≥3 | 14-core TRUS SBX |
Junker (2013) [30] | Retrospective | 2011–2013 | PNB | 73 | 62 (7.4) | 7.0* (5.1–12.9) | 45* (34–61) | 3 T | T2WI/DWI/DCEI | No | PI-RADS | PI-RADS ≥10 and ≥11 for all PCa PI-RADS ≥13 for significant PCa |
10-core TRUS SBx + TBx |
Busetto (2013) [16] | Prospective | 2010–2012 | PNB | 163 | 66.4 (5.3) | 6.8 (1.6) | NR | 3 T | T2WI/DWI/DCEI/MRSI | Yes | NR | NR | 10-core TRUS SBx + TBx |
Rais-Bahrami (2013) [47] | Prospective | 2007–2012 | NR | 583 | 61.3 (8.4) | 9.9 (13.1) | NR | 3 T | T2WI/DWI/DCEI/MRSI | Yes | 1–4 scale (Likert) | ≥2 ≥3 |
12-core TRUS SBx + TBx |
Kuru (2013) [34] | Prospective | 2010–2011 | FB (51%) & PNB (49%) | 347 | 65.3 (42–82) | 9.85 (0.5–104) | 48.7 (9–180) | 3 T | T2WI/DWI/DCEI | No | 1–3 scale (Likert) | ≥2 | 12–36-core TRUS SBx (volume dependent) + TBx |
Ferda (2013) [20] | Prospective | NR | NR | 164 | (49–74) | (4.2–123) | NR | 3 T | T2WI/DWI/DCEI/MRSI | No | NR | In house | TRUS SBx |
Ganie (2013) [21] | NR | 2007–2009 | PNB | 87 | NR | NR | NR | 1.5 T | T2WI/MRSI | Yes | MRSI Cho/Cit ratio | In house | 6 core TRUS SBx + MRI TBx |
Vinet (2013) [57] | Prospective | 2009–2011 | FB | 69 | NR | 5.2* (3.2–28) | NR | 1.5 T (35 pts) & 3 T (34 pts) | T2WI/DWI/DCEI | No | 1–5 scale (Likert) | ≥3 | 12-core TRUS SBx + TBx |
Numao (2013) [38] | Prospective | 2006–2010 | FB | 351 | 65* (59–70) | 6.3* (4.9–9.1) | 32* (24–42) | 1.5 T | T2WI/DWI/DCEI (no DCEI in 42 pts) | No | 1–5 scale (Likert) | ≥3 | 3D 26-core (12 TRUS SBx + 14 TPBx – 203 pts); 3D 14-core (6 TRUS SBx + 8 TPBx – 102 pts); TPBx 14 core (46 pts) |
Belas (2012) [14] | Prospective | 2010–2011 | FB | 71 | 66* (47–76) | 7* (4–10) | 45* (15–150) | 1.5 T | T2WI/DWI/DCEI | No | TZ: 0–4 scale PZ: 0–10 scale |
TZ: >2 PZ: >6 |
12-core TRUS SBx + TBx |
Ibrahiem (2012) [26] | Prospective | 2008–2009 | FB | 100 | 65.03 (7.13) | 26.3 (24.2) | 60.09 (28.7) | 1.5 T | T2WI/DWI | No | NR | In house | 12-core TRUS SBX |
Sciarra (2012) [51] | Prospective | 2008–2011 | PNB | 84 | 64.09 (46–76) | 7.07 (4.2–15.5) | NR | 3 T | T2WI/DWI/DCEI/MRSI | Yes | NR | NR | 10-core TRUS Bx + TBx |
Portalez (2012) [45] | Prospective | 2011 | PNB | 129 | 64.7 (47–79) | 9.6 (2.7–40) | 51.1 (12–192) | 1.5 T | T2WI/DWI/DCEI | Mixed | 1–5 scale (Likert) PI-RADS |
Likert ≥3 PI-RADS ≥9 |
10–12-core TRUS SBx + TBx |
Watanabe (2012) [59] | Prospective | 2004–2008 | NR | 1448 | 72 (7.5) | NR | NR | 1.5 T | T2WI/DWI | No | NR | ADC value ≤1.35 × 10 −3 mm 2 /s | 8-core TRUS SBx + TBx |
Tamada (2011) [54] | Retrospective | 2006–2009 | NR | 50 | 70 (40–84) | 6.84* (4.06–9.94) | NR | 1.5 T | T2WI/DWI/DCEI | No | NR | In house | 12-core TRUS SBx |
Choi (2011) [18] | NR | 2009–2010 | NR | 51 | 67.16 (56–90) | 14.16 (1.02–38.9) | 42.98 (13.8–77.3) | 3 T | T2WI/DWI | NR | NR | NR | 10–12-core TRUS SBx + TBx |
Iwazawa (2011) [28] | Retrospective | 2008–2009 | NR | 178 | 68.8 (41–86) | 20.51 (4.04–568.5) | NR | 1.5 T | T2WI/DWI/DCEI | NR | 1–4 scale (Likert) | NR | 10–12-core TRUS SBx (TBx included in SBx chart) |
Rouse (2011) [48] | Prospective | 2005–2007 | PNB | 114 | 63.6 (41–83) | 13.4 (0–228) | NR | 1.5 T | T2WI/DWI/DCEI | NR | 1–5 scale (Likert) | ≥3 | TRUS SBx |
Haffner (2011) [23] | Prospective | 2005–2009 | FB | 555 | 64* (47–83) | 6.75* (0.18–100) | 46* (15–200) | 1.5 T | T2WI/DCEI | No | 1–5 scale (Likert) | ≥3 | 10-core TRUS SBx + TBx |
Panebianco (2010) [40] | Prospective | 2007–2009 | PNB | 150 | 61.2 (46–78) | 9.42 (3.91) | 41.17 (7.47) | 1.5 T | T2WI/DCEI/MRSI | Yes | NR | In house | 10-core TRUS SBx (TBx included in SBx chart) |
Roy (2010) [49] | Not specified | 2011–2009 | FB (53%) & PNB (47%) | 103 | 63 (52–78) | 7* | NR | 3 T | T2WI/DWI/DCEI | Yes | NR | NR | 8-core TRUS SBx + TBx |
Testa (2010) [55] | Not specified | 2007 | PNB | 54 | 63.9 (52–76) | 11.4 (3–42) | 59.3 (30–150) | 1.5 T | T2WI/MRSI | Yes | 1–3 scale (Likert) | ≥2 | 12-core TRUS SBx + TBx |
Sciarra (2010) [52] | Prospective | 2007–2009 | PNB | 110 | 63.5 (49–74) | NR | NR | 1.5 T | T2WI/DCEI/MRSI | Yes | NR | In house | 10-core TRUS SBx + TBx |
Kitajima (2010) [31] | Prospective | 2008–2009 | NR | 53 | 69* (56–84) | 11.1* (4.2–112.1) | NR | 3 T | T2WI/DWI/DCEI | No | 1–5 scale (Likert) | ≥3 | 20-core TPBx |
Labanaris (2010) [35] | Prospective | 2004–2008 | PNB | 260 | NR | NR | NR | 1 T | T2WI/DWI/DCEI | Yes | Dichotomous | In house | 18-core TRUS SBx |
Kumar (2009) [32] | NR | NR | NR | 61 | 65.3 (9.3) | 16.5 (0.21–155) | NR | 1.5 T | T2WI/MRSI | Yes | NR | (Cit/(Cho + Cr) ≤ 1.2 | TRUS Bx |
Schmuecking (2009) [50] | NR | NR | FB & PNB | 67 | 68 | 11.5 | NR | 1.5 T | T2WI/DCEI | No | NR | NR | 20-core Bx |
Cheikh (2009) [17] | Retrospective | 2005–2008 | PNB | 93 | 63.2 (52–74) | 9.63 (1.6–40) | NR | 1.5 T | T2WI/DCEI | No | Dichotomous | In house | 12-core TRUS SBx + TBx |
Cirillo (2008) [19] | Prospective | 2004–2006 | PNB | 54 | 65.5 (5.2) | 10.8 (7.5) | NR | 1.5 T | T2WI/MRSI | Yes | Dichotomous | In house | 10-core TRUS SBx + TBx |
Kumar (2007) [33] | Prospective | 2003–2005 | NR | 83 | NR | NR | NR | 1.5 T | T2WI/MRSI | Yes | NR | NR | 12-core TRUS SBx + TBx |
Squillaci (2005) [53] | Prospective | 2004–2005 | NR | 65 | NR | NR | NR | 1.5 T | T2WI/DCEI/MRSI | No | 1–3 scale (Likert) | ≥2 | 10-core TRUS SBx + TBx |
Hara (2005) [24] | Prospective | 2003–2004 | FB | 90 | 67.2 (NR) | NR | NR | 1.5 T | T2WI/DCEI | No | 1–3 scale (Likert) | ≥2 = 3 |
14-core TRUS SBx |
The magnetic field strength was 1, 1.5, and 3 T in one, 28, and 15 studies, respectively. Four studies used both 1.5 and 3 T MR systems. DWI and DCEI were used in 36 and 35 studies, respectively. Nineteen studies also added MRSI. An endorectal coil was used in 18 studies. The definition of positive mpMRI varied across studies. The PI-RADS v1 score was used in 12 studies, a five-level subjective (Likert) score was used in eight studies, and one study reported data based on the two scoring systems. In-house criteria were used in 13 studies for defining positive mpMRI, and five studies used a dichotomous definition. Nine studies did not report on the criteria for positive mpMRI. No study used the PI-RADS v2 score.
Regarding the reference standard, TRUS-guided biopsies were used in 39 studies, TTP biopsies in six studies, and mixed TRUS-guided and TTP biopsies in two studies. In one study, the biopsy approach was unclear. The number of cores per biopsy procedure was ≤16 in 30 studies, >16 in nine studies, and variable among patients in three studies. For six studies, the number of biopsy cores taken was unclear.
At patient level, the median biopsy positivity rate (ie, cancer prevalence) was 50.4% (IQR, 36.4–57.7%) for overall cancer and 32.9% (IQR, 28.1–37.2%) for csPCa ( Table 2 ). The median mpMRI NPV was 82.4% (IQR, 69.0–92.4%) for overall cancer and 88.1% (IQR, 85.7–92.3) for csPCa. NPV significantly decreased when cancer prevalence increased, both for overall cancer ( r = –0.64, p < 0.0001) and csPCa ( r = –0.75, p = 0.032; Fig. 3 ). In addition, NPV was highly dependent on the definition used for csPCa, with differences of up to 21% when several definitions were used in the same dataset [12 13 38 47 48] .
Study | Overall PCa prevalence (%) | Reporting level | Multiparametric MRI performance for PCa detection | Definition of csPCa | csPCa prevalence | Multiparametric MRI performance for csPCa detection | ||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
TN | FN | TP | FP | NPV | PPV | TN | FN | TP | FP | NPV | PPV | |||||
Hauth (2015) [25] | 45.7 | Patient | 6 | 1 | 42 | 45 | 85.7% | 48.3% | Low grade: GS ≤ 6 High grade: GS ≥ 7 |
NR | NR | NR | NR | NR | NR | NR |
Lesion | 59 | 13 | 55 | 73 | 81.9% | 43% | ||||||||||
Lamb (2015) [36] | 65.9 | Patient | 23 | 22 | 92 | 36 | 51.1% | 71.9% | GS ≥ 7 | 50.9% | 31 | 14 | 71 | 57 | 68.9% | 55.5% |
Brock (2015) [15] | 42.3 | Patient | 17 | 7 | 56 | 88 | 70.8% | SBx: 38.8% TBx: 22.2% Duo: 44.4% |
Epstein: GS > 6 and/or max CCL ≥50% | 24.4% | SBx: 21 | SBx: 3 | SBx: 38 TBx: 27 duo: 47 |
SBx: 106 TBx: 117 duo: 97 |
87.5% | SBx: 26.4% TBx: 18.8% duo: 32.6% |
Grenabo Bergdahl (2016) [22] | 33.7 | Patient | 36 | 7 | 19 | 21 | 83.7% | 47.5% | Clinically insignificant PCa: T1c, PSAd < 0.15, GS < 7, ≤2 positive cores, and unilateral cancer | NR | NR | NR | NR | NR | NR | NR |
Wang (2015) [58] | 58 | Patient | 165 | 8 | 332 | 81 | 95.4% | 80.4% | NR | NR | NR | NR | NR | NR | NR | NR |
Pepe (2015) [41] | 37 | Patient | 23 | 8 | 29 | 40 | 74.2% | 42% | GS ≥ 7 or GS 6 with CCL ≥ 50% | NR | NR | NR | NR | NR | 100% | 55.8% |
Panebianco (2015) [39] | 74.7 | Patient | Group A (satBx): 104 | Group A (satBx): 43 | Group A: 186 | Group A: 22 | Group A (satBx): 70.7% | Group A: 89.4% | NR | 60% | Group A: 147 | Group A: 0 | Group A: 183 | Group A: 25 | Group A: 100% | Group A: 88% |
Group B (TRUSGB NR TRUS G satBx): 93 | Group B (TRUSGB NR TRUS G satBx): 37 | Group B: 417 before and 425 after satBx | Group B: 23/440 and 15/440 after satBx. | Group B (TRUSGB–TRUS G satBx): 71.5% | Group B: 94.8% before and 96.6% after satBx | 71.9% | Group B: 130 | Group B: 0 | Group B: 410 |
Group B: 30 | Group B: 100% | Group B: 93.2% | ||||
Radtke (2015) [46] | 51 | Patient | ≥2/5: 80 ≥3: 103 ≥4: 138 = 5: 142 |
≥2/5: 18 ≥3/5: 38 ≥4/5: 78 = 5/5: 126 |
≥2/5: 132 ≥3/5: 112 ≥4/5: 72 = 5/5: 24 |
≥2/5: 64 ≥3/5: 41 ≥4/5: 6 = 5/5: 2 |
≥2/5: 81.6% ≥ 3/5: 73.1% ≥ 4/5: 63.9% = 5/5: 53% |
≥2/5: 67.4% ≥ 3/5: 73.2% ≥ 4/5: 92.3% = 5/5: 92.3% |
GS ≥ 7 | 29.3% | ≥2/5: 91 ≥3/5: 124 ≥4/5: 183 = 5/5: 203 |
≥2/5: 7 ≥3/5: 17 ≥4/5: 33 = 5/5: 65 |
≥2/5: 79 ≥3/5: 69 ≥4/5: 53 = 5/5: 21 |
≥2/5: 117 ≥3/5: 84 ≥4/5: 25 = 5/5: 5 |
≥2/5: 92.2% ≥3/5: 87.9% ≥4/5: 84.7% = 5/5: 75.8% |
≥2/5: 40.3% ≥3/5: 45.1% ≥4/5: 68% = 5/5: 80.7% |
Itatani (2014) [27] | 13 | Patient | 168 | 25 | NR | NR | 87% | NR | (1) PSAd ≥ 0.1 or GP 4/5 or ≥ 3/6 pos cores; max CCL < 50% (2) PSAd ≥ 0.15 or GP 4/5 or max core length invasion < 3 mm (min 6 cores) |
NR | NR | NR | NR | NR | NR | NR |
Porpiglia (2014) [44] | 30.6 | Patient | 107 | 5 | 47 | 11 | 95.5% | 81% | NR | NR | NR | NR | NR | NR | NR | NR |
Thompson (2014) [56] | 61.3 | Patient | 35 | 16 | 76 | 23 | 68.6% | 76.7% | Moderate or high risk Moderate risk: GS 7 (GP4 >5%) and <50% of positive cores or GS 6–7 (GP4 ≤ 5%) and either ≥30% of positive cores or max core length invasion ≥8 mm High risk: GS ≥ 7 (GP4 > 5%); ≥50% + cores or GS ≥ 8 |
34% | 49 | 2 | 49 | 50 | 96% | 49.5% |
Pokorny (2014) [43] | 63.7 | Patient | ≥3/5: 56 ≥4/5: 74 |
≥3/5: 25 ≥4/5: 40 |
≥3/5: 101 ≥4/5: 86 |
≥3/5: 41 ≥4/5: 23 |
≥3/5: 69.1% ≥4/5: 64.9% |
≥3/5: 71.1% ≥4/5: 78.9% |
NR | NR | NR | NR | NR | NR | NR | NR |
Petrillo (2014) [42] | 18.4 | Patient | 56 | 4 | 21 | 55 | 93% | 28% | NR | NR | NR | NR | NR | NR | NR | NR |
Javali (2014) [29] | 16.4 | Patient | 49 | 1 | 22 | 68 | 98% | 24.4% | NR | NR | NR | NR | NR | NR | NR | NR |
Abd-Alazeez (2014) [13] | 54.7 | Lobe | ≥3/5: 33 | ≥3/5: 14 | ≥3/5: 127 | ≥3/5: 84 | ≥3/5: 70% | ≥3/5: 60% | Def 1: GS ≥ 4 + 3 and/or max CCL ≥ 6 mm Def 2: GS ≥ 3 + 4 and/or max CCL ≥ 4 mm Def 3: GS ≥ 4 + 3 Def 4: GS ≥ 3 + 4 Def 5: max CCL ≥ 6 mm Def 6: max CCL ≥ 4 mm |
Def 1: NR Def 2: 44.2% Def 3: 23.2% Def 4: 36% Def 5: 32.9% Def 6: 39.5% |
Def 1: 46 Def 2: 42 Def 3: 47 Def 4: 43 Def 5: 46 Def 6: 43 |
Def 1: 1 Def 2: 5 Def 3: 0 Def 4: 4 Def 5: 1 Def 6: 4 |
Def 1: 45 Def 2: 72 Def 3: 13 Def 4: 50 Def 5: 39 Def 6: 59 |
Def 1: 166 Def2: 139 Def 3: 198 Def 4: 161 Def 5: 172 Def 6: 152 |
Def 1: 98 Def 2: 89 Def 3: 100 Def 4: 92 Def 5: 98 Def 6: 91 |
Def 1: 21 Def 2: 34 Deg 3: 6 Def 4: 24 Def 5: 19 Def 6: 28 |
≥4/5: 87 | ≥3/5: 62 | ≥3/5: 79 | ≥3/5: 30 | ≥3/5: 58% | ≥3/5: 73% | Def 1: 140 Def 2: 124 Def 3: 148 Def 4: 133 Def 5: 141 Def 6: 131 |
Def 1: 9 Def 2: 25 Def 3: 1 Def 4: 16 Def 5: 8 Def 6: 18 |
Def 1: 37 Def 2: 52 Def 3: 12 Def 4: 38 Def 5: 32 Def 6: 45 |
Def 1: 72 Def 2: 57 Def 3: 97 Def 4: 71 Def 5: 77 Def 6: 64 |
Def 1: 94 Def 2: 83 Def 3: 99 Def 4: 89 Def 5: 95 Def 6: 88 |
Def 1: 34 Def 2: 48 Def 3: 11 Def 4: 35 Def 5: 30 Def 6: 42 |
|||||
Abd-Alazeez (2014) [12] | 47.2 | Lobe | ≥3/5: 26 | ≥3/5: 13 | ≥3/5: 38 | ≥3/5: 31 | ≥3/5: 66% | ≥3/5: 55% | Def 1: GS ≥ 4 + 3 and/or max CCL ≥ 6 mm Def 2: GS ≥ 3 + 4 and/or max CCL ≥ 4 mm Def 3: GS ≥ 4 + 3 Def 4: GS ≥ 3 + 4 Def 5: max CCL ≥ 6 mm Def 6: max CCL ≥ 4 mm |
Def 1: 18.5% Def 2: 31.5% Def 3: 4.6% Def 4: 21.3% Def 5: 16.7% Def 6: 25% |
Def 1: 37 Def 2: 31 Def 3: 39 Def 4: 36 Def 5: 37 Def 6: 32 |
Def 1: 2 Def 2: 8 Def 3: 0 Def 4: 3 Def 5: 2 Def 6: 7 |
Def 1: 18 Def 2: 26 Def 3: 5 Def 4: 20 Def 5: 16 Def 6: 20 |
Def 1: 51 Def 2: 43 Def 3: 64 Def 4: 49 Def 5: 53 Def 6: 49 |
Def 1: 95 Def 2: 79 Def 3: 100 Def 4: 92 Def 5: 95 Def 6: 82 |
Def 1: 26 Def 2: 38 Def 3: 7 Def 4: 29 Def 5: 23 Def 6: 29 |
≥4/5: 49 | ≥4/5: 25 | ≥4/5: 26 | ≥4/5: 8 | ≥4/5: 66% | ≥4/5: 76% | Def 1: 70 Def 2: 63 Def 3: 73 Def 4: 68 Def 5: 70 Def 6: 64 |
Def 1: 4 Def 2: 11 Def 3: 1 Def 4: 6 Def 5: 4 Def 6: 10 |
Def 1: 16 Def 2: 23 Def 3: 4 Def 4: 17 Def 5: 14 Def 6: 17 |
Def 1: 18; Def 2: 11 Def 3: 30 Def 4: 17 Def 5: 20 Def 6: 17 |
Def 1: 94 Def 2: 85 Def 3: 99 Def 4: 92 Def 5: 94 Def 6: 86 |
Def 1: 47 Def 2: 67 Def 3: 12 Def 4: 50 Def 5: 41 Def 6: 49 |
|||||
Matsuoka (2014) [37] | 64.8 | Lobe | 46 | 49 | 149 | 26 | 48.4% | 85.1% | NR | NR | NR | NR | NR | NR | NR | NR |
Junker (2013) [30] | 53.4 | Patient | ≥10/15: 21 ≥11/15: 28 |
≥10/15: 4 ≥11/15: 12 |
≥10/15: 35 ≥11/15: 27 |
≥10/15: 13 ≥11/15: 6 |
≥10/15: 84% ≥11/15: 70% |
≥10/15: 72.9% ≥11/15: 81.8% |
GS ≥ 4 + 3 | 13.7% | ≥13: 54 | ≥13: 2 | ≥13: 8 | ≥13: 9 | ≥13: 96.4% | ≥13: 47% |
Busetto (2013) [16] | 41.7 | Patient | 59 | 7 | 61 | 36 | 89% | 63% | NR | NR | NR | NR | NR | NR | NR | NR |
Rais-Bahrami (2013) [47] | 54.2 | Patient | ≥2/4 : 80 | ≥2/4: 275 | ≥2/4: 187 | ≥2/4: 275 | ≥2/4: 66% | ≥2/4: 59% | GS ≥ 7: GS ≥ 8 |
31.7% | NR | NR | NR | NR | GS ≥ 7: 91% GS ≥ 8: 91% |
GS ≥ 7: 38% GS ≥ 8: 18% |
≥3/4: 251 | ≥3/4: 76 | ≥3/4: 16 | ≥3/4: 76 | ≥3/4: 51% | ≥3/4: 82% | NR | NR | NR | NR | GS ≥ 7: 75% GS ≥ 8: 91% |
GS ≥ 7: 67% GS ≥ 8: 41% |
|||||
Kuru (2013) [34] | 57.6 | Patient | 80 | 14 | 67 | 186 | 85.1% | 73.5% | NR | NR | NR | NR | NR | NR | NR | NR |
Ferda (2013) [20] | 51.2 | Patient | 52 | 2 | 82 | 28 | 96.3% | 74.5% | NR | NR | NR | NR | NR | NR | NR | NR |
Ganie (2013) [21] | 74.7 | Patient | 13 | 3 | 62 | 9 | 59.1% | 95.4% | NR | NR | NR | NR | NR | NR | NR | NR |
Vinet (2013) [57] | 49.3 | Patient | ≥3/5: 11 | ≥3/5: 6 | ≥3/5: 28 | ≥3/5: 24 | ≥3/5: 64.7% | ≥3/5: 53.8% | NR | NR | NR | NR | NR | NR | NR | NR |
≥4/5: 22 | ≥4/5: 11 | ≥4/5: 23 | ≥4/5: 13 | ≥4/5: 66.7% | ≥4/5: 63.8% | NR | NR | NR | NR | NR | NR | NR | NR | |||
Numao (2013) [38] | 45 | Patient | 137 | 57 | 101 | 56 | 70.6% | 64.3% | Def 1: GS ≥4 + 3 and/or ≥20% positive cores and/or max CCL ≥5 mm Def 2: GS ≥ 3 + 4 and/or ≥20% + cores and/or max CCL ≥5 mm Def 3: GS ≥ 3 + 4 and/or ≥20% + cores |
Def 1: 33.3% Def 2:37.8% Def 3: 35.8% |
Def 1: 74 Def 2: 65 Def 3: 69 |
Def 1: 83 Def 2: 92 Def 3: 88 |
Def 1: 160 Def 2: 153 Def 3: 156 |
Def 1: 34 Def 2: 41 Def 3: 38 |
Def 1: 82.4% Def 2: 78.8% Def 3: 80.4% |
Def 1: 58.8% Def 2: 58.5% Def 3: 56% |
Belas (2012) [14] | 53.5 | Patient | 22 | 12 | 23 | 13 | 64.7% | 63.8% | NR | NR | NR | NR | NR | NR | NR | NR |
Ibrahiem (2012) [26] | 73.9 | Patient | 14 | 11 | 57 | 10 | 56% | 85.1% | NR | NR | NR | NR | NR | NR | NR | NR |
Sciarra (2012) [51] | 34.5 | Patient | 41 | 4 | 25 | 14 | 91.1% | 64.1% | NR | NR | NR | NR | NR | NR | NR | NR |
Portalez (2012) [45] | 48.1 | Lesion | Likert: 357 | Likert: 50 | Likert: 81 | Likert: 50 | Likert: 95% | Likert: 38% | Max CCL >3 mm and/or GG 4/5 | NR | NR | NR | NR | NR | NR | NR |
PI-RADS: 404 | PI-RADS: 47 | PI-RADS: 34 | PI-RADS: 47 | PI-RADS: 95% | PI-RADS: 58% | |||||||||||
Watanabe (2012) [59] | 48.1 | Patient | 485 | 73 | 624 | 266 | 86.9% | 70.1% | NR | NR | NR | NR | NR | NR | NR | NR |
Tamada (2011) [54] | 70 | Patient | 12 | 6 | 29 | 3 | 67% | 91% | NR | NR | NR | NR | NR | NR | NR | NR |
Region | 277 | 48 | 55 | 20 | 85% | 73% | ||||||||||
Choi (2011) [18] | 70.6 | Patient | 9 | 5 | 31 | 6 | 64.2% | 75.7% | NR | NR | NR | NR | NR | NR | NR | NR |
Iwazawa (2011) [28] | 40.5 | Region | 887 | 86 | 232 | 219 | 91.1% | 51.4% | NR | NR | NR | NR | NR | NR | NR | NR |
Rouse (2011) [48] | 33.7 | Sextant | 145 | 11 | 74 | 22 | 92.9% | 77.1% | GS ≥ 7: Def 1: ≥3 mm Def 2: ≥5 mm |
Def 1: 26.6% Def 2: 26.2% |
Def 1: 153 Def 2: 153 |
Def 1: 3 Def 2: 3 |
Def 1: 64 Def 1: 63 |
Def 1: 32 Def 2: 33 |
Def 1: 98.1% Def 2: 98.1% |
Def 1: 68.1% Def 2: 67% |
59.6 | Patient | 24 | 14 | 54 | 22 | 63.2% | 71.1% | Def 1: 41.2% Def 2: 36.8% |
Def 1: 30 Def 2: 31 |
Def 1: 4 Def 2: 3 |
Def 1: 43 Def 2: 39 |
Def 1: 4 Def 2: 3 |
Def 1: 88.2% Def 2: 91.2% |
Def 1: 53.8% Def 2: 48.8% |
||
Haffner (2011) [23] | 54.4 | Patient | 154 | 50 | 240 | 111 | 75.4% | 68.3% | NR | NR | NR | NR | NR | NR | NR | NR |
Panebianco (2010) [40] | 42.7 | Patient | NR | NR | NR | NR | 95.1% | 88.2% | NR | NR | NR | NR | NR | NR | NR | NR |
Roy (2010) [49] | 55.9 | Patient | NR | NR | NR | NR | 71% | 75% | NR | NR | NR | NR | NR | NR | NR | NR |
Testa (2010) [55] | 40.7 | Patient | NR | NR | NR | NR | 79.3% | 64% | NR | NR | NR | NR | NR | NR | NR | NR |
Sciarra (2010) [52] | 50 | Patient | 61 | 4 | 66 | 9 | 93.8% | 88% | NR | NR | NR | NR | NR | NR | NR | NR |
Kitajima (2010) [31] | 56.6 | Patient | 311 | 19 | 80 | 14 | 92.2% | 85.1% | NR | NR | NR | NR | NR | NR | NR | NR |
Labanaris (2010) [35] | 73.9 | Patient | 17 | 73 | 96 | 74 | 81.11% | 56.47% | NR | NR | NR | NR | NR | NR | NR | NR |
Kumar (2009) [32] | 21.7 | Patient | 39 | 3 | 10 | 8 | 92.8% | 55% | NR | NR | NR | NR | NR | NR | NR | NR |
Schmuecking (2009) [50] | NR | Lobe | NR | NR | NR | NR | 96% | 61% | NR | NR | NR | NR | NR | NR | NR | NR |
Cheikh (2009) [17] | 24.7 | Patient | 36 | 12 | 11 | 34 | 80% | 22.9% | NR | NR | NR | NR | NR | NR | NR | NR |
Cirillo (2008) [19] | 31.5 | Patient | 19 | 0 | 17 | 18 | 100% | 48.6% | NR | NR | NR | NR | NR | NR | NR | NR |
Kumar (2007) [33] | 13.3 | Patient | 39 | 0 | 11 | 33 | 100% | 25% | NR | NR | NR | NR | NR | NR | NR | NR |
Squillaci (2005) [53] | 50.8 | Patient | 29% | 8% | 25% | 3% | 89% | 80% | NR | NR | NR | NR | NR | NR | NR | NR |
Hara (2005) [24] | 41.5 | Patient | ≥2/3: 40 = 3/3: 47 |
≥2/3: 4 = 3/3: 8 |
≥2/3 30 = 3/3: 26 |
≥2/3: 8 = 3/3: 1 |
≥2/3: 90% = 3/3: 85% |
≥2/3: 78.9% = 3/3: 96.3% |
NR | NR | NR | NR | NR | NR | NR | NR |
Cancer prevalence tended to be higher and mpMRI NPV lower in the biopsy-naïve group as compared with the repeat biopsy group, in men with positive DRE as compared with men with negative DRE and when an endorectal coil was not used ( Table 3 ). There were no clear differences in the prevalence and NPV of the other analysed subgroups (TRUS-guided vs TTP biopsy, biopsy procedures with ≤16 cores vs >16 cores; Table 3 ). However, comparisons must be interpreted with care, due to the small number of studies in some subgroups. In patients with a PSA level of ≤10 ng/ml, the median NPV for overall PCa was 86.3% (IQR, 73.3–93.6%) for a median cancer prevalence of 35.4% (IQR, 27.6–42.5%).
Nb of studies | Median PCa prevalence | Median mpMRI NPV | Nb of studies | Median csPCa prevalence | Median mpMRI NPV | |
---|---|---|---|---|---|---|
Biopsy-naïve patients | 8 | 51.4% (45.5–56.7) | 69.9% (64.2–78) | 1 | 35.8% (NA) | 80.4% (NA) |
Repeat biopsy | 14 | 42% (35.1–52.6) | 82.6% (75.5–93.1) | 3 | 24.4% (19.1–32.8) | 88.2% (87.9–92.3) |
TRUS-guided biopsy | 36 | 49.7% (34.3–57.7) | 84.6% (68.6–92.8) | 4 | 28.1% (21.7–36.5) | 89.3% (82.9–92.4) |
TTP biopsy | 4 | 53.8% (47.5–57.8) | 73.6% (72–78.7) | 2 | 31.6% (30.5–32.8) | 92% (89.9–94) |
Biopsy with ≤16 cores | 28 | 48.7% (39.2–54.8) | 81.9% (66.8–89.3) | 5 | 28.1% (21.8–36.5) | 89.3% (82.9–92.4) |
Biopsy with >16 cores | 5 | 56.6% (51–61.3) | 81.1% (73.1–92.2) | 2 | 31.7% (30.5–32.8) | 92% (89.9–93.9) |
Positive DRE | 1 | 73.9% (NA) | 56% (NA) | 0 | – | – |
Negative DRE | 6 | 36% (34.6–46.8) | 82.7% (74.2–93.1) | 0 | – | – |
Endorectal coil | 17 | 41.7% (30.6–55.9) | 92.8% (79.3–95.4) | 1 | 31.7% (NA) | 91% (NA) |
No endorectal coil | 22 | 50.9% (41.7–56.1) | 77.7% (69.5–86.6) | 7 | 34% (26.9–46.1%) | 87.9% (78.2–92.1) |
Eight studies reported NPV at patient level for overall PCa and fulfilled the inclusion criteria for meta-analysis ( Table 4 ) [22 25 38 41 43 46 56 57] .
Study | Prevalence a (%) | Neg MRI (%) | NPV (%) | PPV (%) | Spe (%) | Se (%) | ||
---|---|---|---|---|---|---|---|---|
All PCa | Score ≥ 3/5 | Grenabo Bergdahl (2016) [22] | 31.3 | 66.9 | 83.7 | 47.5 | 63.2 | 73.1 |
Numao (2013) [38] | 45 | 29.4 | 70.6 | 64.3 | 71.0 | 63.9 | ||
Hauth (2015) [25] | 45.7 | 14.3 | 85.7 | 48.3 | 11.8 | 97.7 | ||
Vinet (2013) [57] | 49.3 | 24.6 | 64.7 | 53.8 | 31.4 | 82.4 | ||
Radtke (2015) [46] | 51 | 27 | 73 | 73.2 | 71.5 | 74.7 | ||
Thompson (2014) [56] | 61.3 | 31.4 | 68.6 | 76.8 | 60.3 | 82.6 | ||
Pokorny (2014) [43] | 63.7 | 30.9 | 69.1 | 82.4 | 69.1 | 82.4 | ||
Score ≥ 4/5 | Pepe (2015) [41] | 37 | 31 | 74.2 | 42 | 36.5 | 78.4% | |
Vinet (2013) [57] | 49.3 | 47.8 | 66.7 | 63.9 | 62.9 | 67.6% | ||
Radtke (2015) [46] | 51 | 73.5 | 63.9 | 92.3 | 95.8 | 48% | ||
Gleason ≥7 PCa | Score ≥ 3/5 | Radtke (2015) [46] | 29.3 | 27 | 87.9 | 45.1 | 59.6 | 80.2% |
a Prevalence of overall prostate cancers (10 first lines) or Gleason ≥7 cancers (last line).
PCa = prostate cancer; MRI = magnetic resonance imaging; Neg MRI = proportion of negative magnetic resonance imaging; NPV = negative predictive value; PPV = positive predictive value; Se = sensitivity; Spe = specificity.
Seven studies used a score of ≥3/5 for defining positive mpMRI ( Fig. 4 A and B) [22 25 38 43 46 56 57] . Fig. 4 C shows the conditional probability plot of 1 – NPV and PPV as a function of overall PCa prevalence. Table 5 shows NPV and PPV estimates for the given values of PCa prevalence.
PCaPrev | PPV | NPV |
---|---|---|
0.30 | 0.43 (0.34–0.53) | 0.88 (0.77–0.99) |
0.40 | 0.54 (0.45–0.64) | 0.82 (0.70–0.94) |
0.50 | 0.64 (0.55–0.73) | 0.76 (0.64–0.88) |
0.60 | 0.73 (0.65–0.80) | 0.67 (0.56–0.79) |
0.70 | 0.81 (0.75–0.87) | 0.57 (0.47–0.67) |
0.75 | 0.84 (0.79–0.89) | 0.51 (0.42–0.59) |
Only three studies used a score of ≥4/5 for defining positive mpMRI ( Table 4 ) [41 46 57] , and a formal meta-analysis could not be performed.
Only one study reporting NPV at patient level for Gleason ≥7 cancers met the selection criteria for inclusion in the meta-analysis. It reported NPV and PPV of 87.9% and 45.1%, respectively, for a prevalence of 29.3% ( Table 4 ) [46] .
We observed a large variability in reported NPV. Many factors, such as differences in mpMRI protocols, definition of negative mpMRI, or biopsy protocols, can explain this variability. However, two major causes of variability must be pointed out. First, the cancer prevalence was highly variable, ranging at patient level from 13% to 74.7% for overall PCa, and from 13.7% to 50.9% for csPCa. This variability was observed in both the biopsy-naïve and the repeat biopsy setting. As NPV depends on prevalence, this had a major impact on reported NPV ( Fig. 3 ). Second, the definition of csPCa was highly variable from one series to another, and differences of up to 21% could be observed in NPV when different definitions of csPCa were used in the same dataset [12 13 38 47 48] .
To account for clinical heterogeneity and to further explore the clinical relevance of the results, we carefully selected studies for inclusion in the meta-analysis based on stringent criteria. Particularly, we included only studies that: (1) had biopsy protocols with at least 10 cores, since it is no longer recommended to obtain less than 10 cores per biopsy; (2) used DWI, which is the most informative technique, at least for cancers in the peripheral zone [60] ; and (3) reported mpMRI findings using a five-level score, so that negative findings could be better defined. We accepted studies using a subjective (Likert) scale because experienced readers obtained equivalent [45 61 62] or better [63] results with the Likert score than with the PI-RADS v1 score. Owing to the large variations of NPV induced by differences in definitions of csPCa, we did not include different definitions in the meta-analysis since this would have introduced unacceptable clinical heterogeneity in the results, possibly resulting in erroneous and biased estimates. We, therefore, a priori restricted the definition of csPCa to cancers with a Gleason score of ≥7, given the low lethal potential of Gleason 6 cancers [64] and the lack of consensus among pathologists on the best method to measure biopsy core invasion length [65 66] .
In this more homogeneous group of studies, the prevalence range was still large (31.3–63.7%). As a result, we modelled the evolution of NPV (and PPV) as a function of overall PCa prevalence. Unfortunately, we could not duplicate this for csPCa since only one study reporting NPV for Gleason ≥7 cancers met the inclusion criteria for meta-analysis.
We included only studies that reported the results of systematic/standard biopsy in patients with negative mpMRI and used the systematic/standard biopsy as a reference standard. It is well known that TRUS-guided biopsy harbours both random and systematic errors, as evidenced by the high rates of positivity of immediate repeat biopsy after a first series of negative biopsies [67 68] , and as confirmed recently by the PROMIS trial [69] . Therefore, using TRUS-guided biopsy as a reference standard may have overestimated the NPV of mpMRI. However, studies using radical prostatectomy specimens as a reference standard have already reported mpMRI detection rates in relation to PCa Gleason score and volume [1] . In this review, we intended to address the more pragmatic question as to whether a negative mpMRI could predict a negative subsequent biopsy. This is an important question because if the NPV of mpMRI was sufficiently high in comparison with the reference standard of systematic/standard biopsies, then in practice a negative mpMRI result could indeed avoid the need for prostate biopsy. Therefore, studies reporting only biopsy results when the mpMRI was positive (eg, obtained through MRI-targeted, guided, or fusion biopsies with added systematic biopsies) were not included in this review.
It is now well established that mpMRI is a sensitive tool for detecting aggressive PCa 1 2 3 69] . However several reasons preclude its broad use as a triage test before biopsy.
Firstly, the population referred to prostate biopsy is not standardised. The large range of reported prevalence for overall PCa and csPCa suggests substantial heterogeneity in the way patients are selected for biopsy. Owing to this heterogeneity, we did not provide a pooled estimate for mpMRI NPV. The role of mpMRI as a triage test before prostate biopsy should be evaluated in the broader context of the selection of patients with a suspicion of (aggressive) PCa. In a recent retrospective study of 514 patients, mpMRI NPV for Gleason ≥7 cancers was 91% when the PSA density was ≤0.2 ng/ml/ml, and only 71% when the PSA density was >0.2 ng/ml/ml ( p = 0.003) [70] . In another series of 288 biopsy-naïve patients, no csPCa (Gleason score ≥7 or maximum cancer core length ≥4 mm) was found in 44 patients with a PSA density of <0.15 ng/ml/ml and a PI-RADS v2 score of <3/5 [71] . We believe that such prestratification of the risk of csPCa is an interesting way for rationalising the use of mpMRI before biopsy. Patients found at very low risk would be spared both mpMRI and biopsy. Patients at a low risk—for whom mpMRI would have an NPV high enough to be used as a triage test—could avoid biopsy in case of negative mpMRI. Patients at a higher risk would need biopsy even in case of negative mpMRI. Many tools can be used to risk stratify the population of patients referred to biopsy, ranging from simple parameters such as PSA density to more complicated risk calculators [72 73] . The impact of these tools on the NPV of prebiopsy mpMRI needs to be carefully evaluated, both in the biopsy-naïve and in the repeat biopsy setting. For the moment, it is impossible to make any recommendations on the best way to risk stratify patients before referring them for mpMRI.
Secondly, the large variability in the definition of csPCa precludes any definitive conclusion on the ability of mpMRI to rule out aggressive cancer. The issue of the most appropriate definition of csPCa on biopsy is complex, since biopsy results may accurately reflect neither tumour burden nor aggressiveness. Nonetheless, there is an urgent need to standardise the histological definition(s) of csPCa, to allow meaningful comparisons between studies.
Thirdly, the specificity of mpMRI remains moderate, and there is a substantial proportion of false positives in the lesions scored 3/5 or 4/5 [1 74 75] , even with the new PI-RADS v2 score [76] . In a series of 62 patients with 116 lesions biopsied under magnetic resonance/ultrasound fusion, the overall cancer detection rates for PI-RADS v2 scores of 3/5 and 4/5 were only 15.8% and 29.8%, respectively [77] . In theory, a triage test used to rule out a disease needs to be highly sensitive for this disease. However, if its specificity is too low, it will be clinically useless since most patients will be positive, whether they have the disease or not. Therefore, if mpMRI is to be used as a triage test in the future, there is a need to improve its specificity. This could be achieved by a continuous refinement of scores [78] . Promising results in characterising csPCa have also been reported with a quantitative analysis [79] .
Finally, all published studies were conducted in specialised centres. The broad use of mpMRI as a triage test assumes good interobserver reproducibility. Unfortunately, interobserver reproducibility of existing scoring systems remains moderate [62 63 80] even with the use of the PI-RADS v2 score [80 81] . Studies evaluating on a large scale the reproducibility of mpMRI findings between expert and nonexpert centres are currently lacking.
Three systematic reviews (including two meta-analyses) regarding the role of mpMRI in localised PCa have been published recently 4 5 6 . Crucially, all three reviews focused exclusively on the sensitivity of mpMRI-targeted, guided, or fusion biopsies in diagnosing overall PCa and csPCa, using TRUS-guided prostate biopsies as reference standards. The impact of systematic biopsies on the outcome was not addressed in any of the reviews, within either the index test or the reference standard. Our review had a totally different research question and objective, focusing on NPV of mpMRI to see if a negative mpMRI can avoid the need for a prostate biopsy. As MRI-targeted/guided/fusion biopsies are not relevant if the mpMRI was negative for cancer, it can be argued that the three reviews assessed a different index test altogether. As such, we believe that the findings of this review are novel and unique, and pave the way for further focused clinical studies.
The current study represents the first systematic review addressing the role of mpMRI as a triage test before biopsy. The review elements were developed in conjunction with a multidisciplinary panel of experts (EAU Prostate Cancer Guidelines Panel), which included a patient representative, and the review was performed robustly in accordance with recognised standards. However, it is limited by the major heterogeneity of the existing literature in patient population, study design, and definitions of positive mpMRI and csPCa. It highlighted further areas of research that could help in defining the best use of mpMRI in the early detection of aggressive PCa in the future.
Although mpMRI can detect aggressive PCa with excellent sensitivity, a definitive conclusion on its role as a triage test before prostate biopsy will be possible only when three main issues are addressed. Firstly, because NPV depends on prevalence, and because overall PCa and csPCa prevalence was highly variable in the published series, it becomes mandatory to define the optimal way to pre-evaluate the risk of csPCa in patients with a suspicion of PCa. Depending on the risk category, mpMRI could then be used to obviate biopsies or not. Secondly, there is a need for consensus definitions of csPCa on biopsy findings to allow interstudy comparisons. Thirdly, although efforts have been made to standardise mpMRI technical protocols and interpretation in the past few years [11 60 76] , there is still a crucial need to improve mpMRI specificity and inter-reader reproducibility.
This systematic review was performed under the auspices of:
The European Association of Urology Guidelines Office Board
The European Association of Urology Prostate Cancer Guideline Panel
Author contributions: Olivier Rouvière had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.
Study concept and design: Rouvière, Mottet, Cornford.
Acquisition of data: Rouvière, Moldovan, Van den Broeck, Yuan.
Analysis and interpretation of data: Rouvière, Moldovan, Van den Broeck, Lam.
Drafting of the manuscript: Rouvière, Moldovan, Van den Broeck, Lam.
Critical revision of the manuscript for important intellectual content: Bellmunt, van den Bergh, Bolla, Briers, Van den Broeck, Cornford, Cumberbatch, De Santis, Fossati, Gross, Henry, Joniau, Lam, Matveev, Moldovan, van der Poel, van der Kwast, Rouvière, Schoots, Wiegel, Mottet.
Statistical analysis: None.
Obtaining funding: None.
Administrative, technical, or material support: Yuan, Sylvester, Marconi.
Supervision: None.
Other: None.
Financial disclosures: Olivier Rouvière certifies that all conflicts of interest, including specific financial interests and relationships and affiliations relevant to the subject matter or materials discussed in the manuscript (eg, employment/affiliation, grants or funding, consultancies, honoraria, stock ownership or options, expert testimony, royalties, or patents filed, received, or pending), are the following: Bellmunt is a company consultant for Janssen, Astellas, Pierre Fabre, Genentech, Merck, Ipsen, Pfizer, Novartis, and Sanofi Aventis. He has received research support from Takeda, Novartis, and Sanofi, and received travel grants from Pfizer and Pierre Fabre. Bolla has received company speaker honoraria from Ipsen and Astellas, honoraria or consultation fees from Janssen, and fellowship and travel grants from Janssen, AstraZeneca, and Astellas. Briers has received grant and research support from Ipsen, European Association of Urology, and Bayer; is an ex officio board member for Europa UOMO; is an ethics committee and advisory group member for REQUITE; is a member patient advisory board member for PAGMI; and is a member of SCA and EMA PCWP. Cornford is a company consultant for Astellas, Ipsen, and Ferring. He receives company speaker honoraria from Astellas, Janssen, Ipsen, and Pfizer; participates in trials from Ferring; and receives fellowships and travel grants from Astellas and Janssen. De Santis is a company consultant for GlaxoSmithKline, Janssen, Bayer, Novartis, Pierre Fabre, Astellas, Amgen, Eisai Inc., ESSA, Merck, and Synthon; has received company speaker honoraria from Pfizer, Takeda, Sanofi Aventis, Shionogi, Celgene, and Teva OncoGenex; has participated in trials for Pierre Fabre, Astellas, Exelixis, Bayer, and Roche; has received fellowship and travel grants from Bayer, Novartis, Ferring, Astellas, Sanofi Aventis, and Janssen; has received grant and research support from Pierre Fabre; has received honoraria from AstraZeneca; and is associated with Amgen. Joniau is a company consultant for Astellas, Ipsen, Bayer, Sanofi, and Janssen; has received company speaker honoraria from Astellas, Amgen, Bayer, Sanofi, Janssen, and Ipsen; has participated in trials for Astellas, Janssen, and Bayer; has received fellowship and travel grants from Astellas, Amgen, Bayer, Sanofi, Janssen, Ipsen, and Pfizer; and has received grant and research support from Astellas, Bayer, and Janssen. Matveev has received company speaker honoraria from Sanofi and Astellas, has participated in trials for Astellas, Pfizer and Novartis. Lam is a company consultant for and has received company speaker honoraria from Pfizer, GSK, Astellas, and Ipsen. van der Poel is a company consultant for Intuitive Surgical, has participated in trials for Astellas and Steba Biotech, and has received grant and research support from Astellas. Rouvière is a company consultant for EDAP-TMS, Bracco, and Philips; has received company speaker honoraria from EDAP-TMS, Bracco, and Philips; and has participated in trials for EDAP-TMS and Bracco. Wiegel has received company speaker honoraria from Astellas, Takeda, Hexal, Ipsen, Janssen-Cilac, and Ferring. Mottet has received grant and research support from Takeda Pharmaceutical, Millenium, Astellas, Pierre Fabre, Sanofi, and Pasteur, and has received honoraria or consultation fees from Takeda Pharaceutical, Millenium, Jansen, Astellas, BMS, Bayer, Ipsen, Ferring, Novartis, Nuclétron, Pierre Fabre, Sanofi, and Zeneca. van den Bergh, Van den Broeck, Cumberbatch, Fossati, Gross, Henry, van der Kwast, Sylvester, Yuan, Schoots, Moldovan, and Marconi have nothing to disclose.
Funding/Support and role of the sponsor: None.
A correlation with radical prostatectomy specimens has demonstrated that multiparametric magnetic resonance imaging (mpMRI) has excellent sensitivity in detecting prostate cancer (PCa) with a Gleason score of ≥7 1 2 3 . As a result, prostate mpMRI is increasingly used in patients with a suspicion of PCa to localise abnormal areas before biopsy. A large body of literature has shown that targeted biopsies of suspicious lesions seen on mpMRI (TBx) improved the detection of clinically significant PCa (csPCa), at least in the repeat biopsy setting 4 5 6 . As a result, it is now recommended that an mpMRI is performed before repeat biopsy to allow TBx of suspicious lesions in addition to standard biopsies [7] .
Some authors have recently suggested that, besides improving csPCa detection, mpMRI could also be used as a triage test so that patients with negative mpMRI findings could obviate biopsy. Such a strategy remains highly controversial [8] and depends upon the negative predictive value (NPV) of mpMRI. Therefore, the European Association of Urology Prostate Cancer Guidelines Panel undertook this systematic review and meta-analysis to assess the NPV of mpMRI in patients with a suspicion of PCa and, thus, its potential role in eliminating unnecessary prostate biopsy.
Our primary aim was to systematically evaluate the performance of negative prebiopsy prostate mpMRI in predicting a negative biopsy result for overall PCa and csPCa in biopsy-naïve men and in men with previously negative biopsies. A further objective was to explore and define factors that may contribute to relevant thresholds in order to provide guidance for future studies.
The review was performed according to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) statement [9] . The review protocol was published in PROSPERO database ( http://www.crd.york.ac.uk/PROSPERO; registration number CRD42015021929). Databases searched included the Embase and OVID Medline databases, the Cochrane database of systematic reviews, and the Cochrane Central Register for Clinical Trials, covering from January 1, 2000 to February 13, 2016. Systematic or standard prostate biopsies were used as reference standards, with positive or negative cases of PCa being determined by histopathological examination. The detailed search strategy is presented in Supplement 1.
Included studies focused on men who were assessed for suspected PCa by mpMRI before undergoing prostate biopsy. Studies enrolling both biopsy-naïve men and men who had undergone previous negative biopsies were included. Prebiopsy prostate mpMRI was considered the index test and comprised T2-weighted imaging (T2WI) and at least one functional imaging technique (diffusion-weighted imaging [DWI], dynamic contrast-enhanced imaging [DCEI], or magnetic resonance spectroscopic imaging [MRSI]). For inclusion, studies had to report on false negatives and true negatives, in order to calculate NPV (ie, results of systematic/standard prostate biopsies when the mpMRI was negative). When available, false positive and true positive findings were also noted to calculate the positive predictive value (PPV) and the cancer prevalence. There was restriction neither on the biopsy technique (transrectal or transperineal) nor on the number of biopsy cores. Studies using radical prostatectomy specimens as reference standards were excluded, as were studies evaluating men with histologically proven PCa. Studies with less than 50 participants were excluded. No language restrictions were applied.
Two reviewers (P.C.M. and T.V.D.B.) independently screened all abstracts and full-text articles for eligibility. Disagreement was resolved by consensus or reference to an independent third party (L.M.). All screening was performed using a predefined eligibility form.
Using a data extraction form developed a priori, the same two reviewers independently extracted data concerning study methodology, patient characteristics, technical characteristics of the MR scanners, mpMRI protocol, mpMRI scoring system, definition of positive mpMRI, biopsy protocol, and definition of csPCa. Any discrepancies concerning data extraction were resolved by consensus or reference to an independent arbiter (O.R. or T.B.L.).
To assess the risk of bias (RoB), all included reports were reviewed using the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool for diagnostic accuracy studies [10] .
Outcome data regarding false negative and true negative values of mpMRI before prostate biopsy were recorded as reported by authors. When not available, data were indirectly derived from specificity, sensitivity, and prevalence values reported by authors using an online Bayesian statistics calculator ( http://www.medcalc.com/bayes.html ). Descriptive statistics were used to summarise baseline characteristics and outcomes, including median and interquartile range (IQR) for estimates of NPV across studies. A correlation between mpMRI NPV and a positive biopsy rate was established using the Pearson's correlation coefficient.
A meta-analysis was undertaken to calculate pooled NPV and PPV. To ensure appropriate clinical homogeneity of the studies included in the meta-analysis, we selected only the studies enrolling biopsy-naïve patients and/or patients with a history of negative biopsy, and fulfilling the following criteria that were defined a priori: (1) reference standard consisting of prostate biopsy with at least 10 samples on all patients; (2) mpMRI protocol comprising at least T2WI and DWI; (3) mpMRI results presented as a five-level score, using a subjective Likert scale or the Prostate Imaging Reporting Data System (PI-RADS) score [11] ; (4) definition of positive mpMRI as a score ≥3/5 or ≥4/5; and (5) results reported on a per patient basis. In addition, only studies defining csPCa as Gleason ≥7 cancers were selected for the meta-analysis assessing the mpMRI NPV for csPCa. A bivariate random-effects approach was employed using the Midas package in Stata 12 (StataCorp LP, College Station, TX, USA). Since the NPV decreases and the PPV increases as the prevalence increases, post-test probability estimates of NPV and PPV were reported for the given values of the prevalence based on Bayes’ theorem.
For other studies not included in the meta-analysis based on the criteria described above, a narrative synthesis of the data was performed. To explore and define clinical heterogeneity, subgroups were analysed at patient level based on the following variables: biopsy-naïve versus previous negative biopsy; patients with positive versus negative digital rectal examination (DRE); mpMRI performed with an endorectal versus without an endorectal coil; transrectal ultrasound (TRUS) versus template transperineal (TTP) biopsy approach; and ≤16 cores versus >16 cores as the reference standard. Studies reporting mpMRI NPV for patients with a prostate-specific antigen (PSA) level of ≤10 ng/ml were also reported separately.
The study selection process is depicted in the PRISMA flow diagram ( Fig. 1 ). A total of 2980 abstracts were retrieved. After abstract screening and removal of duplicates, 240 articles were eligible for full text screening, of which 48 studies were eligible for inclusion 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 .
Out of the 48 included studies, 42 were single-centre and six were multicentre studies. Thirty-four studies were prospective and six were retrospective, whilst the design of the rest was unclear. RoB assessment using QUADAS-2 was performed for each of the individual studies ( Fig. 2 A and B). Overall, the RoB was highly heterogeneous across studies for all criteria, except for the reference standard domain, in which RoB was low in most studies.
The 48 studies comprised a total of 9613 men who underwent prostate mpMRI followed by biopsy. The study and patient baseline characteristics are presented in Table 1 . The patient population consisted of biopsy-naive men in nine studies, men with at least one previous negative biopsy in 16 studies, and both biopsy-naïve men and men with a history of previous negative biopsy in nine studies. In 14 studies, the biopsy history of the patients was unclear.
Study | Study design | Period | Population | Pt Nb | Mean/median* age (yr) | Mean/median* PSA (ng/ml) | Mean/median* prostate volume (cm 3 ) | Magnetic field strength | MR pulse sequences | Endorectal coil | MR score | Definition of positive MRI | Reference standard |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Hauth (2015) [25] | Prospective | 2011–2013 | FB | 94 | 64 (43–83) | 9 (3–31) | 51 (17–140) | 1.5 T | T2WI/DWI/DCEI/MRSI | No | PI-RADS v1 | ≥3 | 11–13-core TRUS SBx + TBx |
Lamb (2015) [36] | Retrospective | 2013–2013 | FB & PNB | 173 | NR | NR | NR | 1.5 T | T2WI/DWI | NR | NR | NR | 12-core TRUS SBx |
Brock (2015) [15] | Prospective | 2013–2014 | PNB | 168 | 64* (IQR 59–70) | 9.2* (IQR 6.7–13.4) | 55.4* (IQR 42–80) | 3 T | T2WI/DWI/DCEI | No | PI-RADS v1 | NR | 12/24-core TRUS SBx + TBx |
Grenabo Bergdahl (2016) [22] | Prospective | 2013–2014 | FB & PNB | 83 | 69.3* (IQR 69–69.6) | 1.6* (IQR 0.9–2.7) | NR | 3 T | T2WI/DWI/DCEI/MRSI | No | PI-RADS v1 | ≥3 | 10-core TRUS SBx + TBx |
Wang (2015) [58] | Prospective | 2002–2009 | FB & PNB | 586 | 70 (26–91) | 11.11* (0.02–9794) | NR | 1.5 T | T2WI/DWI/DCEI/MRSI | Yes | PI-RADS v1 | ≥3 | TRUS SBx |
Pepe (2015) [41] | Prospective | 2011–2014 | PNB | 100 | 64* | 8.6* (4.2–10) | NR | 3 T | T2WI/DWI/DCEI/MRSI | No | PI-RADS v1 | ≥4 | TPBx + TBx |
Panebianco (2015) [39] | Prospective | 2011–2014 | FB (61.62%) & PNB (38.34%) | 925 (1140 total cohort) |
NR | NR | NR | 3 T | T2WI/DWI/DCEI | Yes | PI-RADS v1 | NR | 14-core TRUS SBx; 45-core sat TPBx + TBx |
Radtke (2015) [46] | Prospective | 2013–2013 | FB (63.3%) & PNB (36.7%) | 294 | 64* (60–71) | 7.3 (6.0) | 47 (37.5) | 3 T | T2WI/DWI/DCEI | No | PI-RADS v1 | PI-RADS ≥2; PI-RADS ≥3; PI-RADS ≥4; PI-RADS = 5; |
24-core TPBx + TBx |
Itatani (2014) [27] | Retrospective | 2004–2007 | NR | 193 | 68.9 (8.4); 70* (47–89) | 11.8 (15.9); 7.9* (1.22–159) | NR | 1.5 T | T2WI/DWI/DCEI | No | 1–5 scale (Likert) | ≥3 | 12–14-core TRUS SBx |
Porpiglia (2014) [44] | Prospective | 2011–2013 | PNB | 170 | 65* (60–70) | 6.9* (5.2–9.8) | 42* (36–48) | 1.5 T | T2WI/DWI/DCEI | Yes | Dichotomous | Positive: at least 2/3 MR seq. with suspicious findings | 18–24-core TRUS SBx (volume dependent) |
Thompson (2014) [56] | Prospective | 2012–2013 | FB (88%) & PNB (12%) | 150 | 62.4* (IQR 55.0–66.4) | 5.6* (IQR 4.5–7.5) | 40* (IQR 30–57) | 1.5 T (47%) & 3 T (53%) | T2WI/DWI/DCEI | No | PI-RADS v1 | ≥3 | Median of 30 TPBx (volume dependent) |
Pokorny (2014) [43] | Prospective | 2012–2013 | FB | 223 | 63* (IQR 57–68) | 5.3* (IQR 4.1–6.6) | 41* (IQR 30–59) | 3 T | T2WI/DWI/DCEI | No | PI-RADS v1 | ≥3 (primary); ≥4 |
12-core TRUS SBx + TBx |
Petrillo (2014) [42] | Prospective | 2009–2010 | NR | 136 | NR | NR | NR | 1.5 T | T2WI/DWI/MRSI | Yes | 1–5 scale (Likert) | ≥3 | 12–16-core TRUS SBx (volume + PSA dependent) |
Javali (2014) [29] | Retrospective | 2002–2011 | NR | 140 | Control: 62.4 (10.5); Study: 62.9 (12.1) | Control: 6.8 (2.3); Study: 6.87 (2.6) | Control: 44 (14.2); Study: 43 (18.4) | 1.5 T | T2WI/MRSI | Yes | Dichotomous | Cit/[Cho + Cr] < 1.2 | 6-core TRUS SBx ( n = 69), 12-core TRUS SBx ( n = 119) |
Abd-Alazeez (2014) [13] | Prospective | 2007–2011 | FB | 129 | 62* (41–82) | 5.8* (1.2–20) | 40* (16–137) | 1.5 & 3 T | T2WI/DWI/DCEI | No | PI-RADS v1 | ≥3 (primary); ≥4 |
20-core TPBx |
Abd-Alazeez (2014) [12] | Retrospective | NR | PNB | 54 | 64* (39–75) | 10* (2–23) | 53* (19–136) | 1.5 & 3 T | T2WI/DWI/DCEI | No | PI-RADS v1 | ≥3 (primary); ≥4 |
≥20-core TPBx + TBx ( n = 15) |
Matsuoka (2014) [37] | Prospective | 2007–2012 | NR | 135 | 67* (50–80) | 7.0* (2.9–19.8) | 25.4* (12.7–90.2) | 1.5 T | T2WI/DWI | No | 1–5 scale (Likert) | ≥3 | 14-core TRUS SBX |
Junker (2013) [30] | Retrospective | 2011–2013 | PNB | 73 | 62 (7.4) | 7.0* (5.1–12.9) | 45* (34–61) | 3 T | T2WI/DWI/DCEI | No | PI-RADS | PI-RADS ≥10 and ≥11 for all PCa PI-RADS ≥13 for significant PCa |
10-core TRUS SBx + TBx |
Busetto (2013) [16] | Prospective | 2010–2012 | PNB | 163 | 66.4 (5.3) | 6.8 (1.6) | NR | 3 T | T2WI/DWI/DCEI/MRSI | Yes | NR | NR | 10-core TRUS SBx + TBx |
Rais-Bahrami (2013) [47] | Prospective | 2007–2012 | NR | 583 | 61.3 (8.4) | 9.9 (13.1) | NR | 3 T | T2WI/DWI/DCEI/MRSI | Yes | 1–4 scale (Likert) | ≥2 ≥3 |
12-core TRUS SBx + TBx |
Kuru (2013) [34] | Prospective | 2010–2011 | FB (51%) & PNB (49%) | 347 | 65.3 (42–82) | 9.85 (0.5–104) | 48.7 (9–180) | 3 T | T2WI/DWI/DCEI | No | 1–3 scale (Likert) | ≥2 | 12–36-core TRUS SBx (volume dependent) + TBx |
Ferda (2013) [20] | Prospective | NR | NR | 164 | (49–74) | (4.2–123) | NR | 3 T | T2WI/DWI/DCEI/MRSI | No | NR | In house | TRUS SBx |
Ganie (2013) [21] | NR | 2007–2009 | PNB | 87 | NR | NR | NR | 1.5 T | T2WI/MRSI | Yes | MRSI Cho/Cit ratio | In house | 6 core TRUS SBx + MRI TBx |
Vinet (2013) [57] | Prospective | 2009–2011 | FB | 69 | NR | 5.2* (3.2–28) | NR | 1.5 T (35 pts) & 3 T (34 pts) | T2WI/DWI/DCEI | No | 1–5 scale (Likert) | ≥3 | 12-core TRUS SBx + TBx |
Numao (2013) [38] | Prospective | 2006–2010 | FB | 351 | 65* (59–70) | 6.3* (4.9–9.1) | 32* (24–42) | 1.5 T | T2WI/DWI/DCEI (no DCEI in 42 pts) | No | 1–5 scale (Likert) | ≥3 | 3D 26-core (12 TRUS SBx + 14 TPBx – 203 pts); 3D 14-core (6 TRUS SBx + 8 TPBx – 102 pts); TPBx 14 core (46 pts) |
Belas (2012) [14] | Prospective | 2010–2011 | FB | 71 | 66* (47–76) | 7* (4–10) | 45* (15–150) | 1.5 T | T2WI/DWI/DCEI | No | TZ: 0–4 scale PZ: 0–10 scale |
TZ: >2 PZ: >6 |
12-core TRUS SBx + TBx |
Ibrahiem (2012) [26] | Prospective | 2008–2009 | FB | 100 | 65.03 (7.13) | 26.3 (24.2) | 60.09 (28.7) | 1.5 T | T2WI/DWI | No | NR | In house | 12-core TRUS SBX |
Sciarra (2012) [51] | Prospective | 2008–2011 | PNB | 84 | 64.09 (46–76) | 7.07 (4.2–15.5) | NR | 3 T | T2WI/DWI/DCEI/MRSI | Yes | NR | NR | 10-core TRUS Bx + TBx |
Portalez (2012) [45] | Prospective | 2011 | PNB | 129 | 64.7 (47–79) | 9.6 (2.7–40) | 51.1 (12–192) | 1.5 T | T2WI/DWI/DCEI | Mixed | 1–5 scale (Likert) PI-RADS |
Likert ≥3 PI-RADS ≥9 |
10–12-core TRUS SBx + TBx |
Watanabe (2012) [59] | Prospective | 2004–2008 | NR | 1448 | 72 (7.5) | NR | NR | 1.5 T | T2WI/DWI | No | NR | ADC value ≤1.35 × 10 −3 mm 2 /s | 8-core TRUS SBx + TBx |
Tamada (2011) [54] | Retrospective | 2006–2009 | NR | 50 | 70 (40–84) | 6.84* (4.06–9.94) | NR | 1.5 T | T2WI/DWI/DCEI | No | NR | In house | 12-core TRUS SBx |
Choi (2011) [18] | NR | 2009–2010 | NR | 51 | 67.16 (56–90) | 14.16 (1.02–38.9) | 42.98 (13.8–77.3) | 3 T | T2WI/DWI | NR | NR | NR | 10–12-core TRUS SBx + TBx |
Iwazawa (2011) [28] | Retrospective | 2008–2009 | NR | 178 | 68.8 (41–86) | 20.51 (4.04–568.5) | NR | 1.5 T | T2WI/DWI/DCEI | NR | 1–4 scale (Likert) | NR | 10–12-core TRUS SBx (TBx included in SBx chart) |
Rouse (2011) [48] | Prospective | 2005–2007 | PNB | 114 | 63.6 (41–83) | 13.4 (0–228) | NR | 1.5 T | T2WI/DWI/DCEI | NR | 1–5 scale (Likert) | ≥3 | TRUS SBx |
Haffner (2011) [23] | Prospective | 2005–2009 | FB | 555 | 64* (47–83) | 6.75* (0.18–100) | 46* (15–200) | 1.5 T | T2WI/DCEI | No | 1–5 scale (Likert) | ≥3 | 10-core TRUS SBx + TBx |
Panebianco (2010) [40] | Prospective | 2007–2009 | PNB | 150 | 61.2 (46–78) | 9.42 (3.91) | 41.17 (7.47) | 1.5 T | T2WI/DCEI/MRSI | Yes | NR | In house | 10-core TRUS SBx (TBx included in SBx chart) |
Roy (2010) [49] | Not specified | 2011–2009 | FB (53%) & PNB (47%) | 103 | 63 (52–78) | 7* | NR | 3 T | T2WI/DWI/DCEI | Yes | NR | NR | 8-core TRUS SBx + TBx |
Testa (2010) [55] | Not specified | 2007 | PNB | 54 | 63.9 (52–76) | 11.4 (3–42) | 59.3 (30–150) | 1.5 T | T2WI/MRSI | Yes | 1–3 scale (Likert) | ≥2 | 12-core TRUS SBx + TBx |
Sciarra (2010) [52] | Prospective | 2007–2009 | PNB | 110 | 63.5 (49–74) | NR | NR | 1.5 T | T2WI/DCEI/MRSI | Yes | NR | In house | 10-core TRUS SBx + TBx |
Kitajima (2010) [31] | Prospective | 2008–2009 | NR | 53 | 69* (56–84) | 11.1* (4.2–112.1) | NR | 3 T | T2WI/DWI/DCEI | No | 1–5 scale (Likert) | ≥3 | 20-core TPBx |
Labanaris (2010) [35] | Prospective | 2004–2008 | PNB | 260 | NR | NR | NR | 1 T | T2WI/DWI/DCEI | Yes | Dichotomous | In house | 18-core TRUS SBx |
Kumar (2009) [32] | NR | NR | NR | 61 | 65.3 (9.3) | 16.5 (0.21–155) | NR | 1.5 T | T2WI/MRSI | Yes | NR | (Cit/(Cho + Cr) ≤ 1.2 | TRUS Bx |
Schmuecking (2009) [50] | NR | NR | FB & PNB | 67 | 68 | 11.5 | NR | 1.5 T | T2WI/DCEI | No | NR | NR | 20-core Bx |
Cheikh (2009) [17] | Retrospective | 2005–2008 | PNB | 93 | 63.2 (52–74) | 9.63 (1.6–40) | NR | 1.5 T | T2WI/DCEI | No | Dichotomous | In house | 12-core TRUS SBx + TBx |
Cirillo (2008) [19] | Prospective | 2004–2006 | PNB | 54 | 65.5 (5.2) | 10.8 (7.5) | NR | 1.5 T | T2WI/MRSI | Yes | Dichotomous | In house | 10-core TRUS SBx + TBx |
Kumar (2007) [33] | Prospective | 2003–2005 | NR | 83 | NR | NR | NR | 1.5 T | T2WI/MRSI | Yes | NR | NR | 12-core TRUS SBx + TBx |
Squillaci (2005) [53] | Prospective | 2004–2005 | NR | 65 | NR | NR | NR | 1.5 T | T2WI/DCEI/MRSI | No | 1–3 scale (Likert) | ≥2 | 10-core TRUS SBx + TBx |
Hara (2005) [24] | Prospective | 2003–2004 | FB | 90 | 67.2 (NR) | NR | NR | 1.5 T | T2WI/DCEI | No | 1–3 scale (Likert) | ≥2 = 3 |
14-core TRUS SBx |
The magnetic field strength was 1, 1.5, and 3 T in one, 28, and 15 studies, respectively. Four studies used both 1.5 and 3 T MR systems. DWI and DCEI were used in 36 and 35 studies, respectively. Nineteen studies also added MRSI. An endorectal coil was used in 18 studies. The definition of positive mpMRI varied across studies. The PI-RADS v1 score was used in 12 studies, a five-level subjective (Likert) score was used in eight studies, and one study reported data based on the two scoring systems. In-house criteria were used in 13 studies for defining positive mpMRI, and five studies used a dichotomous definition. Nine studies did not report on the criteria for positive mpMRI. No study used the PI-RADS v2 score.
Regarding the reference standard, TRUS-guided biopsies were used in 39 studies, TTP biopsies in six studies, and mixed TRUS-guided and TTP biopsies in two studies. In one study, the biopsy approach was unclear. The number of cores per biopsy procedure was ≤16 in 30 studies, >16 in nine studies, and variable among patients in three studies. For six studies, the number of biopsy cores taken was unclear.
At patient level, the median biopsy positivity rate (ie, cancer prevalence) was 50.4% (IQR, 36.4–57.7%) for overall cancer and 32.9% (IQR, 28.1–37.2%) for csPCa ( Table 2 ). The median mpMRI NPV was 82.4% (IQR, 69.0–92.4%) for overall cancer and 88.1% (IQR, 85.7–92.3) for csPCa. NPV significantly decreased when cancer prevalence increased, both for overall cancer ( r = –0.64, p < 0.0001) and csPCa ( r = –0.75, p = 0.032; Fig. 3 ). In addition, NPV was highly dependent on the definition used for csPCa, with differences of up to 21% when several definitions were used in the same dataset [12 13 38 47 48] .
Study | Overall PCa prevalence (%) | Reporting level | Multiparametric MRI performance for PCa detection | Definition of csPCa | csPCa prevalence | Multiparametric MRI performance for csPCa detection | ||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
TN | FN | TP | FP | NPV | PPV | TN | FN | TP | FP | NPV | PPV | |||||
Hauth (2015) [25] | 45.7 | Patient | 6 | 1 | 42 | 45 | 85.7% | 48.3% | Low grade: GS ≤ 6 High grade: GS ≥ 7 |
NR | NR | NR | NR | NR | NR | NR |
Lesion | 59 | 13 | 55 | 73 | 81.9% | 43% | ||||||||||
Lamb (2015) [36] | 65.9 | Patient | 23 | 22 | 92 | 36 | 51.1% | 71.9% | GS ≥ 7 | 50.9% | 31 | 14 | 71 | 57 | 68.9% | 55.5% |
Brock (2015) [15] | 42.3 | Patient | 17 | 7 | 56 | 88 | 70.8% | SBx: 38.8% TBx: 22.2% Duo: 44.4% |
Epstein: GS > 6 and/or max CCL ≥50% | 24.4% | SBx: 21 | SBx: 3 | SBx: 38 TBx: 27 duo: 47 |
SBx: 106 TBx: 117 duo: 97 |
87.5% | SBx: 26.4% TBx: 18.8% duo: 32.6% |
Grenabo Bergdahl (2016) [22] | 33.7 | Patient | 36 | 7 | 19 | 21 | 83.7% | 47.5% | Clinically insignificant PCa: T1c, PSAd < 0.15, GS < 7, ≤2 positive cores, and unilateral cancer | NR | NR | NR | NR | NR | NR | NR |
Wang (2015) [58] | 58 | Patient | 165 | 8 | 332 | 81 | 95.4% | 80.4% | NR | NR | NR | NR | NR | NR | NR | NR |
Pepe (2015) [41] | 37 | Patient | 23 | 8 | 29 | 40 | 74.2% | 42% | GS ≥ 7 or GS 6 with CCL ≥ 50% | NR | NR | NR | NR | NR | 100% | 55.8% |
Panebianco (2015) [39] | 74.7 | Patient | Group A (satBx): 104 | Group A (satBx): 43 | Group A: 186 | Group A: 22 | Group A (satBx): 70.7% | Group A: 89.4% | NR | 60% | Group A: 147 | Group A: 0 | Group A: 183 | Group A: 25 | Group A: 100% | Group A: 88% |
Group B (TRUSGB NR TRUS G satBx): 93 | Group B (TRUSGB NR TRUS G satBx): 37 | Group B: 417 before and 425 after satBx | Group B: 23/440 and 15/440 after satBx. | Group B (TRUSGB–TRUS G satBx): 71.5% | Group B: 94.8% before and 96.6% after satBx | 71.9% | Group B: 130 | Group B: 0 | Group B: 410 |
Group B: 30 | Group B: 100% | Group B: 93.2% | ||||
Radtke (2015) [46] | 51 | Patient | ≥2/5: 80 ≥3: 103 ≥4: 138 = 5: 142 |
≥2/5: 18 ≥3/5: 38 ≥4/5: 78 = 5/5: 126 |
≥2/5: 132 ≥3/5: 112 ≥4/5: 72 = 5/5: 24 |
≥2/5: 64 ≥3/5: 41 ≥4/5: 6 = 5/5: 2 |
≥2/5: 81.6% ≥ 3/5: 73.1% ≥ 4/5: 63.9% = 5/5: 53% |
≥2/5: 67.4% ≥ 3/5: 73.2% ≥ 4/5: 92.3% = 5/5: 92.3% |
GS ≥ 7 | 29.3% | ≥2/5: 91 ≥3/5: 124 ≥4/5: 183 = 5/5: 203 |
≥2/5: 7 ≥3/5: 17 ≥4/5: 33 = 5/5: 65 |
≥2/5: 79 ≥3/5: 69 ≥4/5: 53 = 5/5: 21 |
≥2/5: 117 ≥3/5: 84 ≥4/5: 25 = 5/5: 5 |
≥2/5: 92.2% ≥3/5: 87.9% ≥4/5: 84.7% = 5/5: 75.8% |
≥2/5: 40.3% ≥3/5: 45.1% ≥4/5: 68% = 5/5: 80.7% |
Itatani (2014) [27] | 13 | Patient | 168 | 25 | NR | NR | 87% | NR | (1) PSAd ≥ 0.1 or GP 4/5 or ≥ 3/6 pos cores; max CCL < 50% (2) PSAd ≥ 0.15 or GP 4/5 or max core length invasion < 3 mm (min 6 cores) |
NR | NR | NR | NR | NR | NR | NR |
Porpiglia (2014) [44] | 30.6 | Patient | 107 | 5 | 47 | 11 | 95.5% | 81% | NR | NR | NR | NR | NR | NR | NR | NR |
Thompson (2014) [56] | 61.3 | Patient | 35 | 16 | 76 | 23 | 68.6% | 76.7% | Moderate or high risk Moderate risk: GS 7 (GP4 >5%) and <50% of positive cores or GS 6–7 (GP4 ≤ 5%) and either ≥30% of positive cores or max core length invasion ≥8 mm High risk: GS ≥ 7 (GP4 > 5%); ≥50% + cores or GS ≥ 8 |
34% | 49 | 2 | 49 | 50 | 96% | 49.5% |
Pokorny (2014) [43] | 63.7 | Patient | ≥3/5: 56 ≥4/5: 74 |
≥3/5: 25 ≥4/5: 40 |
≥3/5: 101 ≥4/5: 86 |
≥3/5: 41 ≥4/5: 23 |
≥3/5: 69.1% ≥4/5: 64.9% |
≥3/5: 71.1% ≥4/5: 78.9% |
NR | NR | NR | NR | NR | NR | NR | NR |
Petrillo (2014) [42] | 18.4 | Patient | 56 | 4 | 21 | 55 | 93% | 28% | NR | NR | NR | NR | NR | NR | NR | NR |
Javali (2014) [29] | 16.4 | Patient | 49 | 1 | 22 | 68 | 98% | 24.4% | NR | NR | NR | NR | NR | NR | NR | NR |
Abd-Alazeez (2014) [13] | 54.7 | Lobe | ≥3/5: 33 | ≥3/5: 14 | ≥3/5: 127 | ≥3/5: 84 | ≥3/5: 70% | ≥3/5: 60% | Def 1: GS ≥ 4 + 3 and/or max CCL ≥ 6 mm Def 2: GS ≥ 3 + 4 and/or max CCL ≥ 4 mm Def 3: GS ≥ 4 + 3 Def 4: GS ≥ 3 + 4 Def 5: max CCL ≥ 6 mm Def 6: max CCL ≥ 4 mm |
Def 1: NR Def 2: 44.2% Def 3: 23.2% Def 4: 36% Def 5: 32.9% Def 6: 39.5% |
Def 1: 46 Def 2: 42 Def 3: 47 Def 4: 43 Def 5: 46 Def 6: 43 |
Def 1: 1 Def 2: 5 Def 3: 0 Def 4: 4 Def 5: 1 Def 6: 4 |
Def 1: 45 Def 2: 72 Def 3: 13 Def 4: 50 Def 5: 39 Def 6: 59 |
Def 1: 166 Def2: 139 Def 3: 198 Def 4: 161 Def 5: 172 Def 6: 152 |
Def 1: 98 Def 2: 89 Def 3: 100 Def 4: 92 Def 5: 98 Def 6: 91 |
Def 1: 21 Def 2: 34 Deg 3: 6 Def 4: 24 Def 5: 19 Def 6: 28 |
≥4/5: 87 | ≥3/5: 62 | ≥3/5: 79 | ≥3/5: 30 | ≥3/5: 58% | ≥3/5: 73% | Def 1: 140 Def 2: 124 Def 3: 148 Def 4: 133 Def 5: 141 Def 6: 131 |
Def 1: 9 Def 2: 25 Def 3: 1 Def 4: 16 Def 5: 8 Def 6: 18 |
Def 1: 37 Def 2: 52 Def 3: 12 Def 4: 38 Def 5: 32 Def 6: 45 |
Def 1: 72 Def 2: 57 Def 3: 97 Def 4: 71 Def 5: 77 Def 6: 64 |
Def 1: 94 Def 2: 83 Def 3: 99 Def 4: 89 Def 5: 95 Def 6: 88 |
Def 1: 34 Def 2: 48 Def 3: 11 Def 4: 35 Def 5: 30 Def 6: 42 |
|||||
Abd-Alazeez (2014) [12] | 47.2 | Lobe | ≥3/5: 26 | ≥3/5: 13 | ≥3/5: 38 | ≥3/5: 31 | ≥3/5: 66% | ≥3/5: 55% | Def 1: GS ≥ 4 + 3 and/or max CCL ≥ 6 mm Def 2: GS ≥ 3 + 4 and/or max CCL ≥ 4 mm Def 3: GS ≥ 4 + 3 Def 4: GS ≥ 3 + 4 Def 5: max CCL ≥ 6 mm Def 6: max CCL ≥ 4 mm |
Def 1: 18.5% Def 2: 31.5% Def 3: 4.6% Def 4: 21.3% Def 5: 16.7% Def 6: 25% |
Def 1: 37 Def 2: 31 Def 3: 39 Def 4: 36 Def 5: 37 Def 6: 32 |
Def 1: 2 Def 2: 8 Def 3: 0 Def 4: 3 Def 5: 2 Def 6: 7 |
Def 1: 18 Def 2: 26 Def 3: 5 Def 4: 20 Def 5: 16 Def 6: 20 |
Def 1: 51 Def 2: 43 Def 3: 64 Def 4: 49 Def 5: 53 Def 6: 49 |
Def 1: 95 Def 2: 79 Def 3: 100 Def 4: 92 Def 5: 95 Def 6: 82 |
Def 1: 26 Def 2: 38 Def 3: 7 Def 4: 29 Def 5: 23 Def 6: 29 |
≥4/5: 49 | ≥4/5: 25 | ≥4/5: 26 | ≥4/5: 8 | ≥4/5: 66% | ≥4/5: 76% | Def 1: 70 Def 2: 63 Def 3: 73 Def 4: 68 Def 5: 70 Def 6: 64 |
Def 1: 4 Def 2: 11 Def 3: 1 Def 4: 6 Def 5: 4 Def 6: 10 |
Def 1: 16 Def 2: 23 Def 3: 4 Def 4: 17 Def 5: 14 Def 6: 17 |
Def 1: 18; Def 2: 11 Def 3: 30 Def 4: 17 Def 5: 20 Def 6: 17 |
Def 1: 94 Def 2: 85 Def 3: 99 Def 4: 92 Def 5: 94 Def 6: 86 |
Def 1: 47 Def 2: 67 Def 3: 12 Def 4: 50 Def 5: 41 Def 6: 49 |
|||||
Matsuoka (2014) [37] | 64.8 | Lobe | 46 | 49 | 149 | 26 | 48.4% | 85.1% | NR | NR | NR | NR | NR | NR | NR | NR |
Junker (2013) [30] | 53.4 | Patient | ≥10/15: 21 ≥11/15: 28 |
≥10/15: 4 ≥11/15: 12 |
≥10/15: 35 ≥11/15: 27 |
≥10/15: 13 ≥11/15: 6 |
≥10/15: 84% ≥11/15: 70% |
≥10/15: 72.9% ≥11/15: 81.8% |
GS ≥ 4 + 3 | 13.7% | ≥13: 54 | ≥13: 2 | ≥13: 8 | ≥13: 9 | ≥13: 96.4% | ≥13: 47% |
Busetto (2013) [16] | 41.7 | Patient | 59 | 7 | 61 | 36 | 89% | 63% | NR | NR | NR | NR | NR | NR | NR | NR |
Rais-Bahrami (2013) [47] | 54.2 | Patient | ≥2/4 : 80 | ≥2/4: 275 | ≥2/4: 187 | ≥2/4: 275 | ≥2/4: 66% | ≥2/4: 59% | GS ≥ 7: GS ≥ 8 |
31.7% | NR | NR | NR | NR | GS ≥ 7: 91% GS ≥ 8: 91% |
GS ≥ 7: 38% GS ≥ 8: 18% |
≥3/4: 251 | ≥3/4: 76 | ≥3/4: 16 | ≥3/4: 76 | ≥3/4: 51% | ≥3/4: 82% | NR | NR | NR | NR | GS ≥ 7: 75% GS ≥ 8: 91% |
GS ≥ 7: 67% GS ≥ 8: 41% |
|||||
Kuru (2013) [34] | 57.6 | Patient | 80 | 14 | 67 | 186 | 85.1% | 73.5% | NR | NR | NR | NR | NR | NR | NR | NR |
Ferda (2013) [20] | 51.2 | Patient | 52 | 2 | 82 | 28 | 96.3% | 74.5% | NR | NR | NR | NR | NR | NR | NR | NR |
Ganie (2013) [21] | 74.7 | Patient | 13 | 3 | 62 | 9 | 59.1% | 95.4% | NR | NR | NR | NR | NR | NR | NR | NR |
Vinet (2013) [57] | 49.3 | Patient | ≥3/5: 11 | ≥3/5: 6 | ≥3/5: 28 | ≥3/5: 24 | ≥3/5: 64.7% | ≥3/5: 53.8% | NR | NR | NR | NR | NR | NR | NR | NR |
≥4/5: 22 | ≥4/5: 11 | ≥4/5: 23 | ≥4/5: 13 | ≥4/5: 66.7% | ≥4/5: 63.8% | NR | NR | NR | NR | NR | NR | NR | NR | |||
Numao (2013) [38] | 45 | Patient | 137 | 57 | 101 | 56 | 70.6% | 64.3% | Def 1: GS ≥4 + 3 and/or ≥20% positive cores and/or max CCL ≥5 mm Def 2: GS ≥ 3 + 4 and/or ≥20% + cores and/or max CCL ≥5 mm Def 3: GS ≥ 3 + 4 and/or ≥20% + cores |
Def 1: 33.3% Def 2:37.8% Def 3: 35.8% |
Def 1: 74 Def 2: 65 Def 3: 69 |
Def 1: 83 Def 2: 92 Def 3: 88 |
Def 1: 160 Def 2: 153 Def 3: 156 |
Def 1: 34 Def 2: 41 Def 3: 38 |
Def 1: 82.4% Def 2: 78.8% Def 3: 80.4% |
Def 1: 58.8% Def 2: 58.5% Def 3: 56% |
Belas (2012) [14] | 53.5 | Patient | 22 | 12 | 23 | 13 | 64.7% | 63.8% | NR | NR | NR | NR | NR | NR | NR | NR |
Ibrahiem (2012) [26] | 73.9 | Patient | 14 | 11 | 57 | 10 | 56% | 85.1% | NR | NR | NR | NR | NR | NR | NR | NR |
Sciarra (2012) [51] | 34.5 | Patient | 41 | 4 | 25 | 14 | 91.1% | 64.1% | NR | NR | NR | NR | NR | NR | NR | NR |
Portalez (2012) [45] | 48.1 | Lesion | Likert: 357 | Likert: 50 | Likert: 81 | Likert: 50 | Likert: 95% | Likert: 38% | Max CCL >3 mm and/or GG 4/5 | NR | NR | NR | NR | NR | NR | NR |
PI-RADS: 404 | PI-RADS: 47 | PI-RADS: 34 | PI-RADS: 47 | PI-RADS: 95% | PI-RADS: 58% | |||||||||||
Watanabe (2012) [59] | 48.1 | Patient | 485 | 73 | 624 | 266 | 86.9% | 70.1% | NR | NR | NR | NR | NR | NR | NR | NR |
Tamada (2011) [54] | 70 | Patient | 12 | 6 | 29 | 3 | 67% | 91% | NR | NR | NR | NR | NR | NR | NR | NR |
Region | 277 | 48 | 55 | 20 | 85% | 73% | ||||||||||
Choi (2011) [18] | 70.6 | Patient | 9 | 5 | 31 | 6 | 64.2% | 75.7% | NR | NR | NR | NR | NR | NR | NR | NR |
Iwazawa (2011) [28] | 40.5 | Region | 887 | 86 | 232 | 219 | 91.1% | 51.4% | NR | NR | NR | NR | NR | NR | NR | NR |
Rouse (2011) [48] | 33.7 | Sextant | 145 | 11 | 74 | 22 | 92.9% | 77.1% | GS ≥ 7: Def 1: ≥3 mm Def 2: ≥5 mm |
Def 1: 26.6% Def 2: 26.2% |
Def 1: 153 Def 2: 153 |
Def 1: 3 Def 2: 3 |
Def 1: 64 Def 1: 63 |
Def 1: 32 Def 2: 33 |
Def 1: 98.1% Def 2: 98.1% |
Def 1: 68.1% Def 2: 67% |
59.6 | Patient | 24 | 14 | 54 | 22 | 63.2% | 71.1% | Def 1: 41.2% Def 2: 36.8% |
Def 1: 30 Def 2: 31 |
Def 1: 4 Def 2: 3 |
Def 1: 43 Def 2: 39 |
Def 1: 4 Def 2: 3 |
Def 1: 88.2% Def 2: 91.2% |
Def 1: 53.8% Def 2: 48.8% |
||
Haffner (2011) [23] | 54.4 | Patient | 154 | 50 | 240 | 111 | 75.4% | 68.3% | NR | NR | NR | NR | NR | NR | NR | NR |
Panebianco (2010) [40] | 42.7 | Patient | NR | NR | NR | NR | 95.1% | 88.2% | NR | NR | NR | NR | NR | NR | NR | NR |
Roy (2010) [49] | 55.9 | Patient | NR | NR | NR | NR | 71% | 75% | NR | NR | NR | NR | NR | NR | NR | NR |
Testa (2010) [55] | 40.7 | Patient | NR | NR | NR | NR | 79.3% | 64% | NR | NR | NR | NR | NR | NR | NR | NR |
Sciarra (2010) [52] | 50 | Patient | 61 | 4 | 66 | 9 | 93.8% | 88% | NR | NR | NR | NR | NR | NR | NR | NR |
Kitajima (2010) [31] | 56.6 | Patient | 311 | 19 | 80 | 14 | 92.2% | 85.1% | NR | NR | NR | NR | NR | NR | NR | NR |
Labanaris (2010) [35] | 73.9 | Patient | 17 | 73 | 96 | 74 | 81.11% | 56.47% | NR | NR | NR | NR | NR | NR | NR | NR |
Kumar (2009) [32] | 21.7 | Patient | 39 | 3 | 10 | 8 | 92.8% | 55% | NR | NR | NR | NR | NR | NR | NR | NR |
Schmuecking (2009) [50] | NR | Lobe | NR | NR | NR | NR | 96% | 61% | NR | NR | NR | NR | NR | NR | NR | NR |
Cheikh (2009) [17] | 24.7 | Patient | 36 | 12 | 11 | 34 | 80% | 22.9% | NR | NR | NR | NR | NR | NR | NR | NR |
Cirillo (2008) [19] | 31.5 | Patient | 19 | 0 | 17 | 18 | 100% | 48.6% | NR | NR | NR | NR | NR | NR | NR | NR |
Kumar (2007) [33] | 13.3 | Patient | 39 | 0 | 11 | 33 | 100% | 25% | NR | NR | NR | NR | NR | NR | NR | NR |
Squillaci (2005) [53] | 50.8 | Patient | 29% | 8% | 25% | 3% | 89% | 80% | NR | NR | NR | NR | NR | NR | NR | NR |
Hara (2005) [24] | 41.5 | Patient | ≥2/3: 40 = 3/3: 47 |
≥2/3: 4 = 3/3: 8 |
≥2/3 30 = 3/3: 26 |
≥2/3: 8 = 3/3: 1 |
≥2/3: 90% = 3/3: 85% |
≥2/3: 78.9% = 3/3: 96.3% |
NR | NR | NR | NR | NR | NR | NR | NR |
Cancer prevalence tended to be higher and mpMRI NPV lower in the biopsy-naïve group as compared with the repeat biopsy group, in men with positive DRE as compared with men with negative DRE and when an endorectal coil was not used ( Table 3 ). There were no clear differences in the prevalence and NPV of the other analysed subgroups (TRUS-guided vs TTP biopsy, biopsy procedures with ≤16 cores vs >16 cores; Table 3 ). However, comparisons must be interpreted with care, due to the small number of studies in some subgroups. In patients with a PSA level of ≤10 ng/ml, the median NPV for overall PCa was 86.3% (IQR, 73.3–93.6%) for a median cancer prevalence of 35.4% (IQR, 27.6–42.5%).
Nb of studies | Median PCa prevalence | Median mpMRI NPV | Nb of studies | Median csPCa prevalence | Median mpMRI NPV | |
---|---|---|---|---|---|---|
Biopsy-naïve patients | 8 | 51.4% (45.5–56.7) | 69.9% (64.2–78) | 1 | 35.8% (NA) | 80.4% (NA) |
Repeat biopsy | 14 | 42% (35.1–52.6) | 82.6% (75.5–93.1) | 3 | 24.4% (19.1–32.8) | 88.2% (87.9–92.3) |
TRUS-guided biopsy | 36 | 49.7% (34.3–57.7) | 84.6% (68.6–92.8) | 4 | 28.1% (21.7–36.5) | 89.3% (82.9–92.4) |
TTP biopsy | 4 | 53.8% (47.5–57.8) | 73.6% (72–78.7) | 2 | 31.6% (30.5–32.8) | 92% (89.9–94) |
Biopsy with ≤16 cores | 28 | 48.7% (39.2–54.8) | 81.9% (66.8–89.3) | 5 | 28.1% (21.8–36.5) | 89.3% (82.9–92.4) |
Biopsy with >16 cores | 5 | 56.6% (51–61.3) | 81.1% (73.1–92.2) | 2 | 31.7% (30.5–32.8) | 92% (89.9–93.9) |
Positive DRE | 1 | 73.9% (NA) | 56% (NA) | 0 | – | – |
Negative DRE | 6 | 36% (34.6–46.8) | 82.7% (74.2–93.1) | 0 | – | – |
Endorectal coil | 17 | 41.7% (30.6–55.9) | 92.8% (79.3–95.4) | 1 | 31.7% (NA) | 91% (NA) |
No endorectal coil | 22 | 50.9% (41.7–56.1) | 77.7% (69.5–86.6) | 7 | 34% (26.9–46.1%) | 87.9% (78.2–92.1) |
Eight studies reported NPV at patient level for overall PCa and fulfilled the inclusion criteria for meta-analysis ( Table 4 ) [22 25 38 41 43 46 56 57] .
Study | Prevalence a (%) | Neg MRI (%) | NPV (%) | PPV (%) | Spe (%) | Se (%) | ||
---|---|---|---|---|---|---|---|---|
All PCa | Score ≥ 3/5 | Grenabo Bergdahl (2016) [22] | 31.3 | 66.9 | 83.7 | 47.5 | 63.2 | 73.1 |
Numao (2013) [38] | 45 | 29.4 | 70.6 | 64.3 | 71.0 | 63.9 | ||
Hauth (2015) [25] | 45.7 | 14.3 | 85.7 | 48.3 | 11.8 | 97.7 | ||
Vinet (2013) [57] | 49.3 | 24.6 | 64.7 | 53.8 | 31.4 | 82.4 | ||
Radtke (2015) [46] | 51 | 27 | 73 | 73.2 | 71.5 | 74.7 | ||
Thompson (2014) [56] | 61.3 | 31.4 | 68.6 | 76.8 | 60.3 | 82.6 | ||
Pokorny (2014) [43] | 63.7 | 30.9 | 69.1 | 82.4 | 69.1 | 82.4 | ||
Score ≥ 4/5 | Pepe (2015) [41] | 37 | 31 | 74.2 | 42 | 36.5 | 78.4% | |
Vinet (2013) [57] | 49.3 | 47.8 | 66.7 | 63.9 | 62.9 | 67.6% | ||
Radtke (2015) [46] | 51 | 73.5 | 63.9 | 92.3 | 95.8 | 48% | ||
Gleason ≥7 PCa | Score ≥ 3/5 | Radtke (2015) [46] | 29.3 | 27 | 87.9 | 45.1 | 59.6 | 80.2% |
a Prevalence of overall prostate cancers (10 first lines) or Gleason ≥7 cancers (last line).
PCa = prostate cancer; MRI = magnetic resonance imaging; Neg MRI = proportion of negative magnetic resonance imaging; NPV = negative predictive value; PPV = positive predictive value; Se = sensitivity; Spe = specificity.
Seven studies used a score of ≥3/5 for defining positive mpMRI ( Fig. 4 A and B) [22 25 38 43 46 56 57] . Fig. 4 C shows the conditional probability plot of 1 – NPV and PPV as a function of overall PCa prevalence. Table 5 shows NPV and PPV estimates for the given values of PCa prevalence.
PCaPrev | PPV | NPV |
---|---|---|
0.30 | 0.43 (0.34–0.53) | 0.88 (0.77–0.99) |
0.40 | 0.54 (0.45–0.64) | 0.82 (0.70–0.94) |
0.50 | 0.64 (0.55–0.73) | 0.76 (0.64–0.88) |
0.60 | 0.73 (0.65–0.80) | 0.67 (0.56–0.79) |
0.70 | 0.81 (0.75–0.87) | 0.57 (0.47–0.67) |
0.75 | 0.84 (0.79–0.89) | 0.51 (0.42–0.59) |
Only three studies used a score of ≥4/5 for defining positive mpMRI ( Table 4 ) [41 46 57] , and a formal meta-analysis could not be performed.
Only one study reporting NPV at patient level for Gleason ≥7 cancers met the selection criteria for inclusion in the meta-analysis. It reported NPV and PPV of 87.9% and 45.1%, respectively, for a prevalence of 29.3% ( Table 4 ) [46] .
We observed a large variability in reported NPV. Many factors, such as differences in mpMRI protocols, definition of negative mpMRI, or biopsy protocols, can explain this variability. However, two major causes of variability must be pointed out. First, the cancer prevalence was highly variable, ranging at patient level from 13% to 74.7% for overall PCa, and from 13.7% to 50.9% for csPCa. This variability was observed in both the biopsy-naïve and the repeat biopsy setting. As NPV depends on prevalence, this had a major impact on reported NPV ( Fig. 3 ). Second, the definition of csPCa was highly variable from one series to another, and differences of up to 21% could be observed in NPV when different definitions of csPCa were used in the same dataset [12 13 38 47 48] .
To account for clinical heterogeneity and to further explore the clinical relevance of the results, we carefully selected studies for inclusion in the meta-analysis based on stringent criteria. Particularly, we included only studies that: (1) had biopsy protocols with at least 10 cores, since it is no longer recommended to obtain less than 10 cores per biopsy; (2) used DWI, which is the most informative technique, at least for cancers in the peripheral zone [60] ; and (3) reported mpMRI findings using a five-level score, so that negative findings could be better defined. We accepted studies using a subjective (Likert) scale because experienced readers obtained equivalent [45 61 62] or better [63] results with the Likert score than with the PI-RADS v1 score. Owing to the large variations of NPV induced by differences in definitions of csPCa, we did not include different definitions in the meta-analysis since this would have introduced unacceptable clinical heterogeneity in the results, possibly resulting in erroneous and biased estimates. We, therefore, a priori restricted the definition of csPCa to cancers with a Gleason score of ≥7, given the low lethal potential of Gleason 6 cancers [64] and the lack of consensus among pathologists on the best method to measure biopsy core invasion length [65 66] .
In this more homogeneous group of studies, the prevalence range was still large (31.3–63.7%). As a result, we modelled the evolution of NPV (and PPV) as a function of overall PCa prevalence. Unfortunately, we could not duplicate this for csPCa since only one study reporting NPV for Gleason ≥7 cancers met the inclusion criteria for meta-analysis.
We included only studies that reported the results of systematic/standard biopsy in patients with negative mpMRI and used the systematic/standard biopsy as a reference standard. It is well known that TRUS-guided biopsy harbours both random and systematic errors, as evidenced by the high rates of positivity of immediate repeat biopsy after a first series of negative biopsies [67 68] , and as confirmed recently by the PROMIS trial [69] . Therefore, using TRUS-guided biopsy as a reference standard may have overestimated the NPV of mpMRI. However, studies using radical prostatectomy specimens as a reference standard have already reported mpMRI detection rates in relation to PCa Gleason score and volume [1] . In this review, we intended to address the more pragmatic question as to whether a negative mpMRI could predict a negative subsequent biopsy. This is an important question because if the NPV of mpMRI was sufficiently high in comparison with the reference standard of systematic/standard biopsies, then in practice a negative mpMRI result could indeed avoid the need for prostate biopsy. Therefore, studies reporting only biopsy results when the mpMRI was positive (eg, obtained through MRI-targeted, guided, or fusion biopsies with added systematic biopsies) were not included in this review.
It is now well established that mpMRI is a sensitive tool for detecting aggressive PCa 1 2 3 69] . However several reasons preclude its broad use as a triage test before biopsy.
Firstly, the population referred to prostate biopsy is not standardised. The large range of reported prevalence for overall PCa and csPCa suggests substantial heterogeneity in the way patients are selected for biopsy. Owing to this heterogeneity, we did not provide a pooled estimate for mpMRI NPV. The role of mpMRI as a triage test before prostate biopsy should be evaluated in the broader context of the selection of patients with a suspicion of (aggressive) PCa. In a recent retrospective study of 514 patients, mpMRI NPV for Gleason ≥7 cancers was 91% when the PSA density was ≤0.2 ng/ml/ml, and only 71% when the PSA density was >0.2 ng/ml/ml ( p = 0.003) [70] . In another series of 288 biopsy-naïve patients, no csPCa (Gleason score ≥7 or maximum cancer core length ≥4 mm) was found in 44 patients with a PSA density of <0.15 ng/ml/ml and a PI-RADS v2 score of <3/5 [71] . We believe that such prestratification of the risk of csPCa is an interesting way for rationalising the use of mpMRI before biopsy. Patients found at very low risk would be spared both mpMRI and biopsy. Patients at a low risk—for whom mpMRI would have an NPV high enough to be used as a triage test—could avoid biopsy in case of negative mpMRI. Patients at a higher risk would need biopsy even in case of negative mpMRI. Many tools can be used to risk stratify the population of patients referred to biopsy, ranging from simple parameters such as PSA density to more complicated risk calculators [72 73] . The impact of these tools on the NPV of prebiopsy mpMRI needs to be carefully evaluated, both in the biopsy-naïve and in the repeat biopsy setting. For the moment, it is impossible to make any recommendations on the best way to risk stratify patients before referring them for mpMRI.
Secondly, the large variability in the definition of csPCa precludes any definitive conclusion on the ability of mpMRI to rule out aggressive cancer. The issue of the most appropriate definition of csPCa on biopsy is complex, since biopsy results may accurately reflect neither tumour burden nor aggressiveness. Nonetheless, there is an urgent need to standardise the histological definition(s) of csPCa, to allow meaningful comparisons between studies.
Thirdly, the specificity of mpMRI remains moderate, and there is a substantial proportion of false positives in the lesions scored 3/5 or 4/5 [1 74 75] , even with the new PI-RADS v2 score [76] . In a series of 62 patients with 116 lesions biopsied under magnetic resonance/ultrasound fusion, the overall cancer detection rates for PI-RADS v2 scores of 3/5 and 4/5 were only 15.8% and 29.8%, respectively [77] . In theory, a triage test used to rule out a disease needs to be highly sensitive for this disease. However, if its specificity is too low, it will be clinically useless since most patients will be positive, whether they have the disease or not. Therefore, if mpMRI is to be used as a triage test in the future, there is a need to improve its specificity. This could be achieved by a continuous refinement of scores [78] . Promising results in characterising csPCa have also been reported with a quantitative analysis [79] .
Finally, all published studies were conducted in specialised centres. The broad use of mpMRI as a triage test assumes good interobserver reproducibility. Unfortunately, interobserver reproducibility of existing scoring systems remains moderate [62 63 80] even with the use of the PI-RADS v2 score [80 81] . Studies evaluating on a large scale the reproducibility of mpMRI findings between expert and nonexpert centres are currently lacking.
Three systematic reviews (including two meta-analyses) regarding the role of mpMRI in localised PCa have been published recently 4 5 6 . Crucially, all three reviews focused exclusively on the sensitivity of mpMRI-targeted, guided, or fusion biopsies in diagnosing overall PCa and csPCa, using TRUS-guided prostate biopsies as reference standards. The impact of systematic biopsies on the outcome was not addressed in any of the reviews, within either the index test or the reference standard. Our review had a totally different research question and objective, focusing on NPV of mpMRI to see if a negative mpMRI can avoid the need for a prostate biopsy. As MRI-targeted/guided/fusion biopsies are not relevant if the mpMRI was negative for cancer, it can be argued that the three reviews assessed a different index test altogether. As such, we believe that the findings of this review are novel and unique, and pave the way for further focused clinical studies.
The current study represents the first systematic review addressing the role of mpMRI as a triage test before biopsy. The review elements were developed in conjunction with a multidisciplinary panel of experts (EAU Prostate Cancer Guidelines Panel), which included a patient representative, and the review was performed robustly in accordance with recognised standards. However, it is limited by the major heterogeneity of the existing literature in patient population, study design, and definitions of positive mpMRI and csPCa. It highlighted further areas of research that could help in defining the best use of mpMRI in the early detection of aggressive PCa in the future.
Although mpMRI can detect aggressive PCa with excellent sensitivity, a definitive conclusion on its role as a triage test before prostate biopsy will be possible only when three main issues are addressed. Firstly, because NPV depends on prevalence, and because overall PCa and csPCa prevalence was highly variable in the published series, it becomes mandatory to define the optimal way to pre-evaluate the risk of csPCa in patients with a suspicion of PCa. Depending on the risk category, mpMRI could then be used to obviate biopsies or not. Secondly, there is a need for consensus definitions of csPCa on biopsy findings to allow interstudy comparisons. Thirdly, although efforts have been made to standardise mpMRI technical protocols and interpretation in the past few years [11 60 76] , there is still a crucial need to improve mpMRI specificity and inter-reader reproducibility.
This systematic review was performed under the auspices of:
The European Association of Urology Guidelines Office Board
The European Association of Urology Prostate Cancer Guideline Panel
Author contributions: Olivier Rouvière had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.
Study concept and design: Rouvière, Mottet, Cornford.
Acquisition of data: Rouvière, Moldovan, Van den Broeck, Yuan.
Analysis and interpretation of data: Rouvière, Moldovan, Van den Broeck, Lam.
Drafting of the manuscript: Rouvière, Moldovan, Van den Broeck, Lam.
Critical revision of the manuscript for important intellectual content: Bellmunt, van den Bergh, Bolla, Briers, Van den Broeck, Cornford, Cumberbatch, De Santis, Fossati, Gross, Henry, Joniau, Lam, Matveev, Moldovan, van der Poel, van der Kwast, Rouvière, Schoots, Wiegel, Mottet.
Statistical analysis: None.
Obtaining funding: None.
Administrative, technical, or material support: Yuan, Sylvester, Marconi.
Supervision: None.
Other: None.
Financial disclosures: Olivier Rouvière certifies that all conflicts of interest, including specific financial interests and relationships and affiliations relevant to the subject matter or materials discussed in the manuscript (eg, employment/affiliation, grants or funding, consultancies, honoraria, stock ownership or options, expert testimony, royalties, or patents filed, received, or pending), are the following: Bellmunt is a company consultant for Janssen, Astellas, Pierre Fabre, Genentech, Merck, Ipsen, Pfizer, Novartis, and Sanofi Aventis. He has received research support from Takeda, Novartis, and Sanofi, and received travel grants from Pfizer and Pierre Fabre. Bolla has received company speaker honoraria from Ipsen and Astellas, honoraria or consultation fees from Janssen, and fellowship and travel grants from Janssen, AstraZeneca, and Astellas. Briers has received grant and research support from Ipsen, European Association of Urology, and Bayer; is an ex officio board member for Europa UOMO; is an ethics committee and advisory group member for REQUITE; is a member patient advisory board member for PAGMI; and is a member of SCA and EMA PCWP. Cornford is a company consultant for Astellas, Ipsen, and Ferring. He receives company speaker honoraria from Astellas, Janssen, Ipsen, and Pfizer; participates in trials from Ferring; and receives fellowships and travel grants from Astellas and Janssen. De Santis is a company consultant for GlaxoSmithKline, Janssen, Bayer, Novartis, Pierre Fabre, Astellas, Amgen, Eisai Inc., ESSA, Merck, and Synthon; has received company speaker honoraria from Pfizer, Takeda, Sanofi Aventis, Shionogi, Celgene, and Teva OncoGenex; has participated in trials for Pierre Fabre, Astellas, Exelixis, Bayer, and Roche; has received fellowship and travel grants from Bayer, Novartis, Ferring, Astellas, Sanofi Aventis, and Janssen; has received grant and research support from Pierre Fabre; has received honoraria from AstraZeneca; and is associated with Amgen. Joniau is a company consultant for Astellas, Ipsen, Bayer, Sanofi, and Janssen; has received company speaker honoraria from Astellas, Amgen, Bayer, Sanofi, Janssen, and Ipsen; has participated in trials for Astellas, Janssen, and Bayer; has received fellowship and travel grants from Astellas, Amgen, Bayer, Sanofi, Janssen, Ipsen, and Pfizer; and has received grant and research support from Astellas, Bayer, and Janssen. Matveev has received company speaker honoraria from Sanofi and Astellas, has participated in trials for Astellas, Pfizer and Novartis. Lam is a company consultant for and has received company speaker honoraria from Pfizer, GSK, Astellas, and Ipsen. van der Poel is a company consultant for Intuitive Surgical, has participated in trials for Astellas and Steba Biotech, and has received grant and research support from Astellas. Rouvière is a company consultant for EDAP-TMS, Bracco, and Philips; has received company speaker honoraria from EDAP-TMS, Bracco, and Philips; and has participated in trials for EDAP-TMS and Bracco. Wiegel has received company speaker honoraria from Astellas, Takeda, Hexal, Ipsen, Janssen-Cilac, and Ferring. Mottet has received grant and research support from Takeda Pharmaceutical, Millenium, Astellas, Pierre Fabre, Sanofi, and Pasteur, and has received honoraria or consultation fees from Takeda Pharaceutical, Millenium, Jansen, Astellas, BMS, Bayer, Ipsen, Ferring, Novartis, Nuclétron, Pierre Fabre, Sanofi, and Zeneca. van den Bergh, Van den Broeck, Cumberbatch, Fossati, Gross, Henry, van der Kwast, Sylvester, Yuan, Schoots, Moldovan, and Marconi have nothing to disclose.
Funding/Support and role of the sponsor: None.
A correlation with radical prostatectomy specimens has demonstrated that multiparametric magnetic resonance imaging (mpMRI) has excellent sensitivity in detecting prostate cancer (PCa) with a Gleason score of ≥7 1 2 3 . As a result, prostate mpMRI is increasingly used in patients with a suspicion of PCa to localise abnormal areas before biopsy. A large body of literature has shown that targeted biopsies of suspicious lesions seen on mpMRI (TBx) improved the detection of clinically significant PCa (csPCa), at least in the repeat biopsy setting 4 5 6 . As a result, it is now recommended that an mpMRI is performed before repeat biopsy to allow TBx of suspicious lesions in addition to standard biopsies [7] .
Some authors have recently suggested that, besides improving csPCa detection, mpMRI could also be used as a triage test so that patients with negative mpMRI findings could obviate biopsy. Such a strategy remains highly controversial [8] and depends upon the negative predictive value (NPV) of mpMRI. Therefore, the European Association of Urology Prostate Cancer Guidelines Panel undertook this systematic review and meta-analysis to assess the NPV of mpMRI in patients with a suspicion of PCa and, thus, its potential role in eliminating unnecessary prostate biopsy.
Our primary aim was to systematically evaluate the performance of negative prebiopsy prostate mpMRI in predicting a negative biopsy result for overall PCa and csPCa in biopsy-naïve men and in men with previously negative biopsies. A further objective was to explore and define factors that may contribute to relevant thresholds in order to provide guidance for future studies.
The review was performed according to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) statement [9] . The review protocol was published in PROSPERO database ( http://www.crd.york.ac.uk/PROSPERO; registration number CRD42015021929). Databases searched included the Embase and OVID Medline databases, the Cochrane database of systematic reviews, and the Cochrane Central Register for Clinical Trials, covering from January 1, 2000 to February 13, 2016. Systematic or standard prostate biopsies were used as reference standards, with positive or negative cases of PCa being determined by histopathological examination. The detailed search strategy is presented in Supplement 1.
Included studies focused on men who were assessed for suspected PCa by mpMRI before undergoing prostate biopsy. Studies enrolling both biopsy-naïve men and men who had undergone previous negative biopsies were included. Prebiopsy prostate mpMRI was considered the index test and comprised T2-weighted imaging (T2WI) and at least one functional imaging technique (diffusion-weighted imaging [DWI], dynamic contrast-enhanced imaging [DCEI], or magnetic resonance spectroscopic imaging [MRSI]). For inclusion, studies had to report on false negatives and true negatives, in order to calculate NPV (ie, results of systematic/standard prostate biopsies when the mpMRI was negative). When available, false positive and true positive findings were also noted to calculate the positive predictive value (PPV) and the cancer prevalence. There was restriction neither on the biopsy technique (transrectal or transperineal) nor on the number of biopsy cores. Studies using radical prostatectomy specimens as reference standards were excluded, as were studies evaluating men with histologically proven PCa. Studies with less than 50 participants were excluded. No language restrictions were applied.
Two reviewers (P.C.M. and T.V.D.B.) independently screened all abstracts and full-text articles for eligibility. Disagreement was resolved by consensus or reference to an independent third party (L.M.). All screening was performed using a predefined eligibility form.
Using a data extraction form developed a priori, the same two reviewers independently extracted data concerning study methodology, patient characteristics, technical characteristics of the MR scanners, mpMRI protocol, mpMRI scoring system, definition of positive mpMRI, biopsy protocol, and definition of csPCa. Any discrepancies concerning data extraction were resolved by consensus or reference to an independent arbiter (O.R. or T.B.L.).
To assess the risk of bias (RoB), all included reports were reviewed using the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool for diagnostic accuracy studies [10] .
Outcome data regarding false negative and true negative values of mpMRI before prostate biopsy were recorded as reported by authors. When not available, data were indirectly derived from specificity, sensitivity, and prevalence values reported by authors using an online Bayesian statistics calculator ( http://www.medcalc.com/bayes.html ). Descriptive statistics were used to summarise baseline characteristics and outcomes, including median and interquartile range (IQR) for estimates of NPV across studies. A correlation between mpMRI NPV and a positive biopsy rate was established using the Pearson's correlation coefficient.
A meta-analysis was undertaken to calculate pooled NPV and PPV. To ensure appropriate clinical homogeneity of the studies included in the meta-analysis, we selected only the studies enrolling biopsy-naïve patients and/or patients with a history of negative biopsy, and fulfilling the following criteria that were defined a priori: (1) reference standard consisting of prostate biopsy with at least 10 samples on all patients; (2) mpMRI protocol comprising at least T2WI and DWI; (3) mpMRI results presented as a five-level score, using a subjective Likert scale or the Prostate Imaging Reporting Data System (PI-RADS) score [11] ; (4) definition of positive mpMRI as a score ≥3/5 or ≥4/5; and (5) results reported on a per patient basis. In addition, only studies defining csPCa as Gleason ≥7 cancers were selected for the meta-analysis assessing the mpMRI NPV for csPCa. A bivariate random-effects approach was employed using the Midas package in Stata 12 (StataCorp LP, College Station, TX, USA). Since the NPV decreases and the PPV increases as the prevalence increases, post-test probability estimates of NPV and PPV were reported for the given values of the prevalence based on Bayes’ theorem.
For other studies not included in the meta-analysis based on the criteria described above, a narrative synthesis of the data was performed. To explore and define clinical heterogeneity, subgroups were analysed at patient level based on the following variables: biopsy-naïve versus previous negative biopsy; patients with positive versus negative digital rectal examination (DRE); mpMRI performed with an endorectal versus without an endorectal coil; transrectal ultrasound (TRUS) versus template transperineal (TTP) biopsy approach; and ≤16 cores versus >16 cores as the reference standard. Studies reporting mpMRI NPV for patients with a prostate-specific antigen (PSA) level of ≤10 ng/ml were also reported separately.
The study selection process is depicted in the PRISMA flow diagram ( Fig. 1 ). A total of 2980 abstracts were retrieved. After abstract screening and removal of duplicates, 240 articles were eligible for full text screening, of which 48 studies were eligible for inclusion 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 .
Out of the 48 included studies, 42 were single-centre and six were multicentre studies. Thirty-four studies were prospective and six were retrospective, whilst the design of the rest was unclear. RoB assessment using QUADAS-2 was performed for each of the individual studies ( Fig. 2 A and B). Overall, the RoB was highly heterogeneous across studies for all criteria, except for the reference standard domain, in which RoB was low in most studies.
The 48 studies comprised a total of 9613 men who underwent prostate mpMRI followed by biopsy. The study and patient baseline characteristics are presented in Table 1 . The patient population consisted of biopsy-naive men in nine studies, men with at least one previous negative biopsy in 16 studies, and both biopsy-naïve men and men with a history of previous negative biopsy in nine studies. In 14 studies, the biopsy history of the patients was unclear.
Study | Study design | Period | Population | Pt Nb | Mean/median* age (yr) | Mean/median* PSA (ng/ml) | Mean/median* prostate volume (cm 3 ) | Magnetic field strength | MR pulse sequences | Endorectal coil | MR score | Definition of positive MRI | Reference standard |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Hauth (2015) [25] | Prospective | 2011–2013 | FB | 94 | 64 (43–83) | 9 (3–31) | 51 (17–140) | 1.5 T | T2WI/DWI/DCEI/MRSI | No | PI-RADS v1 | ≥3 | 11–13-core TRUS SBx + TBx |
Lamb (2015) [36] | Retrospective | 2013–2013 | FB & PNB | 173 | NR | NR | NR | 1.5 T | T2WI/DWI | NR | NR | NR | 12-core TRUS SBx |
Brock (2015) [15] | Prospective | 2013–2014 | PNB | 168 | 64* (IQR 59–70) | 9.2* (IQR 6.7–13.4) | 55.4* (IQR 42–80) | 3 T | T2WI/DWI/DCEI | No | PI-RADS v1 | NR | 12/24-core TRUS SBx + TBx |
Grenabo Bergdahl (2016) [22] | Prospective | 2013–2014 | FB & PNB | 83 | 69.3* (IQR 69–69.6) | 1.6* (IQR 0.9–2.7) | NR | 3 T | T2WI/DWI/DCEI/MRSI | No | PI-RADS v1 | ≥3 | 10-core TRUS SBx + TBx |
Wang (2015) [58] | Prospective | 2002–2009 | FB & PNB | 586 | 70 (26–91) | 11.11* (0.02–9794) | NR | 1.5 T | T2WI/DWI/DCEI/MRSI | Yes | PI-RADS v1 | ≥3 | TRUS SBx |
Pepe (2015) [41] | Prospective | 2011–2014 | PNB | 100 | 64* | 8.6* (4.2–10) | NR | 3 T | T2WI/DWI/DCEI/MRSI | No | PI-RADS v1 | ≥4 | TPBx + TBx |
Panebianco (2015) [39] | Prospective | 2011–2014 | FB (61.62%) & PNB (38.34%) | 925 (1140 total cohort) |
NR | NR | NR | 3 T | T2WI/DWI/DCEI | Yes | PI-RADS v1 | NR | 14-core TRUS SBx; 45-core sat TPBx + TBx |
Radtke (2015) [46] | Prospective | 2013–2013 | FB (63.3%) & PNB (36.7%) | 294 | 64* (60–71) | 7.3 (6.0) | 47 (37.5) | 3 T | T2WI/DWI/DCEI | No | PI-RADS v1 | PI-RADS ≥2; PI-RADS ≥3; PI-RADS ≥4; PI-RADS = 5; |
24-core TPBx + TBx |
Itatani (2014) [27] | Retrospective | 2004–2007 | NR | 193 | 68.9 (8.4); 70* (47–89) | 11.8 (15.9); 7.9* (1.22–159) | NR | 1.5 T | T2WI/DWI/DCEI | No | 1–5 scale (Likert) | ≥3 | 12–14-core TRUS SBx |
Porpiglia (2014) [44] | Prospective | 2011–2013 | PNB | 170 | 65* (60–70) | 6.9* (5.2–9.8) | 42* (36–48) | 1.5 T | T2WI/DWI/DCEI | Yes | Dichotomous | Positive: at least 2/3 MR seq. with suspicious findings | 18–24-core TRUS SBx (volume dependent) |
Thompson (2014) [56] | Prospective | 2012–2013 | FB (88%) & PNB (12%) | 150 | 62.4* (IQR 55.0–66.4) | 5.6* (IQR 4.5–7.5) | 40* (IQR 30–57) | 1.5 T (47%) & 3 T (53%) | T2WI/DWI/DCEI | No | PI-RADS v1 | ≥3 | Median of 30 TPBx (volume dependent) |
Pokorny (2014) [43] | Prospective | 2012–2013 | FB | 223 | 63* (IQR 57–68) | 5.3* (IQR 4.1–6.6) | 41* (IQR 30–59) | 3 T | T2WI/DWI/DCEI | No | PI-RADS v1 | ≥3 (primary); ≥4 |
12-core TRUS SBx + TBx |
Petrillo (2014) [42] | Prospective | 2009–2010 | NR | 136 | NR | NR | NR | 1.5 T | T2WI/DWI/MRSI | Yes | 1–5 scale (Likert) | ≥3 | 12–16-core TRUS SBx (volume + PSA dependent) |
Javali (2014) [29] | Retrospective | 2002–2011 | NR | 140 | Control: 62.4 (10.5); Study: 62.9 (12.1) | Control: 6.8 (2.3); Study: 6.87 (2.6) | Control: 44 (14.2); Study: 43 (18.4) | 1.5 T | T2WI/MRSI | Yes | Dichotomous | Cit/[Cho + Cr] < 1.2 | 6-core TRUS SBx ( n = 69), 12-core TRUS SBx ( n = 119) |
Abd-Alazeez (2014) [13] | Prospective | 2007–2011 | FB | 129 | 62* (41–82) | 5.8* (1.2–20) | 40* (16–137) | 1.5 & 3 T | T2WI/DWI/DCEI | No | PI-RADS v1 | ≥3 (primary); ≥4 |
20-core TPBx |
Abd-Alazeez (2014) [12] | Retrospective | NR | PNB | 54 | 64* (39–75) | 10* (2–23) | 53* (19–136) | 1.5 & 3 T | T2WI/DWI/DCEI | No | PI-RADS v1 | ≥3 (primary); ≥4 |
≥20-core TPBx + TBx ( n = 15) |
Matsuoka (2014) [37] | Prospective | 2007–2012 | NR | 135 | 67* (50–80) | 7.0* (2.9–19.8) | 25.4* (12.7–90.2) | 1.5 T | T2WI/DWI | No | 1–5 scale (Likert) | ≥3 | 14-core TRUS SBX |
Junker (2013) [30] | Retrospective | 2011–2013 | PNB | 73 | 62 (7.4) | 7.0* (5.1–12.9) | 45* (34–61) | 3 T | T2WI/DWI/DCEI | No | PI-RADS | PI-RADS ≥10 and ≥11 for all PCa PI-RADS ≥13 for significant PCa |
10-core TRUS SBx + TBx |
Busetto (2013) [16] | Prospective | 2010–2012 | PNB | 163 | 66.4 (5.3) | 6.8 (1.6) | NR | 3 T | T2WI/DWI/DCEI/MRSI | Yes | NR | NR | 10-core TRUS SBx + TBx |
Rais-Bahrami (2013) [47] | Prospective | 2007–2012 | NR | 583 | 61.3 (8.4) | 9.9 (13.1) | NR | 3 T | T2WI/DWI/DCEI/MRSI | Yes | 1–4 scale (Likert) | ≥2 ≥3 |
12-core TRUS SBx + TBx |
Kuru (2013) [34] | Prospective | 2010–2011 | FB (51%) & PNB (49%) | 347 | 65.3 (42–82) | 9.85 (0.5–104) | 48.7 (9–180) | 3 T | T2WI/DWI/DCEI | No | 1–3 scale (Likert) | ≥2 | 12–36-core TRUS SBx (volume dependent) + TBx |
Ferda (2013) [20] | Prospective | NR | NR | 164 | (49–74) | (4.2–123) | NR | 3 T | T2WI/DWI/DCEI/MRSI | No | NR | In house | TRUS SBx |
Ganie (2013) [21] | NR | 2007–2009 | PNB | 87 | NR | NR | NR | 1.5 T | T2WI/MRSI | Yes | MRSI Cho/Cit ratio | In house | 6 core TRUS SBx + MRI TBx |
Vinet (2013) [57] | Prospective | 2009–2011 | FB | 69 | NR | 5.2* (3.2–28) | NR | 1.5 T (35 pts) & 3 T (34 pts) | T2WI/DWI/DCEI | No | 1–5 scale (Likert) | ≥3 | 12-core TRUS SBx + TBx |
Numao (2013) [38] | Prospective | 2006–2010 | FB | 351 | 65* (59–70) | 6.3* (4.9–9.1) | 32* (24–42) | 1.5 T | T2WI/DWI/DCEI (no DCEI in 42 pts) | No | 1–5 scale (Likert) | ≥3 | 3D 26-core (12 TRUS SBx + 14 TPBx – 203 pts); 3D 14-core (6 TRUS SBx + 8 TPBx – 102 pts); TPBx 14 core (46 pts) |
Belas (2012) [14] | Prospective | 2010–2011 | FB | 71 | 66* (47–76) | 7* (4–10) | 45* (15–150) | 1.5 T | T2WI/DWI/DCEI | No | TZ: 0–4 scale PZ: 0–10 scale |
TZ: >2 PZ: >6 |
12-core TRUS SBx + TBx |
Ibrahiem (2012) [26] | Prospective | 2008–2009 | FB | 100 | 65.03 (7.13) | 26.3 (24.2) | 60.09 (28.7) | 1.5 T | T2WI/DWI | No | NR | In house | 12-core TRUS SBX |
Sciarra (2012) [51] | Prospective | 2008–2011 | PNB | 84 | 64.09 (46–76) | 7.07 (4.2–15.5) | NR | 3 T | T2WI/DWI/DCEI/MRSI | Yes | NR | NR | 10-core TRUS Bx + TBx |
Portalez (2012) [45] | Prospective | 2011 | PNB | 129 | 64.7 (47–79) | 9.6 (2.7–40) | 51.1 (12–192) | 1.5 T | T2WI/DWI/DCEI | Mixed | 1–5 scale (Likert) PI-RADS |
Likert ≥3 PI-RADS ≥9 |
10–12-core TRUS SBx + TBx |
Watanabe (2012) [59] | Prospective | 2004–2008 | NR | 1448 | 72 (7.5) | NR | NR | 1.5 T | T2WI/DWI | No | NR | ADC value ≤1.35 × 10 −3 mm 2 /s | 8-core TRUS SBx + TBx |
Tamada (2011) [54] | Retrospective | 2006–2009 | NR | 50 | 70 (40–84) | 6.84* (4.06–9.94) | NR | 1.5 T | T2WI/DWI/DCEI | No | NR | In house | 12-core TRUS SBx |
Choi (2011) [18] | NR | 2009–2010 | NR | 51 | 67.16 (56–90) | 14.16 (1.02–38.9) | 42.98 (13.8–77.3) | 3 T | T2WI/DWI | NR | NR | NR | 10–12-core TRUS SBx + TBx |
Iwazawa (2011) [28] | Retrospective | 2008–2009 | NR | 178 | 68.8 (41–86) | 20.51 (4.04–568.5) | NR | 1.5 T | T2WI/DWI/DCEI | NR | 1–4 scale (Likert) | NR | 10–12-core TRUS SBx (TBx included in SBx chart) |
Rouse (2011) [48] | Prospective | 2005–2007 | PNB | 114 | 63.6 (41–83) | 13.4 (0–228) | NR | 1.5 T | T2WI/DWI/DCEI | NR | 1–5 scale (Likert) | ≥3 | TRUS SBx |
Haffner (2011) [23] | Prospective | 2005–2009 | FB | 555 | 64* (47–83) | 6.75* (0.18–100) | 46* (15–200) | 1.5 T | T2WI/DCEI | No | 1–5 scale (Likert) | ≥3 | 10-core TRUS SBx + TBx |
Panebianco (2010) [40] | Prospective | 2007–2009 | PNB | 150 | 61.2 (46–78) | 9.42 (3.91) | 41.17 (7.47) | 1.5 T | T2WI/DCEI/MRSI | Yes | NR | In house | 10-core TRUS SBx (TBx included in SBx chart) |
Roy (2010) [49] | Not specified | 2011–2009 | FB (53%) & PNB (47%) | 103 | 63 (52–78) | 7* | NR | 3 T | T2WI/DWI/DCEI | Yes | NR | NR | 8-core TRUS SBx + TBx |
Testa (2010) [55] | Not specified | 2007 | PNB | 54 | 63.9 (52–76) | 11.4 (3–42) | 59.3 (30–150) | 1.5 T | T2WI/MRSI | Yes | 1–3 scale (Likert) | ≥2 | 12-core TRUS SBx + TBx |
Sciarra (2010) [52] | Prospective | 2007–2009 | PNB | 110 | 63.5 (49–74) | NR | NR | 1.5 T | T2WI/DCEI/MRSI | Yes | NR | In house | 10-core TRUS SBx + TBx |
Kitajima (2010) [31] | Prospective | 2008–2009 | NR | 53 | 69* (56–84) | 11.1* (4.2–112.1) | NR | 3 T | T2WI/DWI/DCEI | No | 1–5 scale (Likert) | ≥3 | 20-core TPBx |
Labanaris (2010) [35] | Prospective | 2004–2008 | PNB | 260 | NR | NR | NR | 1 T | T2WI/DWI/DCEI | Yes | Dichotomous | In house | 18-core TRUS SBx |
Kumar (2009) [32] | NR | NR | NR | 61 | 65.3 (9.3) | 16.5 (0.21–155) | NR | 1.5 T | T2WI/MRSI | Yes | NR | (Cit/(Cho + Cr) ≤ 1.2 | TRUS Bx |
Schmuecking (2009) [50] | NR | NR | FB & PNB | 67 | 68 | 11.5 | NR | 1.5 T | T2WI/DCEI | No | NR | NR | 20-core Bx |
Cheikh (2009) [17] | Retrospective | 2005–2008 | PNB | 93 | 63.2 (52–74) | 9.63 (1.6–40) | NR | 1.5 T | T2WI/DCEI | No | Dichotomous | In house | 12-core TRUS SBx + TBx |
Cirillo (2008) [19] | Prospective | 2004–2006 | PNB | 54 | 65.5 (5.2) | 10.8 (7.5) | NR | 1.5 T | T2WI/MRSI | Yes | Dichotomous | In house | 10-core TRUS SBx + TBx |
Kumar (2007) [33] | Prospective | 2003–2005 | NR | 83 | NR | NR | NR | 1.5 T | T2WI/MRSI | Yes | NR | NR | 12-core TRUS SBx + TBx |
Squillaci (2005) [53] | Prospective | 2004–2005 | NR | 65 | NR | NR | NR | 1.5 T | T2WI/DCEI/MRSI | No | 1–3 scale (Likert) | ≥2 | 10-core TRUS SBx + TBx |
Hara (2005) [24] | Prospective | 2003–2004 | FB | 90 | 67.2 (NR) | NR | NR | 1.5 T | T2WI/DCEI | No | 1–3 scale (Likert) | ≥2 = 3 |
14-core TRUS SBx |
The magnetic field strength was 1, 1.5, and 3 T in one, 28, and 15 studies, respectively. Four studies used both 1.5 and 3 T MR systems. DWI and DCEI were used in 36 and 35 studies, respectively. Nineteen studies also added MRSI. An endorectal coil was used in 18 studies. The definition of positive mpMRI varied across studies. The PI-RADS v1 score was used in 12 studies, a five-level subjective (Likert) score was used in eight studies, and one study reported data based on the two scoring systems. In-house criteria were used in 13 studies for defining positive mpMRI, and five studies used a dichotomous definition. Nine studies did not report on the criteria for positive mpMRI. No study used the PI-RADS v2 score.
Regarding the reference standard, TRUS-guided biopsies were used in 39 studies, TTP biopsies in six studies, and mixed TRUS-guided and TTP biopsies in two studies. In one study, the biopsy approach was unclear. The number of cores per biopsy procedure was ≤16 in 30 studies, >16 in nine studies, and variable among patients in three studies. For six studies, the number of biopsy cores taken was unclear.
At patient level, the median biopsy positivity rate (ie, cancer prevalence) was 50.4% (IQR, 36.4–57.7%) for overall cancer and 32.9% (IQR, 28.1–37.2%) for csPCa ( Table 2 ). The median mpMRI NPV was 82.4% (IQR, 69.0–92.4%) for overall cancer and 88.1% (IQR, 85.7–92.3) for csPCa. NPV significantly decreased when cancer prevalence increased, both for overall cancer ( r = –0.64, p < 0.0001) and csPCa ( r = –0.75, p = 0.032; Fig. 3 ). In addition, NPV was highly dependent on the definition used for csPCa, with differences of up to 21% when several definitions were used in the same dataset [12 13 38 47 48] .
Study | Overall PCa prevalence (%) | Reporting level | Multiparametric MRI performance for PCa detection | Definition of csPCa | csPCa prevalence | Multiparametric MRI performance for csPCa detection | ||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
TN | FN | TP | FP | NPV | PPV | TN | FN | TP | FP | NPV | PPV | |||||
Hauth (2015) [25] | 45.7 | Patient | 6 | 1 | 42 | 45 | 85.7% | 48.3% | Low grade: GS ≤ 6 High grade: GS ≥ 7 |
NR | NR | NR | NR | NR | NR | NR |
Lesion | 59 | 13 | 55 | 73 | 81.9% | 43% | ||||||||||
Lamb (2015) [36] | 65.9 | Patient | 23 | 22 | 92 | 36 | 51.1% | 71.9% | GS ≥ 7 | 50.9% | 31 | 14 | 71 | 57 | 68.9% | 55.5% |
Brock (2015) [15] | 42.3 | Patient | 17 | 7 | 56 | 88 | 70.8% | SBx: 38.8% TBx: 22.2% Duo: 44.4% |
Epstein: GS > 6 and/or max CCL ≥50% | 24.4% | SBx: 21 | SBx: 3 | SBx: 38 TBx: 27 duo: 47 |
SBx: 106 TBx: 117 duo: 97 |
87.5% | SBx: 26.4% TBx: 18.8% duo: 32.6% |
Grenabo Bergdahl (2016) [22] | 33.7 | Patient | 36 | 7 | 19 | 21 | 83.7% | 47.5% | Clinically insignificant PCa: T1c, PSAd < 0.15, GS < 7, ≤2 positive cores, and unilateral cancer | NR | NR | NR | NR | NR | NR | NR |
Wang (2015) [58] | 58 | Patient | 165 | 8 | 332 | 81 | 95.4% | 80.4% | NR | NR | NR | NR | NR | NR | NR | NR |
Pepe (2015) [41] | 37 | Patient | 23 | 8 | 29 | 40 | 74.2% | 42% | GS ≥ 7 or GS 6 with CCL ≥ 50% | NR | NR | NR | NR | NR | 100% | 55.8% |
Panebianco (2015) [39] | 74.7 | Patient | Group A (satBx): 104 | Group A (satBx): 43 | Group A: 186 | Group A: 22 | Group A (satBx): 70.7% | Group A: 89.4% | NR | 60% | Group A: 147 | Group A: 0 | Group A: 183 | Group A: 25 | Group A: 100% | Group A: 88% |
Group B (TRUSGB NR TRUS G satBx): 93 | Group B (TRUSGB NR TRUS G satBx): 37 | Group B: 417 before and 425 after satBx | Group B: 23/440 and 15/440 after satBx. | Group B (TRUSGB–TRUS G satBx): 71.5% | Group B: 94.8% before and 96.6% after satBx | 71.9% | Group B: 130 | Group B: 0 | Group B: 410 |
Group B: 30 | Group B: 100% | Group B: 93.2% | ||||
Radtke (2015) [46] | 51 | Patient | ≥2/5: 80 ≥3: 103 ≥4: 138 = 5: 142 |
≥2/5: 18 ≥3/5: 38 ≥4/5: 78 = 5/5: 126 |
≥2/5: 132 ≥3/5: 112 ≥4/5: 72 = 5/5: 24 |
≥2/5: 64 ≥3/5: 41 ≥4/5: 6 = 5/5: 2 |
≥2/5: 81.6% ≥ 3/5: 73.1% ≥ 4/5: 63.9% = 5/5: 53% |
≥2/5: 67.4% ≥ 3/5: 73.2% ≥ 4/5: 92.3% = 5/5: 92.3% |
GS ≥ 7 | 29.3% | ≥2/5: 91 ≥3/5: 124 ≥4/5: 183 = 5/5: 203 |
≥2/5: 7 ≥3/5: 17 ≥4/5: 33 = 5/5: 65 |
≥2/5: 79 ≥3/5: 69 ≥4/5: 53 = 5/5: 21 |
≥2/5: 117 ≥3/5: 84 ≥4/5: 25 = 5/5: 5 |
≥2/5: 92.2% ≥3/5: 87.9% ≥4/5: 84.7% = 5/5: 75.8% |
≥2/5: 40.3% ≥3/5: 45.1% ≥4/5: 68% = 5/5: 80.7% |
Itatani (2014) [27] | 13 | Patient | 168 | 25 | NR | NR | 87% | NR | (1) PSAd ≥ 0.1 or GP 4/5 or ≥ 3/6 pos cores; max CCL < 50% (2) PSAd ≥ 0.15 or GP 4/5 or max core length invasion < 3 mm (min 6 cores) |
NR | NR | NR | NR | NR | NR | NR |
Porpiglia (2014) [44] | 30.6 | Patient | 107 | 5 | 47 | 11 | 95.5% | 81% | NR | NR | NR | NR | NR | NR | NR | NR |
Thompson (2014) [56] | 61.3 | Patient | 35 | 16 | 76 | 23 | 68.6% | 76.7% | Moderate or high risk Moderate risk: GS 7 (GP4 >5%) and <50% of positive cores or GS 6–7 (GP4 ≤ 5%) and either ≥30% of positive cores or max core length invasion ≥8 mm High risk: GS ≥ 7 (GP4 > 5%); ≥50% + cores or GS ≥ 8 |
34% | 49 | 2 | 49 | 50 | 96% | 49.5% |
Pokorny (2014) [43] | 63.7 | Patient | ≥3/5: 56 ≥4/5: 74 |
≥3/5: 25 ≥4/5: 40 |
≥3/5: 101 ≥4/5: 86 |
≥3/5: 41 ≥4/5: 23 |
≥3/5: 69.1% ≥4/5: 64.9% |
≥3/5: 71.1% ≥4/5: 78.9% |
NR | NR | NR | NR | NR | NR | NR | NR |
Petrillo (2014) [42] | 18.4 | Patient | 56 | 4 | 21 | 55 | 93% | 28% | NR | NR | NR | NR | NR | NR | NR | NR |
Javali (2014) [29] | 16.4 | Patient | 49 | 1 | 22 | 68 | 98% | 24.4% | NR | NR | NR | NR | NR | NR | NR | NR |
Abd-Alazeez (2014) [13] | 54.7 | Lobe | ≥3/5: 33 | ≥3/5: 14 | ≥3/5: 127 | ≥3/5: 84 | ≥3/5: 70% | ≥3/5: 60% | Def 1: GS ≥ 4 + 3 and/or max CCL ≥ 6 mm Def 2: GS ≥ 3 + 4 and/or max CCL ≥ 4 mm Def 3: GS ≥ 4 + 3 Def 4: GS ≥ 3 + 4 Def 5: max CCL ≥ 6 mm Def 6: max CCL ≥ 4 mm |
Def 1: NR Def 2: 44.2% Def 3: 23.2% Def 4: 36% Def 5: 32.9% Def 6: 39.5% |
Def 1: 46 Def 2: 42 Def 3: 47 Def 4: 43 Def 5: 46 Def 6: 43 |
Def 1: 1 Def 2: 5 Def 3: 0 Def 4: 4 Def 5: 1 Def 6: 4 |
Def 1: 45 Def 2: 72 Def 3: 13 Def 4: 50 Def 5: 39 Def 6: 59 |
Def 1: 166 Def2: 139 Def 3: 198 Def 4: 161 Def 5: 172 Def 6: 152 |
Def 1: 98 Def 2: 89 Def 3: 100 Def 4: 92 Def 5: 98 Def 6: 91 |
Def 1: 21 Def 2: 34 Deg 3: 6 Def 4: 24 Def 5: 19 Def 6: 28 |
≥4/5: 87 | ≥3/5: 62 | ≥3/5: 79 | ≥3/5: 30 | ≥3/5: 58% | ≥3/5: 73% | Def 1: 140 Def 2: 124 Def 3: 148 Def 4: 133 Def 5: 141 Def 6: 131 |
Def 1: 9 Def 2: 25 Def 3: 1 Def 4: 16 Def 5: 8 Def 6: 18 |
Def 1: 37 Def 2: 52 Def 3: 12 Def 4: 38 Def 5: 32 Def 6: 45 |
Def 1: 72 Def 2: 57 Def 3: 97 Def 4: 71 Def 5: 77 Def 6: 64 |
Def 1: 94 Def 2: 83 Def 3: 99 Def 4: 89 Def 5: 95 Def 6: 88 |
Def 1: 34 Def 2: 48 Def 3: 11 Def 4: 35 Def 5: 30 Def 6: 42 |
|||||
Abd-Alazeez (2014) [12] | 47.2 | Lobe | ≥3/5: 26 | ≥3/5: 13 | ≥3/5: 38 | ≥3/5: 31 | ≥3/5: 66% | ≥3/5: 55% | Def 1: GS ≥ 4 + 3 and/or max CCL ≥ 6 mm Def 2: GS ≥ 3 + 4 and/or max CCL ≥ 4 mm Def 3: GS ≥ 4 + 3 Def 4: GS ≥ 3 + 4 Def 5: max CCL ≥ 6 mm Def 6: max CCL ≥ 4 mm |
Def 1: 18.5% Def 2: 31.5% Def 3: 4.6% Def 4: 21.3% Def 5: 16.7% Def 6: 25% |
Def 1: 37 Def 2: 31 Def 3: 39 Def 4: 36 Def 5: 37 Def 6: 32 |
Def 1: 2 Def 2: 8 Def 3: 0 Def 4: 3 Def 5: 2 Def 6: 7 |
Def 1: 18 Def 2: 26 Def 3: 5 Def 4: 20 Def 5: 16 Def 6: 20 |
Def 1: 51 Def 2: 43 Def 3: 64 Def 4: 49 Def 5: 53 Def 6: 49 |
Def 1: 95 Def 2: 79 Def 3: 100 Def 4: 92 Def 5: 95 Def 6: 82 |
Def 1: 26 Def 2: 38 Def 3: 7 Def 4: 29 Def 5: 23 Def 6: 29 |
≥4/5: 49 | ≥4/5: 25 | ≥4/5: 26 | ≥4/5: 8 | ≥4/5: 66% | ≥4/5: 76% | Def 1: 70 Def 2: 63 Def 3: 73 Def 4: 68 Def 5: 70 Def 6: 64 |
Def 1: 4 Def 2: 11 Def 3: 1 Def 4: 6 Def 5: 4 Def 6: 10 |
Def 1: 16 Def 2: 23 Def 3: 4 Def 4: 17 Def 5: 14 Def 6: 17 |
Def 1: 18; Def 2: 11 Def 3: 30 Def 4: 17 Def 5: 20 Def 6: 17 |
Def 1: 94 Def 2: 85 Def 3: 99 Def 4: 92 Def 5: 94 Def 6: 86 |
Def 1: 47 Def 2: 67 Def 3: 12 Def 4: 50 Def 5: 41 Def 6: 49 |
|||||
Matsuoka (2014) [37] | 64.8 | Lobe | 46 | 49 | 149 | 26 | 48.4% | 85.1% | NR | NR | NR | NR | NR | NR | NR | NR |
Junker (2013) [30] | 53.4 | Patient | ≥10/15: 21 ≥11/15: 28 |
≥10/15: 4 ≥11/15: 12 |
≥10/15: 35 ≥11/15: 27 |
≥10/15: 13 ≥11/15: 6 |
≥10/15: 84% ≥11/15: 70% |
≥10/15: 72.9% ≥11/15: 81.8% |
GS ≥ 4 + 3 | 13.7% | ≥13: 54 | ≥13: 2 | ≥13: 8 | ≥13: 9 | ≥13: 96.4% | ≥13: 47% |
Busetto (2013) [16] | 41.7 | Patient | 59 | 7 | 61 | 36 | 89% | 63% | NR | NR | NR | NR | NR | NR | NR | NR |
Rais-Bahrami (2013) [47] | 54.2 | Patient | ≥2/4 : 80 | ≥2/4: 275 | ≥2/4: 187 | ≥2/4: 275 | ≥2/4: 66% | ≥2/4: 59% | GS ≥ 7: GS ≥ 8 |
31.7% | NR | NR | NR | NR | GS ≥ 7: 91% GS ≥ 8: 91% |
GS ≥ 7: 38% GS ≥ 8: 18% |
≥3/4: 251 | ≥3/4: 76 | ≥3/4: 16 | ≥3/4: 76 | ≥3/4: 51% | ≥3/4: 82% | NR | NR | NR | NR | GS ≥ 7: 75% GS ≥ 8: 91% |
GS ≥ 7: 67% GS ≥ 8: 41% |
|||||
Kuru (2013) [34] | 57.6 | Patient | 80 | 14 | 67 | 186 | 85.1% | 73.5% | NR | NR | NR | NR | NR | NR | NR | NR |
Ferda (2013) [20] | 51.2 | Patient | 52 | 2 | 82 | 28 | 96.3% | 74.5% | NR | NR | NR | NR | NR | NR | NR | NR |
Ganie (2013) [21] | 74.7 | Patient | 13 | 3 | 62 | 9 | 59.1% | 95.4% | NR | NR | NR | NR | NR | NR | NR | NR |
Vinet (2013) [57] | 49.3 | Patient | ≥3/5: 11 | ≥3/5: 6 | ≥3/5: 28 | ≥3/5: 24 | ≥3/5: 64.7% | ≥3/5: 53.8% | NR | NR | NR | NR | NR | NR | NR | NR |
≥4/5: 22 | ≥4/5: 11 | ≥4/5: 23 | ≥4/5: 13 | ≥4/5: 66.7% | ≥4/5: 63.8% | NR | NR | NR | NR | NR | NR | NR | NR | |||
Numao (2013) [38] | 45 | Patient | 137 | 57 | 101 | 56 | 70.6% | 64.3% | Def 1: GS ≥4 + 3 and/or ≥20% positive cores and/or max CCL ≥5 mm Def 2: GS ≥ 3 + 4 and/or ≥20% + cores and/or max CCL ≥5 mm Def 3: GS ≥ 3 + 4 and/or ≥20% + cores |
Def 1: 33.3% Def 2:37.8% Def 3: 35.8% |
Def 1: 74 Def 2: 65 Def 3: 69 |
Def 1: 83 Def 2: 92 Def 3: 88 |
Def 1: 160 Def 2: 153 Def 3: 156 |
Def 1: 34 Def 2: 41 Def 3: 38 |
Def 1: 82.4% Def 2: 78.8% Def 3: 80.4% |
Def 1: 58.8% Def 2: 58.5% Def 3: 56% |
Belas (2012) [14] | 53.5 | Patient | 22 | 12 | 23 | 13 | 64.7% | 63.8% | NR | NR | NR | NR | NR | NR | NR | NR |
Ibrahiem (2012) [26] | 73.9 | Patient | 14 | 11 | 57 | 10 | 56% | 85.1% | NR | NR | NR | NR | NR | NR | NR | NR |
Sciarra (2012) [51] | 34.5 | Patient | 41 | 4 | 25 | 14 | 91.1% | 64.1% | NR | NR | NR | NR | NR | NR | NR | NR |
Portalez (2012) [45] | 48.1 | Lesion | Likert: 357 | Likert: 50 | Likert: 81 | Likert: 50 | Likert: 95% | Likert: 38% | Max CCL >3 mm and/or GG 4/5 | NR | NR | NR | NR | NR | NR | NR |
PI-RADS: 404 | PI-RADS: 47 | PI-RADS: 34 | PI-RADS: 47 | PI-RADS: 95% | PI-RADS: 58% | |||||||||||
Watanabe (2012) [59] | 48.1 | Patient | 485 | 73 | 624 | 266 | 86.9% | 70.1% | NR | NR | NR | NR | NR | NR | NR | NR |
Tamada (2011) [54] | 70 | Patient | 12 | 6 | 29 | 3 | 67% | 91% | NR | NR | NR | NR | NR | NR | NR | NR |
Region | 277 | 48 | 55 | 20 | 85% | 73% | ||||||||||
Choi (2011) [18] | 70.6 | Patient | 9 | 5 | 31 | 6 | 64.2% | 75.7% | NR | NR | NR | NR | NR | NR | NR | NR |
Iwazawa (2011) [28] | 40.5 | Region | 887 | 86 | 232 | 219 | 91.1% | 51.4% | NR | NR | NR | NR | NR | NR | NR | NR |
Rouse (2011) [48] | 33.7 | Sextant | 145 | 11 | 74 | 22 | 92.9% | 77.1% | GS ≥ 7: Def 1: ≥3 mm Def 2: ≥5 mm |
Def 1: 26.6% Def 2: 26.2% |
Def 1: 153 Def 2: 153 |
Def 1: 3 Def 2: 3 |
Def 1: 64 Def 1: 63 |
Def 1: 32 Def 2: 33 |
Def 1: 98.1% Def 2: 98.1% |
Def 1: 68.1% Def 2: 67% |
59.6 | Patient | 24 | 14 | 54 | 22 | 63.2% | 71.1% | Def 1: 41.2% Def 2: 36.8% |
Def 1: 30 Def 2: 31 |
Def 1: 4 Def 2: 3 |
Def 1: 43 Def 2: 39 |
Def 1: 4 Def 2: 3 |
Def 1: 88.2% Def 2: 91.2% |
Def 1: 53.8% Def 2: 48.8% |
||
Haffner (2011) [23] | 54.4 | Patient | 154 | 50 | 240 | 111 | 75.4% | 68.3% | NR | NR | NR | NR | NR | NR | NR | NR |
Panebianco (2010) [40] | 42.7 | Patient | NR | NR | NR | NR | 95.1% | 88.2% | NR | NR | NR | NR | NR | NR | NR | NR |
Roy (2010) [49] | 55.9 | Patient | NR | NR | NR | NR | 71% | 75% | NR | NR | NR | NR | NR | NR | NR | NR |
Testa (2010) [55] | 40.7 | Patient | NR | NR | NR | NR | 79.3% | 64% | NR | NR | NR | NR | NR | NR | NR | NR |
Sciarra (2010) [52] | 50 | Patient | 61 | 4 | 66 | 9 | 93.8% | 88% | NR | NR | NR | NR | NR | NR | NR | NR |
Kitajima (2010) [31] | 56.6 | Patient | 311 | 19 | 80 | 14 | 92.2% | 85.1% | NR | NR | NR | NR | NR | NR | NR | NR |
Labanaris (2010) [35] | 73.9 | Patient | 17 | 73 | 96 | 74 | 81.11% | 56.47% | NR | NR | NR | NR | NR | NR | NR | NR |
Kumar (2009) [32] | 21.7 | Patient | 39 | 3 | 10 | 8 | 92.8% | 55% | NR | NR | NR | NR | NR | NR | NR | NR |
Schmuecking (2009) [50] | NR | Lobe | NR | NR | NR | NR | 96% | 61% | NR | NR | NR | NR | NR | NR | NR | NR |
Cheikh (2009) [17] | 24.7 | Patient | 36 | 12 | 11 | 34 | 80% | 22.9% | NR | NR | NR | NR | NR | NR | NR | NR |
Cirillo (2008) [19] | 31.5 | Patient | 19 | 0 | 17 | 18 | 100% | 48.6% | NR | NR | NR | NR | NR | NR | NR | NR |
Kumar (2007) [33] | 13.3 | Patient | 39 | 0 | 11 | 33 | 100% | 25% | NR | NR | NR | NR | NR | NR | NR | NR |
Squillaci (2005) [53] | 50.8 | Patient | 29% | 8% | 25% | 3% | 89% | 80% | NR | NR | NR | NR | NR | NR | NR | NR |
Hara (2005) [24] | 41.5 | Patient | ≥2/3: 40 = 3/3: 47 |
≥2/3: 4 = 3/3: 8 |
≥2/3 30 = 3/3: 26 |
≥2/3: 8 = 3/3: 1 |
≥2/3: 90% = 3/3: 85% |
≥2/3: 78.9% = 3/3: 96.3% |
NR | NR | NR | NR | NR | NR | NR | NR |
Cancer prevalence tended to be higher and mpMRI NPV lower in the biopsy-naïve group as compared with the repeat biopsy group, in men with positive DRE as compared with men with negative DRE and when an endorectal coil was not used ( Table 3 ). There were no clear differences in the prevalence and NPV of the other analysed subgroups (TRUS-guided vs TTP biopsy, biopsy procedures with ≤16 cores vs >16 cores; Table 3 ). However, comparisons must be interpreted with care, due to the small number of studies in some subgroups. In patients with a PSA level of ≤10 ng/ml, the median NPV for overall PCa was 86.3% (IQR, 73.3–93.6%) for a median cancer prevalence of 35.4% (IQR, 27.6–42.5%).
Nb of studies | Median PCa prevalence | Median mpMRI NPV | Nb of studies | Median csPCa prevalence | Median mpMRI NPV | |
---|---|---|---|---|---|---|
Biopsy-naïve patients | 8 | 51.4% (45.5–56.7) | 69.9% (64.2–78) | 1 | 35.8% (NA) | 80.4% (NA) |
Repeat biopsy | 14 | 42% (35.1–52.6) | 82.6% (75.5–93.1) | 3 | 24.4% (19.1–32.8) | 88.2% (87.9–92.3) |
TRUS-guided biopsy | 36 | 49.7% (34.3–57.7) | 84.6% (68.6–92.8) | 4 | 28.1% (21.7–36.5) | 89.3% (82.9–92.4) |
TTP biopsy | 4 | 53.8% (47.5–57.8) | 73.6% (72–78.7) | 2 | 31.6% (30.5–32.8) | 92% (89.9–94) |
Biopsy with ≤16 cores | 28 | 48.7% (39.2–54.8) | 81.9% (66.8–89.3) | 5 | 28.1% (21.8–36.5) | 89.3% (82.9–92.4) |
Biopsy with >16 cores | 5 | 56.6% (51–61.3) | 81.1% (73.1–92.2) | 2 | 31.7% (30.5–32.8) | 92% (89.9–93.9) |
Positive DRE | 1 | 73.9% (NA) | 56% (NA) | 0 | – | – |
Negative DRE | 6 | 36% (34.6–46.8) | 82.7% (74.2–93.1) | 0 | – | – |
Endorectal coil | 17 | 41.7% (30.6–55.9) | 92.8% (79.3–95.4) | 1 | 31.7% (NA) | 91% (NA) |
No endorectal coil | 22 | 50.9% (41.7–56.1) | 77.7% (69.5–86.6) | 7 | 34% (26.9–46.1%) | 87.9% (78.2–92.1) |
Eight studies reported NPV at patient level for overall PCa and fulfilled the inclusion criteria for meta-analysis ( Table 4 ) [22 25 38 41 43 46 56 57] .
Study | Prevalence a (%) | Neg MRI (%) | NPV (%) | PPV (%) | Spe (%) | Se (%) | ||
---|---|---|---|---|---|---|---|---|
All PCa | Score ≥ 3/5 | Grenabo Bergdahl (2016) [22] | 31.3 | 66.9 | 83.7 | 47.5 | 63.2 | 73.1 |
Numao (2013) [38] | 45 | 29.4 | 70.6 | 64.3 | 71.0 | 63.9 | ||
Hauth (2015) [25] | 45.7 | 14.3 | 85.7 | 48.3 | 11.8 | 97.7 | ||
Vinet (2013) [57] | 49.3 | 24.6 | 64.7 | 53.8 | 31.4 | 82.4 | ||
Radtke (2015) [46] | 51 | 27 | 73 | 73.2 | 71.5 | 74.7 | ||
Thompson (2014) [56] | 61.3 | 31.4 | 68.6 | 76.8 | 60.3 | 82.6 | ||
Pokorny (2014) [43] | 63.7 | 30.9 | 69.1 | 82.4 | 69.1 | 82.4 | ||
Score ≥ 4/5 | Pepe (2015) [41] | 37 | 31 | 74.2 | 42 | 36.5 | 78.4% | |
Vinet (2013) [57] | 49.3 | 47.8 | 66.7 | 63.9 | 62.9 | 67.6% | ||
Radtke (2015) [46] | 51 | 73.5 | 63.9 | 92.3 | 95.8 | 48% | ||
Gleason ≥7 PCa | Score ≥ 3/5 | Radtke (2015) [46] | 29.3 | 27 | 87.9 | 45.1 | 59.6 | 80.2% |
a Prevalence of overall prostate cancers (10 first lines) or Gleason ≥7 cancers (last line).
PCa = prostate cancer; MRI = magnetic resonance imaging; Neg MRI = proportion of negative magnetic resonance imaging; NPV = negative predictive value; PPV = positive predictive value; Se = sensitivity; Spe = specificity.
Seven studies used a score of ≥3/5 for defining positive mpMRI ( Fig. 4 A and B) [22 25 38 43 46 56 57] . Fig. 4 C shows the conditional probability plot of 1 – NPV and PPV as a function of overall PCa prevalence. Table 5 shows NPV and PPV estimates for the given values of PCa prevalence.
PCaPrev | PPV | NPV |
---|---|---|
0.30 | 0.43 (0.34–0.53) | 0.88 (0.77–0.99) |
0.40 | 0.54 (0.45–0.64) | 0.82 (0.70–0.94) |
0.50 | 0.64 (0.55–0.73) | 0.76 (0.64–0.88) |
0.60 | 0.73 (0.65–0.80) | 0.67 (0.56–0.79) |
0.70 | 0.81 (0.75–0.87) | 0.57 (0.47–0.67) |
0.75 | 0.84 (0.79–0.89) | 0.51 (0.42–0.59) |
Only three studies used a score of ≥4/5 for defining positive mpMRI ( Table 4 ) [41 46 57] , and a formal meta-analysis could not be performed.
Only one study reporting NPV at patient level for Gleason ≥7 cancers met the selection criteria for inclusion in the meta-analysis. It reported NPV and PPV of 87.9% and 45.1%, respectively, for a prevalence of 29.3% ( Table 4 ) [46] .
We observed a large variability in reported NPV. Many factors, such as differences in mpMRI protocols, definition of negative mpMRI, or biopsy protocols, can explain this variability. However, two major causes of variability must be pointed out. First, the cancer prevalence was highly variable, ranging at patient level from 13% to 74.7% for overall PCa, and from 13.7% to 50.9% for csPCa. This variability was observed in both the biopsy-naïve and the repeat biopsy setting. As NPV depends on prevalence, this had a major impact on reported NPV ( Fig. 3 ). Second, the definition of csPCa was highly variable from one series to another, and differences of up to 21% could be observed in NPV when different definitions of csPCa were used in the same dataset [12 13 38 47 48] .
To account for clinical heterogeneity and to further explore the clinical relevance of the results, we carefully selected studies for inclusion in the meta-analysis based on stringent criteria. Particularly, we included only studies that: (1) had biopsy protocols with at least 10 cores, since it is no longer recommended to obtain less than 10 cores per biopsy; (2) used DWI, which is the most informative technique, at least for cancers in the peripheral zone [60] ; and (3) reported mpMRI findings using a five-level score, so that negative findings could be better defined. We accepted studies using a subjective (Likert) scale because experienced readers obtained equivalent [45 61 62] or better [63] results with the Likert score than with the PI-RADS v1 score. Owing to the large variations of NPV induced by differences in definitions of csPCa, we did not include different definitions in the meta-analysis since this would have introduced unacceptable clinical heterogeneity in the results, possibly resulting in erroneous and biased estimates. We, therefore, a priori restricted the definition of csPCa to cancers with a Gleason score of ≥7, given the low lethal potential of Gleason 6 cancers [64] and the lack of consensus among pathologists on the best method to measure biopsy core invasion length [65 66] .
In this more homogeneous group of studies, the prevalence range was still large (31.3–63.7%). As a result, we modelled the evolution of NPV (and PPV) as a function of overall PCa prevalence. Unfortunately, we could not duplicate this for csPCa since only one study reporting NPV for Gleason ≥7 cancers met the inclusion criteria for meta-analysis.
We included only studies that reported the results of systematic/standard biopsy in patients with negative mpMRI and used the systematic/standard biopsy as a reference standard. It is well known that TRUS-guided biopsy harbours both random and systematic errors, as evidenced by the high rates of positivity of immediate repeat biopsy after a first series of negative biopsies [67 68] , and as confirmed recently by the PROMIS trial [69] . Therefore, using TRUS-guided biopsy as a reference standard may have overestimated the NPV of mpMRI. However, studies using radical prostatectomy specimens as a reference standard have already reported mpMRI detection rates in relation to PCa Gleason score and volume [1] . In this review, we intended to address the more pragmatic question as to whether a negative mpMRI could predict a negative subsequent biopsy. This is an important question because if the NPV of mpMRI was sufficiently high in comparison with the reference standard of systematic/standard biopsies, then in practice a negative mpMRI result could indeed avoid the need for prostate biopsy. Therefore, studies reporting only biopsy results when the mpMRI was positive (eg, obtained through MRI-targeted, guided, or fusion biopsies with added systematic biopsies) were not included in this review.
It is now well established that mpMRI is a sensitive tool for detecting aggressive PCa 1 2 3 69] . However several reasons preclude its broad use as a triage test before biopsy.
Firstly, the population referred to prostate biopsy is not standardised. The large range of reported prevalence for overall PCa and csPCa suggests substantial heterogeneity in the way patients are selected for biopsy. Owing to this heterogeneity, we did not provide a pooled estimate for mpMRI NPV. The role of mpMRI as a triage test before prostate biopsy should be evaluated in the broader context of the selection of patients with a suspicion of (aggressive) PCa. In a recent retrospective study of 514 patients, mpMRI NPV for Gleason ≥7 cancers was 91% when the PSA density was ≤0.2 ng/ml/ml, and only 71% when the PSA density was >0.2 ng/ml/ml ( p = 0.003) [70] . In another series of 288 biopsy-naïve patients, no csPCa (Gleason score ≥7 or maximum cancer core length ≥4 mm) was found in 44 patients with a PSA density of <0.15 ng/ml/ml and a PI-RADS v2 score of <3/5 [71] . We believe that such prestratification of the risk of csPCa is an interesting way for rationalising the use of mpMRI before biopsy. Patients found at very low risk would be spared both mpMRI and biopsy. Patients at a low risk—for whom mpMRI would have an NPV high enough to be used as a triage test—could avoid biopsy in case of negative mpMRI. Patients at a higher risk would need biopsy even in case of negative mpMRI. Many tools can be used to risk stratify the population of patients referred to biopsy, ranging from simple parameters such as PSA density to more complicated risk calculators [72 73] . The impact of these tools on the NPV of prebiopsy mpMRI needs to be carefully evaluated, both in the biopsy-naïve and in the repeat biopsy setting. For the moment, it is impossible to make any recommendations on the best way to risk stratify patients before referring them for mpMRI.
Secondly, the large variability in the definition of csPCa precludes any definitive conclusion on the ability of mpMRI to rule out aggressive cancer. The issue of the most appropriate definition of csPCa on biopsy is complex, since biopsy results may accurately reflect neither tumour burden nor aggressiveness. Nonetheless, there is an urgent need to standardise the histological definition(s) of csPCa, to allow meaningful comparisons between studies.
Thirdly, the specificity of mpMRI remains moderate, and there is a substantial proportion of false positives in the lesions scored 3/5 or 4/5 [1 74 75] , even with the new PI-RADS v2 score [76] . In a series of 62 patients with 116 lesions biopsied under magnetic resonance/ultrasound fusion, the overall cancer detection rates for PI-RADS v2 scores of 3/5 and 4/5 were only 15.8% and 29.8%, respectively [77] . In theory, a triage test used to rule out a disease needs to be highly sensitive for this disease. However, if its specificity is too low, it will be clinically useless since most patients will be positive, whether they have the disease or not. Therefore, if mpMRI is to be used as a triage test in the future, there is a need to improve its specificity. This could be achieved by a continuous refinement of scores [78] . Promising results in characterising csPCa have also been reported with a quantitative analysis [79] .
Finally, all published studies were conducted in specialised centres. The broad use of mpMRI as a triage test assumes good interobserver reproducibility. Unfortunately, interobserver reproducibility of existing scoring systems remains moderate [62 63 80] even with the use of the PI-RADS v2 score [80 81] . Studies evaluating on a large scale the reproducibility of mpMRI findings between expert and nonexpert centres are currently lacking.
Three systematic reviews (including two meta-analyses) regarding the role of mpMRI in localised PCa have been published recently 4 5 6 . Crucially, all three reviews focused exclusively on the sensitivity of mpMRI-targeted, guided, or fusion biopsies in diagnosing overall PCa and csPCa, using TRUS-guided prostate biopsies as reference standards. The impact of systematic biopsies on the outcome was not addressed in any of the reviews, within either the index test or the reference standard. Our review had a totally different research question and objective, focusing on NPV of mpMRI to see if a negative mpMRI can avoid the need for a prostate biopsy. As MRI-targeted/guided/fusion biopsies are not relevant if the mpMRI was negative for cancer, it can be argued that the three reviews assessed a different index test altogether. As such, we believe that the findings of this review are novel and unique, and pave the way for further focused clinical studies.
The current study represents the first systematic review addressing the role of mpMRI as a triage test before biopsy. The review elements were developed in conjunction with a multidisciplinary panel of experts (EAU Prostate Cancer Guidelines Panel), which included a patient representative, and the review was performed robustly in accordance with recognised standards. However, it is limited by the major heterogeneity of the existing literature in patient population, study design, and definitions of positive mpMRI and csPCa. It highlighted further areas of research that could help in defining the best use of mpMRI in the early detection of aggressive PCa in the future.
Although mpMRI can detect aggressive PCa with excellent sensitivity, a definitive conclusion on its role as a triage test before prostate biopsy will be possible only when three main issues are addressed. Firstly, because NPV depends on prevalence, and because overall PCa and csPCa prevalence was highly variable in the published series, it becomes mandatory to define the optimal way to pre-evaluate the risk of csPCa in patients with a suspicion of PCa. Depending on the risk category, mpMRI could then be used to obviate biopsies or not. Secondly, there is a need for consensus definitions of csPCa on biopsy findings to allow interstudy comparisons. Thirdly, although efforts have been made to standardise mpMRI technical protocols and interpretation in the past few years [11 60 76] , there is still a crucial need to improve mpMRI specificity and inter-reader reproducibility.
This systematic review was performed under the auspices of:
The European Association of Urology Guidelines Office Board
The European Association of Urology Prostate Cancer Guideline Panel
Author contributions: Olivier Rouvière had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.
Study concept and design: Rouvière, Mottet, Cornford.
Acquisition of data: Rouvière, Moldovan, Van den Broeck, Yuan.
Analysis and interpretation of data: Rouvière, Moldovan, Van den Broeck, Lam.
Drafting of the manuscript: Rouvière, Moldovan, Van den Broeck, Lam.
Critical revision of the manuscript for important intellectual content: Bellmunt, van den Bergh, Bolla, Briers, Van den Broeck, Cornford, Cumberbatch, De Santis, Fossati, Gross, Henry, Joniau, Lam, Matveev, Moldovan, van der Poel, van der Kwast, Rouvière, Schoots, Wiegel, Mottet.
Statistical analysis: None.
Obtaining funding: None.
Administrative, technical, or material support: Yuan, Sylvester, Marconi.
Supervision: None.
Other: None.
Financial disclosures: Olivier Rouvière certifies that all conflicts of interest, including specific financial interests and relationships and affiliations relevant to the subject matter or materials discussed in the manuscript (eg, employment/affiliation, grants or funding, consultancies, honoraria, stock ownership or options, expert testimony, royalties, or patents filed, received, or pending), are the following: Bellmunt is a company consultant for Janssen, Astellas, Pierre Fabre, Genentech, Merck, Ipsen, Pfizer, Novartis, and Sanofi Aventis. He has received research support from Takeda, Novartis, and Sanofi, and received travel grants from Pfizer and Pierre Fabre. Bolla has received company speaker honoraria from Ipsen and Astellas, honoraria or consultation fees from Janssen, and fellowship and travel grants from Janssen, AstraZeneca, and Astellas. Briers has received grant and research support from Ipsen, European Association of Urology, and Bayer; is an ex officio board member for Europa UOMO; is an ethics committee and advisory group member for REQUITE; is a member patient advisory board member for PAGMI; and is a member of SCA and EMA PCWP. Cornford is a company consultant for Astellas, Ipsen, and Ferring. He receives company speaker honoraria from Astellas, Janssen, Ipsen, and Pfizer; participates in trials from Ferring; and receives fellowships and travel grants from Astellas and Janssen. De Santis is a company consultant for GlaxoSmithKline, Janssen, Bayer, Novartis, Pierre Fabre, Astellas, Amgen, Eisai Inc., ESSA, Merck, and Synthon; has received company speaker honoraria from Pfizer, Takeda, Sanofi Aventis, Shionogi, Celgene, and Teva OncoGenex; has participated in trials for Pierre Fabre, Astellas, Exelixis, Bayer, and Roche; has received fellowship and travel grants from Bayer, Novartis, Ferring, Astellas, Sanofi Aventis, and Janssen; has received grant and research support from Pierre Fabre; has received honoraria from AstraZeneca; and is associated with Amgen. Joniau is a company consultant for Astellas, Ipsen, Bayer, Sanofi, and Janssen; has received company speaker honoraria from Astellas, Amgen, Bayer, Sanofi, Janssen, and Ipsen; has participated in trials for Astellas, Janssen, and Bayer; has received fellowship and travel grants from Astellas, Amgen, Bayer, Sanofi, Janssen, Ipsen, and Pfizer; and has received grant and research support from Astellas, Bayer, and Janssen. Matveev has received company speaker honoraria from Sanofi and Astellas, has participated in trials for Astellas, Pfizer and Novartis. Lam is a company consultant for and has received company speaker honoraria from Pfizer, GSK, Astellas, and Ipsen. van der Poel is a company consultant for Intuitive Surgical, has participated in trials for Astellas and Steba Biotech, and has received grant and research support from Astellas. Rouvière is a company consultant for EDAP-TMS, Bracco, and Philips; has received company speaker honoraria from EDAP-TMS, Bracco, and Philips; and has participated in trials for EDAP-TMS and Bracco. Wiegel has received company speaker honoraria from Astellas, Takeda, Hexal, Ipsen, Janssen-Cilac, and Ferring. Mottet has received grant and research support from Takeda Pharmaceutical, Millenium, Astellas, Pierre Fabre, Sanofi, and Pasteur, and has received honoraria or consultation fees from Takeda Pharaceutical, Millenium, Jansen, Astellas, BMS, Bayer, Ipsen, Ferring, Novartis, Nuclétron, Pierre Fabre, Sanofi, and Zeneca. van den Bergh, Van den Broeck, Cumberbatch, Fossati, Gross, Henry, van der Kwast, Sylvester, Yuan, Schoots, Moldovan, and Marconi have nothing to disclose.
Funding/Support and role of the sponsor: None.
A correlation with radical prostatectomy specimens has demonstrated that multiparametric magnetic resonance imaging (mpMRI) has excellent sensitivity in detecting prostate cancer (PCa) with a Gleason score of ≥7 1 2 3 . As a result, prostate mpMRI is increasingly used in patients with a suspicion of PCa to localise abnormal areas before biopsy. A large body of literature has shown that targeted biopsies of suspicious lesions seen on mpMRI (TBx) improved the detection of clinically significant PCa (csPCa), at least in the repeat biopsy setting 4 5 6 . As a result, it is now recommended that an mpMRI is performed before repeat biopsy to allow TBx of suspicious lesions in addition to standard biopsies [7] .
Some authors have recently suggested that, besides improving csPCa detection, mpMRI could also be used as a triage test so that patients with negative mpMRI findings could obviate biopsy. Such a strategy remains highly controversial [8] and depends upon the negative predictive value (NPV) of mpMRI. Therefore, the European Association of Urology Prostate Cancer Guidelines Panel undertook this systematic review and meta-analysis to assess the NPV of mpMRI in patients with a suspicion of PCa and, thus, its potential role in eliminating unnecessary prostate biopsy.
Our primary aim was to systematically evaluate the performance of negative prebiopsy prostate mpMRI in predicting a negative biopsy result for overall PCa and csPCa in biopsy-naïve men and in men with previously negative biopsies. A further objective was to explore and define factors that may contribute to relevant thresholds in order to provide guidance for future studies.
The review was performed according to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) statement [9] . The review protocol was published in PROSPERO database ( http://www.crd.york.ac.uk/PROSPERO; registration number CRD42015021929). Databases searched included the Embase and OVID Medline databases, the Cochrane database of systematic reviews, and the Cochrane Central Register for Clinical Trials, covering from January 1, 2000 to February 13, 2016. Systematic or standard prostate biopsies were used as reference standards, with positive or negative cases of PCa being determined by histopathological examination. The detailed search strategy is presented in Supplement 1.
Included studies focused on men who were assessed for suspected PCa by mpMRI before undergoing prostate biopsy. Studies enrolling both biopsy-naïve men and men who had undergone previous negative biopsies were included. Prebiopsy prostate mpMRI was considered the index test and comprised T2-weighted imaging (T2WI) and at least one functional imaging technique (diffusion-weighted imaging [DWI], dynamic contrast-enhanced imaging [DCEI], or magnetic resonance spectroscopic imaging [MRSI]). For inclusion, studies had to report on false negatives and true negatives, in order to calculate NPV (ie, results of systematic/standard prostate biopsies when the mpMRI was negative). When available, false positive and true positive findings were also noted to calculate the positive predictive value (PPV) and the cancer prevalence. There was restriction neither on the biopsy technique (transrectal or transperineal) nor on the number of biopsy cores. Studies using radical prostatectomy specimens as reference standards were excluded, as were studies evaluating men with histologically proven PCa. Studies with less than 50 participants were excluded. No language restrictions were applied.
Two reviewers (P.C.M. and T.V.D.B.) independently screened all abstracts and full-text articles for eligibility. Disagreement was resolved by consensus or reference to an independent third party (L.M.). All screening was performed using a predefined eligibility form.
Using a data extraction form developed a priori, the same two reviewers independently extracted data concerning study methodology, patient characteristics, technical characteristics of the MR scanners, mpMRI protocol, mpMRI scoring system, definition of positive mpMRI, biopsy protocol, and definition of csPCa. Any discrepancies concerning data extraction were resolved by consensus or reference to an independent arbiter (O.R. or T.B.L.).
To assess the risk of bias (RoB), all included reports were reviewed using the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool for diagnostic accuracy studies [10] .
Outcome data regarding false negative and true negative values of mpMRI before prostate biopsy were recorded as reported by authors. When not available, data were indirectly derived from specificity, sensitivity, and prevalence values reported by authors using an online Bayesian statistics calculator ( http://www.medcalc.com/bayes.html ). Descriptive statistics were used to summarise baseline characteristics and outcomes, including median and interquartile range (IQR) for estimates of NPV across studies. A correlation between mpMRI NPV and a positive biopsy rate was established using the Pearson's correlation coefficient.
A meta-analysis was undertaken to calculate pooled NPV and PPV. To ensure appropriate clinical homogeneity of the studies included in the meta-analysis, we selected only the studies enrolling biopsy-naïve patients and/or patients with a history of negative biopsy, and fulfilling the following criteria that were defined a priori: (1) reference standard consisting of prostate biopsy with at least 10 samples on all patients; (2) mpMRI protocol comprising at least T2WI and DWI; (3) mpMRI results presented as a five-level score, using a subjective Likert scale or the Prostate Imaging Reporting Data System (PI-RADS) score [11] ; (4) definition of positive mpMRI as a score ≥3/5 or ≥4/5; and (5) results reported on a per patient basis. In addition, only studies defining csPCa as Gleason ≥7 cancers were selected for the meta-analysis assessing the mpMRI NPV for csPCa. A bivariate random-effects approach was employed using the Midas package in Stata 12 (StataCorp LP, College Station, TX, USA). Since the NPV decreases and the PPV increases as the prevalence increases, post-test probability estimates of NPV and PPV were reported for the given values of the prevalence based on Bayes’ theorem.
For other studies not included in the meta-analysis based on the criteria described above, a narrative synthesis of the data was performed. To explore and define clinical heterogeneity, subgroups were analysed at patient level based on the following variables: biopsy-naïve versus previous negative biopsy; patients with positive versus negative digital rectal examination (DRE); mpMRI performed with an endorectal versus without an endorectal coil; transrectal ultrasound (TRUS) versus template transperineal (TTP) biopsy approach; and ≤16 cores versus >16 cores as the reference standard. Studies reporting mpMRI NPV for patients with a prostate-specific antigen (PSA) level of ≤10 ng/ml were also reported separately.
The study selection process is depicted in the PRISMA flow diagram ( Fig. 1 ). A total of 2980 abstracts were retrieved. After abstract screening and removal of duplicates, 240 articles were eligible for full text screening, of which 48 studies were eligible for inclusion 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 .
Out of the 48 included studies, 42 were single-centre and six were multicentre studies. Thirty-four studies were prospective and six were retrospective, whilst the design of the rest was unclear. RoB assessment using QUADAS-2 was performed for each of the individual studies ( Fig. 2 A and B). Overall, the RoB was highly heterogeneous across studies for all criteria, except for the reference standard domain, in which RoB was low in most studies.
The 48 studies comprised a total of 9613 men who underwent prostate mpMRI followed by biopsy. The study and patient baseline characteristics are presented in Table 1 . The patient population consisted of biopsy-naive men in nine studies, men with at least one previous negative biopsy in 16 studies, and both biopsy-naïve men and men with a history of previous negative biopsy in nine studies. In 14 studies, the biopsy history of the patients was unclear.
Study | Study design | Period | Population | Pt Nb | Mean/median* age (yr) | Mean/median* PSA (ng/ml) | Mean/median* prostate volume (cm 3 ) | Magnetic field strength | MR pulse sequences | Endorectal coil | MR score | Definition of positive MRI | Reference standard |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Hauth (2015) [25] | Prospective | 2011–2013 | FB | 94 | 64 (43–83) | 9 (3–31) | 51 (17–140) | 1.5 T | T2WI/DWI/DCEI/MRSI | No | PI-RADS v1 | ≥3 | 11–13-core TRUS SBx + TBx |
Lamb (2015) [36] | Retrospective | 2013–2013 | FB & PNB | 173 | NR | NR | NR | 1.5 T | T2WI/DWI | NR | NR | NR | 12-core TRUS SBx |
Brock (2015) [15] | Prospective | 2013–2014 | PNB | 168 | 64* (IQR 59–70) | 9.2* (IQR 6.7–13.4) | 55.4* (IQR 42–80) | 3 T | T2WI/DWI/DCEI | No | PI-RADS v1 | NR | 12/24-core TRUS SBx + TBx |
Grenabo Bergdahl (2016) [22] | Prospective | 2013–2014 | FB & PNB | 83 | 69.3* (IQR 69–69.6) | 1.6* (IQR 0.9–2.7) | NR | 3 T | T2WI/DWI/DCEI/MRSI | No | PI-RADS v1 | ≥3 | 10-core TRUS SBx + TBx |
Wang (2015) [58] | Prospective | 2002–2009 | FB & PNB | 586 | 70 (26–91) | 11.11* (0.02–9794) | NR | 1.5 T | T2WI/DWI/DCEI/MRSI | Yes | PI-RADS v1 | ≥3 | TRUS SBx |
Pepe (2015) [41] | Prospective | 2011–2014 | PNB | 100 | 64* | 8.6* (4.2–10) | NR | 3 T | T2WI/DWI/DCEI/MRSI | No | PI-RADS v1 | ≥4 | TPBx + TBx |
Panebianco (2015) [39] | Prospective | 2011–2014 | FB (61.62%) & PNB (38.34%) | 925 (1140 total cohort) |
NR | NR | NR | 3 T | T2WI/DWI/DCEI | Yes | PI-RADS v1 | NR | 14-core TRUS SBx; 45-core sat TPBx + TBx |
Radtke (2015) [46] | Prospective | 2013–2013 | FB (63.3%) & PNB (36.7%) | 294 | 64* (60–71) | 7.3 (6.0) | 47 (37.5) | 3 T | T2WI/DWI/DCEI | No | PI-RADS v1 | PI-RADS ≥2; PI-RADS ≥3; PI-RADS ≥4; PI-RADS = 5; |
24-core TPBx + TBx |
Itatani (2014) [27] | Retrospective | 2004–2007 | NR | 193 | 68.9 (8.4); 70* (47–89) | 11.8 (15.9); 7.9* (1.22–159) | NR | 1.5 T | T2WI/DWI/DCEI | No | 1–5 scale (Likert) | ≥3 | 12–14-core TRUS SBx |
Porpiglia (2014) [44] | Prospective | 2011–2013 | PNB | 170 | 65* (60–70) | 6.9* (5.2–9.8) | 42* (36–48) | 1.5 T | T2WI/DWI/DCEI | Yes | Dichotomous | Positive: at least 2/3 MR seq. with suspicious findings | 18–24-core TRUS SBx (volume dependent) |
Thompson (2014) [56] | Prospective | 2012–2013 | FB (88%) & PNB (12%) | 150 | 62.4* (IQR 55.0–66.4) | 5.6* (IQR 4.5–7.5) | 40* (IQR 30–57) | 1.5 T (47%) & 3 T (53%) | T2WI/DWI/DCEI | No | PI-RADS v1 | ≥3 | Median of 30 TPBx (volume dependent) |
Pokorny (2014) [43] | Prospective | 2012–2013 | FB | 223 | 63* (IQR 57–68) | 5.3* (IQR 4.1–6.6) | 41* (IQR 30–59) | 3 T | T2WI/DWI/DCEI | No | PI-RADS v1 | ≥3 (primary); ≥4 |
12-core TRUS SBx + TBx |
Petrillo (2014) [42] | Prospective | 2009–2010 | NR | 136 | NR | NR | NR | 1.5 T | T2WI/DWI/MRSI | Yes | 1–5 scale (Likert) | ≥3 | 12–16-core TRUS SBx (volume + PSA dependent) |
Javali (2014) [29] | Retrospective | 2002–2011 | NR | 140 | Control: 62.4 (10.5); Study: 62.9 (12.1) | Control: 6.8 (2.3); Study: 6.87 (2.6) | Control: 44 (14.2); Study: 43 (18.4) | 1.5 T | T2WI/MRSI | Yes | Dichotomous | Cit/[Cho + Cr] < 1.2 | 6-core TRUS SBx ( n = 69), 12-core TRUS SBx ( n = 119) |
Abd-Alazeez (2014) [13] | Prospective | 2007–2011 | FB | 129 | 62* (41–82) | 5.8* (1.2–20) | 40* (16–137) | 1.5 & 3 T | T2WI/DWI/DCEI | No | PI-RADS v1 | ≥3 (primary); ≥4 |
20-core TPBx |
Abd-Alazeez (2014) [12] | Retrospective | NR | PNB | 54 | 64* (39–75) | 10* (2–23) | 53* (19–136) | 1.5 & 3 T | T2WI/DWI/DCEI | No | PI-RADS v1 | ≥3 (primary); ≥4 |
≥20-core TPBx + TBx ( n = 15) |
Matsuoka (2014) [37] | Prospective | 2007–2012 | NR | 135 | 67* (50–80) | 7.0* (2.9–19.8) | 25.4* (12.7–90.2) | 1.5 T | T2WI/DWI | No | 1–5 scale (Likert) | ≥3 | 14-core TRUS SBX |
Junker (2013) [30] | Retrospective | 2011–2013 | PNB | 73 | 62 (7.4) | 7.0* (5.1–12.9) | 45* (34–61) | 3 T | T2WI/DWI/DCEI | No | PI-RADS | PI-RADS ≥10 and ≥11 for all PCa PI-RADS ≥13 for significant PCa |
10-core TRUS SBx + TBx |
Busetto (2013) [16] | Prospective | 2010–2012 | PNB | 163 | 66.4 (5.3) | 6.8 (1.6) | NR | 3 T | T2WI/DWI/DCEI/MRSI | Yes | NR | NR | 10-core TRUS SBx + TBx |
Rais-Bahrami (2013) [47] | Prospective | 2007–2012 | NR | 583 | 61.3 (8.4) | 9.9 (13.1) | NR | 3 T | T2WI/DWI/DCEI/MRSI | Yes | 1–4 scale (Likert) | ≥2 ≥3 |
12-core TRUS SBx + TBx |
Kuru (2013) [34] | Prospective | 2010–2011 | FB (51%) & PNB (49%) | 347 | 65.3 (42–82) | 9.85 (0.5–104) | 48.7 (9–180) | 3 T | T2WI/DWI/DCEI | No | 1–3 scale (Likert) | ≥2 | 12–36-core TRUS SBx (volume dependent) + TBx |
Ferda (2013) [20] | Prospective | NR | NR | 164 | (49–74) | (4.2–123) | NR | 3 T | T2WI/DWI/DCEI/MRSI | No | NR | In house | TRUS SBx |
Ganie (2013) [21] | NR | 2007–2009 | PNB | 87 | NR | NR | NR | 1.5 T | T2WI/MRSI | Yes | MRSI Cho/Cit ratio | In house | 6 core TRUS SBx + MRI TBx |
Vinet (2013) [57] | Prospective | 2009–2011 | FB | 69 | NR | 5.2* (3.2–28) | NR | 1.5 T (35 pts) & 3 T (34 pts) | T2WI/DWI/DCEI | No | 1–5 scale (Likert) | ≥3 | 12-core TRUS SBx + TBx |
Numao (2013) [38] | Prospective | 2006–2010 | FB | 351 | 65* (59–70) | 6.3* (4.9–9.1) | 32* (24–42) | 1.5 T | T2WI/DWI/DCEI (no DCEI in 42 pts) | No | 1–5 scale (Likert) | ≥3 | 3D 26-core (12 TRUS SBx + 14 TPBx – 203 pts); 3D 14-core (6 TRUS SBx + 8 TPBx – 102 pts); TPBx 14 core (46 pts) |
Belas (2012) [14] | Prospective | 2010–2011 | FB | 71 | 66* (47–76) | 7* (4–10) | 45* (15–150) | 1.5 T | T2WI/DWI/DCEI | No | TZ: 0–4 scale PZ: 0–10 scale |
TZ: >2 PZ: >6 |
12-core TRUS SBx + TBx |
Ibrahiem (2012) [26] | Prospective | 2008–2009 | FB | 100 | 65.03 (7.13) | 26.3 (24.2) | 60.09 (28.7) | 1.5 T | T2WI/DWI | No | NR | In house | 12-core TRUS SBX |
Sciarra (2012) [51] | Prospective | 2008–2011 | PNB | 84 | 64.09 (46–76) | 7.07 (4.2–15.5) | NR | 3 T | T2WI/DWI/DCEI/MRSI | Yes | NR | NR | 10-core TRUS Bx + TBx |
Portalez (2012) [45] | Prospective | 2011 | PNB | 129 | 64.7 (47–79) | 9.6 (2.7–40) | 51.1 (12–192) | 1.5 T | T2WI/DWI/DCEI | Mixed | 1–5 scale (Likert) PI-RADS |
Likert ≥3 PI-RADS ≥9 |
10–12-core TRUS SBx + TBx |
Watanabe (2012) [59] | Prospective | 2004–2008 | NR | 1448 | 72 (7.5) | NR | NR | 1.5 T | T2WI/DWI | No | NR | ADC value ≤1.35 × 10 −3 mm 2 /s | 8-core TRUS SBx + TBx |
Tamada (2011) [54] | Retrospective | 2006–2009 | NR | 50 | 70 (40–84) | 6.84* (4.06–9.94) | NR | 1.5 T | T2WI/DWI/DCEI | No | NR | In house | 12-core TRUS SBx |
Choi (2011) [18] | NR | 2009–2010 | NR | 51 | 67.16 (56–90) | 14.16 (1.02–38.9) | 42.98 (13.8–77.3) | 3 T | T2WI/DWI | NR | NR | NR | 10–12-core TRUS SBx + TBx |
Iwazawa (2011) [28] | Retrospective | 2008–2009 | NR | 178 | 68.8 (41–86) | 20.51 (4.04–568.5) | NR | 1.5 T | T2WI/DWI/DCEI | NR | 1–4 scale (Likert) | NR | 10–12-core TRUS SBx (TBx included in SBx chart) |
Rouse (2011) [48] | Prospective | 2005–2007 | PNB | 114 | 63.6 (41–83) | 13.4 (0–228) | NR | 1.5 T | T2WI/DWI/DCEI | NR | 1–5 scale (Likert) | ≥3 | TRUS SBx |
Haffner (2011) [23] | Prospective | 2005–2009 | FB | 555 | 64* (47–83) | 6.75* (0.18–100) | 46* (15–200) | 1.5 T | T2WI/DCEI | No | 1–5 scale (Likert) | ≥3 | 10-core TRUS SBx + TBx |
Panebianco (2010) [40] | Prospective | 2007–2009 | PNB | 150 | 61.2 (46–78) | 9.42 (3.91) | 41.17 (7.47) | 1.5 T | T2WI/DCEI/MRSI | Yes | NR | In house | 10-core TRUS SBx (TBx included in SBx chart) |
Roy (2010) [49] | Not specified | 2011–2009 | FB (53%) & PNB (47%) | 103 | 63 (52–78) | 7* | NR | 3 T | T2WI/DWI/DCEI | Yes | NR | NR | 8-core TRUS SBx + TBx |
Testa (2010) [55] | Not specified | 2007 | PNB | 54 | 63.9 (52–76) | 11.4 (3–42) | 59.3 (30–150) | 1.5 T | T2WI/MRSI | Yes | 1–3 scale (Likert) | ≥2 | 12-core TRUS SBx + TBx |
Sciarra (2010) [52] | Prospective | 2007–2009 | PNB | 110 | 63.5 (49–74) | NR | NR | 1.5 T | T2WI/DCEI/MRSI | Yes | NR | In house | 10-core TRUS SBx + TBx |
Kitajima (2010) [31] | Prospective | 2008–2009 | NR | 53 | 69* (56–84) | 11.1* (4.2–112.1) | NR | 3 T | T2WI/DWI/DCEI | No | 1–5 scale (Likert) | ≥3 | 20-core TPBx |
Labanaris (2010) [35] | Prospective | 2004–2008 | PNB | 260 | NR | NR | NR | 1 T | T2WI/DWI/DCEI | Yes | Dichotomous | In house | 18-core TRUS SBx |
Kumar (2009) [32] | NR | NR | NR | 61 | 65.3 (9.3) | 16.5 (0.21–155) | NR | 1.5 T | T2WI/MRSI | Yes | NR | (Cit/(Cho + Cr) ≤ 1.2 | TRUS Bx |
Schmuecking (2009) [50] | NR | NR | FB & PNB | 67 | 68 | 11.5 | NR | 1.5 T | T2WI/DCEI | No | NR | NR | 20-core Bx |
Cheikh (2009) [17] | Retrospective | 2005–2008 | PNB | 93 | 63.2 (52–74) | 9.63 (1.6–40) | NR | 1.5 T | T2WI/DCEI | No | Dichotomous | In house | 12-core TRUS SBx + TBx |
Cirillo (2008) [19] | Prospective | 2004–2006 | PNB | 54 | 65.5 (5.2) | 10.8 (7.5) | NR | 1.5 T | T2WI/MRSI | Yes | Dichotomous | In house | 10-core TRUS SBx + TBx |
Kumar (2007) [33] | Prospective | 2003–2005 | NR | 83 | NR | NR | NR | 1.5 T | T2WI/MRSI | Yes | NR | NR | 12-core TRUS SBx + TBx |
Squillaci (2005) [53] | Prospective | 2004–2005 | NR | 65 | NR | NR | NR | 1.5 T | T2WI/DCEI/MRSI | No | 1–3 scale (Likert) | ≥2 | 10-core TRUS SBx + TBx |
Hara (2005) [24] | Prospective | 2003–2004 | FB | 90 | 67.2 (NR) | NR | NR | 1.5 T | T2WI/DCEI | No | 1–3 scale (Likert) | ≥2 = 3 |
14-core TRUS SBx |
The magnetic field strength was 1, 1.5, and 3 T in one, 28, and 15 studies, respectively. Four studies used both 1.5 and 3 T MR systems. DWI and DCEI were used in 36 and 35 studies, respectively. Nineteen studies also added MRSI. An endorectal coil was used in 18 studies. The definition of positive mpMRI varied across studies. The PI-RADS v1 score was used in 12 studies, a five-level subjective (Likert) score was used in eight studies, and one study reported data based on the two scoring systems. In-house criteria were used in 13 studies for defining positive mpMRI, and five studies used a dichotomous definition. Nine studies did not report on the criteria for positive mpMRI. No study used the PI-RADS v2 score.
Regarding the reference standard, TRUS-guided biopsies were used in 39 studies, TTP biopsies in six studies, and mixed TRUS-guided and TTP biopsies in two studies. In one study, the biopsy approach was unclear. The number of cores per biopsy procedure was ≤16 in 30 studies, >16 in nine studies, and variable among patients in three studies. For six studies, the number of biopsy cores taken was unclear.
At patient level, the median biopsy positivity rate (ie, cancer prevalence) was 50.4% (IQR, 36.4–57.7%) for overall cancer and 32.9% (IQR, 28.1–37.2%) for csPCa ( Table 2 ). The median mpMRI NPV was 82.4% (IQR, 69.0–92.4%) for overall cancer and 88.1% (IQR, 85.7–92.3) for csPCa. NPV significantly decreased when cancer prevalence increased, both for overall cancer ( r = –0.64, p < 0.0001) and csPCa ( r = –0.75, p = 0.032; Fig. 3 ). In addition, NPV was highly dependent on the definition used for csPCa, with differences of up to 21% when several definitions were used in the same dataset [12 13 38 47 48] .
Study | Overall PCa prevalence (%) | Reporting level | Multiparametric MRI performance for PCa detection | Definition of csPCa | csPCa prevalence | Multiparametric MRI performance for csPCa detection | ||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
TN | FN | TP | FP | NPV | PPV | TN | FN | TP | FP | NPV | PPV | |||||
Hauth (2015) [25] | 45.7 | Patient | 6 | 1 | 42 | 45 | 85.7% | 48.3% | Low grade: GS ≤ 6 High grade: GS ≥ 7 |
NR | NR | NR | NR | NR | NR | NR |
Lesion | 59 | 13 | 55 | 73 | 81.9% | 43% | ||||||||||
Lamb (2015) [36] | 65.9 | Patient | 23 | 22 | 92 | 36 | 51.1% | 71.9% | GS ≥ 7 | 50.9% | 31 | 14 | 71 | 57 | 68.9% | 55.5% |
Brock (2015) [15] | 42.3 | Patient | 17 | 7 | 56 | 88 | 70.8% | SBx: 38.8% TBx: 22.2% Duo: 44.4% |
Epstein: GS > 6 and/or max CCL ≥50% | 24.4% | SBx: 21 | SBx: 3 | SBx: 38 TBx: 27 duo: 47 |
SBx: 106 TBx: 117 duo: 97 |
87.5% | SBx: 26.4% TBx: 18.8% duo: 32.6% |
Grenabo Bergdahl (2016) [22] | 33.7 | Patient | 36 | 7 | 19 | 21 | 83.7% | 47.5% | Clinically insignificant PCa: T1c, PSAd < 0.15, GS < 7, ≤2 positive cores, and unilateral cancer | NR | NR | NR | NR | NR | NR | NR |
Wang (2015) [58] | 58 | Patient | 165 | 8 | 332 | 81 | 95.4% | 80.4% | NR | NR | NR | NR | NR | NR | NR | NR |
Pepe (2015) [41] | 37 | Patient | 23 | 8 | 29 | 40 | 74.2% | 42% | GS ≥ 7 or GS 6 with CCL ≥ 50% | NR | NR | NR | NR | NR | 100% | 55.8% |
Panebianco (2015) [39] | 74.7 | Patient | Group A (satBx): 104 | Group A (satBx): 43 | Group A: 186 | Group A: 22 | Group A (satBx): 70.7% | Group A: 89.4% | NR | 60% | Group A: 147 | Group A: 0 | Group A: 183 | Group A: 25 | Group A: 100% | Group A: 88% |
Group B (TRUSGB NR TRUS G satBx): 93 | Group B (TRUSGB NR TRUS G satBx): 37 | Group B: 417 before and 425 after satBx | Group B: 23/440 and 15/440 after satBx. | Group B (TRUSGB–TRUS G satBx): 71.5% | Group B: 94.8% before and 96.6% after satBx | 71.9% | Group B: 130 | Group B: 0 | Group B: 410 |
Group B: 30 | Group B: 100% | Group B: 93.2% | ||||
Radtke (2015) [46] | 51 | Patient | ≥2/5: 80 ≥3: 103 ≥4: 138 = 5: 142 |
≥2/5: 18 ≥3/5: 38 ≥4/5: 78 = 5/5: 126 |
≥2/5: 132 ≥3/5: 112 ≥4/5: 72 = 5/5: 24 |
≥2/5: 64 ≥3/5: 41 ≥4/5: 6 = 5/5: 2 |
≥2/5: 81.6% ≥ 3/5: 73.1% ≥ 4/5: 63.9% = 5/5: 53% |
≥2/5: 67.4% ≥ 3/5: 73.2% ≥ 4/5: 92.3% = 5/5: 92.3% |
GS ≥ 7 | 29.3% | ≥2/5: 91 ≥3/5: 124 ≥4/5: 183 = 5/5: 203 |
≥2/5: 7 ≥3/5: 17 ≥4/5: 33 = 5/5: 65 |
≥2/5: 79 ≥3/5: 69 ≥4/5: 53 = 5/5: 21 |
≥2/5: 117 ≥3/5: 84 ≥4/5: 25 = 5/5: 5 |
≥2/5: 92.2% ≥3/5: 87.9% ≥4/5: 84.7% = 5/5: 75.8% |
≥2/5: 40.3% ≥3/5: 45.1% ≥4/5: 68% = 5/5: 80.7% |
Itatani (2014) [27] | 13 | Patient | 168 | 25 | NR | NR | 87% | NR | (1) PSAd ≥ 0.1 or GP 4/5 or ≥ 3/6 pos cores; max CCL < 50% (2) PSAd ≥ 0.15 or GP 4/5 or max core length invasion < 3 mm (min 6 cores) |
NR | NR | NR | NR | NR | NR | NR |
Porpiglia (2014) [44] | 30.6 | Patient | 107 | 5 | 47 | 11 | 95.5% | 81% | NR | NR | NR | NR | NR | NR | NR | NR |
Thompson (2014) [56] | 61.3 | Patient | 35 | 16 | 76 | 23 | 68.6% | 76.7% | Moderate or high risk Moderate risk: GS 7 (GP4 >5%) and <50% of positive cores or GS 6–7 (GP4 ≤ 5%) and either ≥30% of positive cores or max core length invasion ≥8 mm High risk: GS ≥ 7 (GP4 > 5%); ≥50% + cores or GS ≥ 8 |
34% | 49 | 2 | 49 | 50 | 96% | 49.5% |
Pokorny (2014) [43] | 63.7 | Patient | ≥3/5: 56 ≥4/5: 74 |
≥3/5: 25 ≥4/5: 40 |
≥3/5: 101 ≥4/5: 86 |
≥3/5: 41 ≥4/5: 23 |
≥3/5: 69.1% ≥4/5: 64.9% |
≥3/5: 71.1% ≥4/5: 78.9% |
NR | NR | NR | NR | NR | NR | NR | NR |
Petrillo (2014) [42] | 18.4 | Patient | 56 | 4 | 21 | 55 | 93% | 28% | NR | NR | NR | NR | NR | NR | NR | NR |
Javali (2014) [29] | 16.4 | Patient | 49 | 1 | 22 | 68 | 98% | 24.4% | NR | NR | NR | NR | NR | NR | NR | NR |
Abd-Alazeez (2014) [13] | 54.7 | Lobe | ≥3/5: 33 | ≥3/5: 14 | ≥3/5: 127 | ≥3/5: 84 | ≥3/5: 70% | ≥3/5: 60% | Def 1: GS ≥ 4 + 3 and/or max CCL ≥ 6 mm Def 2: GS ≥ 3 + 4 and/or max CCL ≥ 4 mm Def 3: GS ≥ 4 + 3 Def 4: GS ≥ 3 + 4 Def 5: max CCL ≥ 6 mm Def 6: max CCL ≥ 4 mm |
Def 1: NR Def 2: 44.2% Def 3: 23.2% Def 4: 36% Def 5: 32.9% Def 6: 39.5% |
Def 1: 46 Def 2: 42 Def 3: 47 Def 4: 43 Def 5: 46 Def 6: 43 |
Def 1: 1 Def 2: 5 Def 3: 0 Def 4: 4 Def 5: 1 Def 6: 4 |
Def 1: 45 Def 2: 72 Def 3: 13 Def 4: 50 Def 5: 39 Def 6: 59 |
Def 1: 166 Def2: 139 Def 3: 198 Def 4: 161 Def 5: 172 Def 6: 152 |
Def 1: 98 Def 2: 89 Def 3: 100 Def 4: 92 Def 5: 98 Def 6: 91 |
Def 1: 21 Def 2: 34 Deg 3: 6 Def 4: 24 Def 5: 19 Def 6: 28 |
≥4/5: 87 | ≥3/5: 62 | ≥3/5: 79 | ≥3/5: 30 | ≥3/5: 58% | ≥3/5: 73% | Def 1: 140 Def 2: 124 Def 3: 148 Def 4: 133 Def 5: 141 Def 6: 131 |
Def 1: 9 Def 2: 25 Def 3: 1 Def 4: 16 Def 5: 8 Def 6: 18 |
Def 1: 37 Def 2: 52 Def 3: 12 Def 4: 38 Def 5: 32 Def 6: 45 |
Def 1: 72 Def 2: 57 Def 3: 97 Def 4: 71 Def 5: 77 Def 6: 64 |
Def 1: 94 Def 2: 83 Def 3: 99 Def 4: 89 Def 5: 95 Def 6: 88 |
Def 1: 34 Def 2: 48 Def 3: 11 Def 4: 35 Def 5: 30 Def 6: 42 |
|||||
Abd-Alazeez (2014) [12] | 47.2 | Lobe | ≥3/5: 26 | ≥3/5: 13 | ≥3/5: 38 | ≥3/5: 31 | ≥3/5: 66% | ≥3/5: 55% | Def 1: GS ≥ 4 + 3 and/or max CCL ≥ 6 mm Def 2: GS ≥ 3 + 4 and/or max CCL ≥ 4 mm Def 3: GS ≥ 4 + 3 Def 4: GS ≥ 3 + 4 Def 5: max CCL ≥ 6 mm Def 6: max CCL ≥ 4 mm |
Def 1: 18.5% Def 2: 31.5% Def 3: 4.6% Def 4: 21.3% Def 5: 16.7% Def 6: 25% |
Def 1: 37 Def 2: 31 Def 3: 39 Def 4: 36 Def 5: 37 Def 6: 32 |
Def 1: 2 Def 2: 8 Def 3: 0 Def 4: 3 Def 5: 2 Def 6: 7 |
Def 1: 18 Def 2: 26 Def 3: 5 Def 4: 20 Def 5: 16 Def 6: 20 |
Def 1: 51 Def 2: 43 Def 3: 64 Def 4: 49 Def 5: 53 Def 6: 49 |
Def 1: 95 Def 2: 79 Def 3: 100 Def 4: 92 Def 5: 95 Def 6: 82 |
Def 1: 26 Def 2: 38 Def 3: 7 Def 4: 29 Def 5: 23 Def 6: 29 |
≥4/5: 49 | ≥4/5: 25 | ≥4/5: 26 | ≥4/5: 8 | ≥4/5: 66% | ≥4/5: 76% | Def 1: 70 Def 2: 63 Def 3: 73 Def 4: 68 Def 5: 70 Def 6: 64 |
Def 1: 4 Def 2: 11 Def 3: 1 Def 4: 6 Def 5: 4 Def 6: 10 |
Def 1: 16 Def 2: 23 Def 3: 4 Def 4: 17 Def 5: 14 Def 6: 17 |
Def 1: 18; Def 2: 11 Def 3: 30 Def 4: 17 Def 5: 20 Def 6: 17 |
Def 1: 94 Def 2: 85 Def 3: 99 Def 4: 92 Def 5: 94 Def 6: 86 |
Def 1: 47 Def 2: 67 Def 3: 12 Def 4: 50 Def 5: 41 Def 6: 49 |
|||||
Matsuoka (2014) [37] | 64.8 | Lobe | 46 | 49 | 149 | 26 | 48.4% | 85.1% | NR | NR | NR | NR | NR | NR | NR | NR |
Junker (2013) [30] | 53.4 | Patient | ≥10/15: 21 ≥11/15: 28 |
≥10/15: 4 ≥11/15: 12 |
≥10/15: 35 ≥11/15: 27 |
≥10/15: 13 ≥11/15: 6 |
≥10/15: 84% ≥11/15: 70% |
≥10/15: 72.9% ≥11/15: 81.8% |
GS ≥ 4 + 3 | 13.7% | ≥13: 54 | ≥13: 2 | ≥13: 8 | ≥13: 9 | ≥13: 96.4% | ≥13: 47% |
Busetto (2013) [16] | 41.7 | Patient | 59 | 7 | 61 | 36 | 89% | 63% | NR | NR | NR | NR | NR | NR | NR | NR |
Rais-Bahrami (2013) [47] | 54.2 | Patient | ≥2/4 : 80 | ≥2/4: 275 | ≥2/4: 187 | ≥2/4: 275 | ≥2/4: 66% | ≥2/4: 59% | GS ≥ 7: GS ≥ 8 |
31.7% | NR | NR | NR | NR | GS ≥ 7: 91% GS ≥ 8: 91% |
GS ≥ 7: 38% GS ≥ 8: 18% |
≥3/4: 251 | ≥3/4: 76 | ≥3/4: 16 | ≥3/4: 76 | ≥3/4: 51% | ≥3/4: 82% | NR | NR | NR | NR | GS ≥ 7: 75% GS ≥ 8: 91% |
GS ≥ 7: 67% GS ≥ 8: 41% |
|||||
Kuru (2013) [34] | 57.6 | Patient | 80 | 14 | 67 | 186 | 85.1% | 73.5% | NR | NR | NR | NR | NR | NR | NR | NR |
Ferda (2013) [20] | 51.2 | Patient | 52 | 2 | 82 | 28 | 96.3% | 74.5% | NR | NR | NR | NR | NR | NR | NR | NR |
Ganie (2013) [21] | 74.7 | Patient | 13 | 3 | 62 | 9 | 59.1% | 95.4% | NR | NR | NR | NR | NR | NR | NR | NR |
Vinet (2013) [57] | 49.3 | Patient | ≥3/5: 11 | ≥3/5: 6 | ≥3/5: 28 | ≥3/5: 24 | ≥3/5: 64.7% | ≥3/5: 53.8% | NR | NR | NR | NR | NR | NR | NR | NR |
≥4/5: 22 | ≥4/5: 11 | ≥4/5: 23 | ≥4/5: 13 | ≥4/5: 66.7% | ≥4/5: 63.8% | NR | NR | NR | NR | NR | NR | NR | NR | |||
Numao (2013) [38] | 45 | Patient | 137 | 57 | 101 | 56 | 70.6% | 64.3% | Def 1: GS ≥4 + 3 and/or ≥20% positive cores and/or max CCL ≥5 mm Def 2: GS ≥ 3 + 4 and/or ≥20% + cores and/or max CCL ≥5 mm Def 3: GS ≥ 3 + 4 and/or ≥20% + cores |
Def 1: 33.3% Def 2:37.8% Def 3: 35.8% |
Def 1: 74 Def 2: 65 Def 3: 69 |
Def 1: 83 Def 2: 92 Def 3: 88 |
Def 1: 160 Def 2: 153 Def 3: 156 |
Def 1: 34 Def 2: 41 Def 3: 38 |
Def 1: 82.4% Def 2: 78.8% Def 3: 80.4% |
Def 1: 58.8% Def 2: 58.5% Def 3: 56% |
Belas (2012) [14] | 53.5 | Patient | 22 | 12 | 23 | 13 | 64.7% | 63.8% | NR | NR | NR | NR | NR | NR | NR | NR |
Ibrahiem (2012) [26] | 73.9 | Patient | 14 | 11 | 57 | 10 | 56% | 85.1% | NR | NR | NR | NR | NR | NR | NR | NR |
Sciarra (2012) [51] | 34.5 | Patient | 41 | 4 | 25 | 14 | 91.1% | 64.1% | NR | NR | NR | NR | NR | NR | NR | NR |
Portalez (2012) [45] | 48.1 | Lesion | Likert: 357 | Likert: 50 | Likert: 81 | Likert: 50 | Likert: 95% | Likert: 38% | Max CCL >3 mm and/or GG 4/5 | NR | NR | NR | NR | NR | NR | NR |
PI-RADS: 404 | PI-RADS: 47 | PI-RADS: 34 | PI-RADS: 47 | PI-RADS: 95% | PI-RADS: 58% | |||||||||||
Watanabe (2012) [59] | 48.1 | Patient | 485 | 73 | 624 | 266 | 86.9% | 70.1% | NR | NR | NR | NR | NR | NR | NR | NR |
Tamada (2011) [54] | 70 | Patient | 12 | 6 | 29 | 3 | 67% | 91% | NR | NR | NR | NR | NR | NR | NR | NR |
Region | 277 | 48 | 55 | 20 | 85% | 73% | ||||||||||
Choi (2011) [18] | 70.6 | Patient | 9 | 5 | 31 | 6 | 64.2% | 75.7% | NR | NR | NR | NR | NR | NR | NR | NR |
Iwazawa (2011) [28] | 40.5 | Region | 887 | 86 | 232 | 219 | 91.1% | 51.4% | NR | NR | NR | NR | NR | NR | NR | NR |
Rouse (2011) [48] | 33.7 | Sextant | 145 | 11 | 74 | 22 | 92.9% | 77.1% | GS ≥ 7: Def 1: ≥3 mm Def 2: ≥5 mm |
Def 1: 26.6% Def 2: 26.2% |
Def 1: 153 Def 2: 153 |
Def 1: 3 Def 2: 3 |
Def 1: 64 Def 1: 63 |
Def 1: 32 Def 2: 33 |
Def 1: 98.1% Def 2: 98.1% |
Def 1: 68.1% Def 2: 67% |
59.6 | Patient | 24 | 14 | 54 | 22 | 63.2% | 71.1% | Def 1: 41.2% Def 2: 36.8% |
Def 1: 30 Def 2: 31 |
Def 1: 4 Def 2: 3 |
Def 1: 43 Def 2: 39 |
Def 1: 4 Def 2: 3 |
Def 1: 88.2% Def 2: 91.2% |
Def 1: 53.8% Def 2: 48.8% |
||
Haffner (2011) [23] | 54.4 | Patient | 154 | 50 | 240 | 111 | 75.4% | 68.3% | NR | NR | NR | NR | NR | NR | NR | NR |
Panebianco (2010) [40] | 42.7 | Patient | NR | NR | NR | NR | 95.1% | 88.2% | NR | NR | NR | NR | NR | NR | NR | NR |
Roy (2010) [49] | 55.9 | Patient | NR | NR | NR | NR | 71% | 75% | NR | NR | NR | NR | NR | NR | NR | NR |
Testa (2010) [55] | 40.7 | Patient | NR | NR | NR | NR | 79.3% | 64% | NR | NR | NR | NR | NR | NR | NR | NR |
Sciarra (2010) [52] | 50 | Patient | 61 | 4 | 66 | 9 | 93.8% | 88% | NR | NR | NR | NR | NR | NR | NR | NR |
Kitajima (2010) [31] | 56.6 | Patient | 311 | 19 | 80 | 14 | 92.2% | 85.1% | NR | NR | NR | NR | NR | NR | NR | NR |
Labanaris (2010) [35] | 73.9 | Patient | 17 | 73 | 96 | 74 | 81.11% | 56.47% | NR | NR | NR | NR | NR | NR | NR | NR |
Kumar (2009) [32] | 21.7 | Patient | 39 | 3 | 10 | 8 | 92.8% | 55% | NR | NR | NR | NR | NR | NR | NR | NR |
Schmuecking (2009) [50] | NR | Lobe | NR | NR | NR | NR | 96% | 61% | NR | NR | NR | NR | NR | NR | NR | NR |
Cheikh (2009) [17] | 24.7 | Patient | 36 | 12 | 11 | 34 | 80% | 22.9% | NR | NR | NR | NR | NR | NR | NR | NR |
Cirillo (2008) [19] | 31.5 | Patient | 19 | 0 | 17 | 18 | 100% | 48.6% | NR | NR | NR | NR | NR | NR | NR | NR |
Kumar (2007) [33] | 13.3 | Patient | 39 | 0 | 11 | 33 | 100% | 25% | NR | NR | NR | NR | NR | NR | NR | NR |
Squillaci (2005) [53] | 50.8 | Patient | 29% | 8% | 25% | 3% | 89% | 80% | NR | NR | NR | NR | NR | NR | NR | NR |
Hara (2005) [24] | 41.5 | Patient | ≥2/3: 40 = 3/3: 47 |
≥2/3: 4 = 3/3: 8 |
≥2/3 30 = 3/3: 26 |
≥2/3: 8 = 3/3: 1 |
≥2/3: 90% = 3/3: 85% |
≥2/3: 78.9% = 3/3: 96.3% |
NR | NR | NR | NR | NR | NR | NR | NR |
Cancer prevalence tended to be higher and mpMRI NPV lower in the biopsy-naïve group as compared with the repeat biopsy group, in men with positive DRE as compared with men with negative DRE and when an endorectal coil was not used ( Table 3 ). There were no clear differences in the prevalence and NPV of the other analysed subgroups (TRUS-guided vs TTP biopsy, biopsy procedures with ≤16 cores vs >16 cores; Table 3 ). However, comparisons must be interpreted with care, due to the small number of studies in some subgroups. In patients with a PSA level of ≤10 ng/ml, the median NPV for overall PCa was 86.3% (IQR, 73.3–93.6%) for a median cancer prevalence of 35.4% (IQR, 27.6–42.5%).
Nb of studies | Median PCa prevalence | Median mpMRI NPV | Nb of studies | Median csPCa prevalence | Median mpMRI NPV | |
---|---|---|---|---|---|---|
Biopsy-naïve patients | 8 | 51.4% (45.5–56.7) | 69.9% (64.2–78) | 1 | 35.8% (NA) | 80.4% (NA) |
Repeat biopsy | 14 | 42% (35.1–52.6) | 82.6% (75.5–93.1) | 3 | 24.4% (19.1–32.8) | 88.2% (87.9–92.3) |
TRUS-guided biopsy | 36 | 49.7% (34.3–57.7) | 84.6% (68.6–92.8) | 4 | 28.1% (21.7–36.5) | 89.3% (82.9–92.4) |
TTP biopsy | 4 | 53.8% (47.5–57.8) | 73.6% (72–78.7) | 2 | 31.6% (30.5–32.8) | 92% (89.9–94) |
Biopsy with ≤16 cores | 28 | 48.7% (39.2–54.8) | 81.9% (66.8–89.3) | 5 | 28.1% (21.8–36.5) | 89.3% (82.9–92.4) |
Biopsy with >16 cores | 5 | 56.6% (51–61.3) | 81.1% (73.1–92.2) | 2 | 31.7% (30.5–32.8) | 92% (89.9–93.9) |
Positive DRE | 1 | 73.9% (NA) | 56% (NA) | 0 | – | – |
Negative DRE | 6 | 36% (34.6–46.8) | 82.7% (74.2–93.1) | 0 | – | – |
Endorectal coil | 17 | 41.7% (30.6–55.9) | 92.8% (79.3–95.4) | 1 | 31.7% (NA) | 91% (NA) |
No endorectal coil | 22 | 50.9% (41.7–56.1) | 77.7% (69.5–86.6) | 7 | 34% (26.9–46.1%) | 87.9% (78.2–92.1) |
Eight studies reported NPV at patient level for overall PCa and fulfilled the inclusion criteria for meta-analysis ( Table 4 ) [22 25 38 41 43 46 56 57] .
Study | Prevalence a (%) | Neg MRI (%) | NPV (%) | PPV (%) | Spe (%) | Se (%) | ||
---|---|---|---|---|---|---|---|---|
All PCa | Score ≥ 3/5 | Grenabo Bergdahl (2016) [22] | 31.3 | 66.9 | 83.7 | 47.5 | 63.2 | 73.1 |
Numao (2013) [38] | 45 | 29.4 | 70.6 | 64.3 | 71.0 | 63.9 | ||
Hauth (2015) [25] | 45.7 | 14.3 | 85.7 | 48.3 | 11.8 | 97.7 | ||
Vinet (2013) [57] | 49.3 | 24.6 | 64.7 | 53.8 | 31.4 | 82.4 | ||
Radtke (2015) [46] | 51 | 27 | 73 | 73.2 | 71.5 | 74.7 | ||
Thompson (2014) [56] | 61.3 | 31.4 | 68.6 | 76.8 | 60.3 | 82.6 | ||
Pokorny (2014) [43] | 63.7 | 30.9 | 69.1 | 82.4 | 69.1 | 82.4 | ||
Score ≥ 4/5 | Pepe (2015) [41] | 37 | 31 | 74.2 | 42 | 36.5 | 78.4% | |
Vinet (2013) [57] | 49.3 | 47.8 | 66.7 | 63.9 | 62.9 | 67.6% | ||
Radtke (2015) [46] | 51 | 73.5 | 63.9 | 92.3 | 95.8 | 48% | ||
Gleason ≥7 PCa | Score ≥ 3/5 | Radtke (2015) [46] | 29.3 | 27 | 87.9 | 45.1 | 59.6 | 80.2% |
a Prevalence of overall prostate cancers (10 first lines) or Gleason ≥7 cancers (last line).
PCa = prostate cancer; MRI = magnetic resonance imaging; Neg MRI = proportion of negative magnetic resonance imaging; NPV = negative predictive value; PPV = positive predictive value; Se = sensitivity; Spe = specificity.
Seven studies used a score of ≥3/5 for defining positive mpMRI ( Fig. 4 A and B) [22 25 38 43 46 56 57] . Fig. 4 C shows the conditional probability plot of 1 – NPV and PPV as a function of overall PCa prevalence. Table 5 shows NPV and PPV estimates for the given values of PCa prevalence.
PCaPrev | PPV | NPV |
---|---|---|
0.30 | 0.43 (0.34–0.53) | 0.88 (0.77–0.99) |
0.40 | 0.54 (0.45–0.64) | 0.82 (0.70–0.94) |
0.50 | 0.64 (0.55–0.73) | 0.76 (0.64–0.88) |
0.60 | 0.73 (0.65–0.80) | 0.67 (0.56–0.79) |
0.70 | 0.81 (0.75–0.87) | 0.57 (0.47–0.67) |
0.75 | 0.84 (0.79–0.89) | 0.51 (0.42–0.59) |
Only three studies used a score of ≥4/5 for defining positive mpMRI ( Table 4 ) [41 46 57] , and a formal meta-analysis could not be performed.
Only one study reporting NPV at patient level for Gleason ≥7 cancers met the selection criteria for inclusion in the meta-analysis. It reported NPV and PPV of 87.9% and 45.1%, respectively, for a prevalence of 29.3% ( Table 4 ) [46] .
We observed a large variability in reported NPV. Many factors, such as differences in mpMRI protocols, definition of negative mpMRI, or biopsy protocols, can explain this variability. However, two major causes of variability must be pointed out. First, the cancer prevalence was highly variable, ranging at patient level from 13% to 74.7% for overall PCa, and from 13.7% to 50.9% for csPCa. This variability was observed in both the biopsy-naïve and the repeat biopsy setting. As NPV depends on prevalence, this had a major impact on reported NPV ( Fig. 3 ). Second, the definition of csPCa was highly variable from one series to another, and differences of up to 21% could be observed in NPV when different definitions of csPCa were used in the same dataset [12 13 38 47 48] .
To account for clinical heterogeneity and to further explore the clinical relevance of the results, we carefully selected studies for inclusion in the meta-analysis based on stringent criteria. Particularly, we included only studies that: (1) had biopsy protocols with at least 10 cores, since it is no longer recommended to obtain less than 10 cores per biopsy; (2) used DWI, which is the most informative technique, at least for cancers in the peripheral zone [60] ; and (3) reported mpMRI findings using a five-level score, so that negative findings could be better defined. We accepted studies using a subjective (Likert) scale because experienced readers obtained equivalent [45 61 62] or better [63] results with the Likert score than with the PI-RADS v1 score. Owing to the large variations of NPV induced by differences in definitions of csPCa, we did not include different definitions in the meta-analysis since this would have introduced unacceptable clinical heterogeneity in the results, possibly resulting in erroneous and biased estimates. We, therefore, a priori restricted the definition of csPCa to cancers with a Gleason score of ≥7, given the low lethal potential of Gleason 6 cancers [64] and the lack of consensus among pathologists on the best method to measure biopsy core invasion length [65 66] .
In this more homogeneous group of studies, the prevalence range was still large (31.3–63.7%). As a result, we modelled the evolution of NPV (and PPV) as a function of overall PCa prevalence. Unfortunately, we could not duplicate this for csPCa since only one study reporting NPV for Gleason ≥7 cancers met the inclusion criteria for meta-analysis.
We included only studies that reported the results of systematic/standard biopsy in patients with negative mpMRI and used the systematic/standard biopsy as a reference standard. It is well known that TRUS-guided biopsy harbours both random and systematic errors, as evidenced by the high rates of positivity of immediate repeat biopsy after a first series of negative biopsies [67 68] , and as confirmed recently by the PROMIS trial [69] . Therefore, using TRUS-guided biopsy as a reference standard may have overestimated the NPV of mpMRI. However, studies using radical prostatectomy specimens as a reference standard have already reported mpMRI detection rates in relation to PCa Gleason score and volume [1] . In this review, we intended to address the more pragmatic question as to whether a negative mpMRI could predict a negative subsequent biopsy. This is an important question because if the NPV of mpMRI was sufficiently high in comparison with the reference standard of systematic/standard biopsies, then in practice a negative mpMRI result could indeed avoid the need for prostate biopsy. Therefore, studies reporting only biopsy results when the mpMRI was positive (eg, obtained through MRI-targeted, guided, or fusion biopsies with added systematic biopsies) were not included in this review.
It is now well established that mpMRI is a sensitive tool for detecting aggressive PCa 1 2 3 69] . However several reasons preclude its broad use as a triage test before biopsy.
Firstly, the population referred to prostate biopsy is not standardised. The large range of reported prevalence for overall PCa and csPCa suggests substantial heterogeneity in the way patients are selected for biopsy. Owing to this heterogeneity, we did not provide a pooled estimate for mpMRI NPV. The role of mpMRI as a triage test before prostate biopsy should be evaluated in the broader context of the selection of patients with a suspicion of (aggressive) PCa. In a recent retrospective study of 514 patients, mpMRI NPV for Gleason ≥7 cancers was 91% when the PSA density was ≤0.2 ng/ml/ml, and only 71% when the PSA density was >0.2 ng/ml/ml ( p = 0.003) [70] . In another series of 288 biopsy-naïve patients, no csPCa (Gleason score ≥7 or maximum cancer core length ≥4 mm) was found in 44 patients with a PSA density of <0.15 ng/ml/ml and a PI-RADS v2 score of <3/5 [71] . We believe that such prestratification of the risk of csPCa is an interesting way for rationalising the use of mpMRI before biopsy. Patients found at very low risk would be spared both mpMRI and biopsy. Patients at a low risk—for whom mpMRI would have an NPV high enough to be used as a triage test—could avoid biopsy in case of negative mpMRI. Patients at a higher risk would need biopsy even in case of negative mpMRI. Many tools can be used to risk stratify the population of patients referred to biopsy, ranging from simple parameters such as PSA density to more complicated risk calculators [72 73] . The impact of these tools on the NPV of prebiopsy mpMRI needs to be carefully evaluated, both in the biopsy-naïve and in the repeat biopsy setting. For the moment, it is impossible to make any recommendations on the best way to risk stratify patients before referring them for mpMRI.
Secondly, the large variability in the definition of csPCa precludes any definitive conclusion on the ability of mpMRI to rule out aggressive cancer. The issue of the most appropriate definition of csPCa on biopsy is complex, since biopsy results may accurately reflect neither tumour burden nor aggressiveness. Nonetheless, there is an urgent need to standardise the histological definition(s) of csPCa, to allow meaningful comparisons between studies.
Thirdly, the specificity of mpMRI remains moderate, and there is a substantial proportion of false positives in the lesions scored 3/5 or 4/5 [1 74 75] , even with the new PI-RADS v2 score [76] . In a series of 62 patients with 116 lesions biopsied under magnetic resonance/ultrasound fusion, the overall cancer detection rates for PI-RADS v2 scores of 3/5 and 4/5 were only 15.8% and 29.8%, respectively [77] . In theory, a triage test used to rule out a disease needs to be highly sensitive for this disease. However, if its specificity is too low, it will be clinically useless since most patients will be positive, whether they have the disease or not. Therefore, if mpMRI is to be used as a triage test in the future, there is a need to improve its specificity. This could be achieved by a continuous refinement of scores [78] . Promising results in characterising csPCa have also been reported with a quantitative analysis [79] .
Finally, all published studies were conducted in specialised centres. The broad use of mpMRI as a triage test assumes good interobserver reproducibility. Unfortunately, interobserver reproducibility of existing scoring systems remains moderate [62 63 80] even with the use of the PI-RADS v2 score [80 81] . Studies evaluating on a large scale the reproducibility of mpMRI findings between expert and nonexpert centres are currently lacking.
Three systematic reviews (including two meta-analyses) regarding the role of mpMRI in localised PCa have been published recently 4 5 6 . Crucially, all three reviews focused exclusively on the sensitivity of mpMRI-targeted, guided, or fusion biopsies in diagnosing overall PCa and csPCa, using TRUS-guided prostate biopsies as reference standards. The impact of systematic biopsies on the outcome was not addressed in any of the reviews, within either the index test or the reference standard. Our review had a totally different research question and objective, focusing on NPV of mpMRI to see if a negative mpMRI can avoid the need for a prostate biopsy. As MRI-targeted/guided/fusion biopsies are not relevant if the mpMRI was negative for cancer, it can be argued that the three reviews assessed a different index test altogether. As such, we believe that the findings of this review are novel and unique, and pave the way for further focused clinical studies.
The current study represents the first systematic review addressing the role of mpMRI as a triage test before biopsy. The review elements were developed in conjunction with a multidisciplinary panel of experts (EAU Prostate Cancer Guidelines Panel), which included a patient representative, and the review was performed robustly in accordance with recognised standards. However, it is limited by the major heterogeneity of the existing literature in patient population, study design, and definitions of positive mpMRI and csPCa. It highlighted further areas of research that could help in defining the best use of mpMRI in the early detection of aggressive PCa in the future.
Although mpMRI can detect aggressive PCa with excellent sensitivity, a definitive conclusion on its role as a triage test before prostate biopsy will be possible only when three main issues are addressed. Firstly, because NPV depends on prevalence, and because overall PCa and csPCa prevalence was highly variable in the published series, it becomes mandatory to define the optimal way to pre-evaluate the risk of csPCa in patients with a suspicion of PCa. Depending on the risk category, mpMRI could then be used to obviate biopsies or not. Secondly, there is a need for consensus definitions of csPCa on biopsy findings to allow interstudy comparisons. Thirdly, although efforts have been made to standardise mpMRI technical protocols and interpretation in the past few years [11 60 76] , there is still a crucial need to improve mpMRI specificity and inter-reader reproducibility.
This systematic review was performed under the auspices of:
The European Association of Urology Guidelines Office Board
The European Association of Urology Prostate Cancer Guideline Panel
Author contributions: Olivier Rouvière had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.
Study concept and design: Rouvière, Mottet, Cornford.
Acquisition of data: Rouvière, Moldovan, Van den Broeck, Yuan.
Analysis and interpretation of data: Rouvière, Moldovan, Van den Broeck, Lam.
Drafting of the manuscript: Rouvière, Moldovan, Van den Broeck, Lam.
Critical revision of the manuscript for important intellectual content: Bellmunt, van den Bergh, Bolla, Briers, Van den Broeck, Cornford, Cumberbatch, De Santis, Fossati, Gross, Henry, Joniau, Lam, Matveev, Moldovan, van der Poel, van der Kwast, Rouvière, Schoots, Wiegel, Mottet.
Statistical analysis: None.
Obtaining funding: None.
Administrative, technical, or material support: Yuan, Sylvester, Marconi.
Supervision: None.
Other: None.
Financial disclosures: Olivier Rouvière certifies that all conflicts of interest, including specific financial interests and relationships and affiliations relevant to the subject matter or materials discussed in the manuscript (eg, employment/affiliation, grants or funding, consultancies, honoraria, stock ownership or options, expert testimony, royalties, or patents filed, received, or pending), are the following: Bellmunt is a company consultant for Janssen, Astellas, Pierre Fabre, Genentech, Merck, Ipsen, Pfizer, Novartis, and Sanofi Aventis. He has received research support from Takeda, Novartis, and Sanofi, and received travel grants from Pfizer and Pierre Fabre. Bolla has received company speaker honoraria from Ipsen and Astellas, honoraria or consultation fees from Janssen, and fellowship and travel grants from Janssen, AstraZeneca, and Astellas. Briers has received grant and research support from Ipsen, European Association of Urology, and Bayer; is an ex officio board member for Europa UOMO; is an ethics committee and advisory group member for REQUITE; is a member patient advisory board member for PAGMI; and is a member of SCA and EMA PCWP. Cornford is a company consultant for Astellas, Ipsen, and Ferring. He receives company speaker honoraria from Astellas, Janssen, Ipsen, and Pfizer; participates in trials from Ferring; and receives fellowships and travel grants from Astellas and Janssen. De Santis is a company consultant for GlaxoSmithKline, Janssen, Bayer, Novartis, Pierre Fabre, Astellas, Amgen, Eisai Inc., ESSA, Merck, and Synthon; has received company speaker honoraria from Pfizer, Takeda, Sanofi Aventis, Shionogi, Celgene, and Teva OncoGenex; has participated in trials for Pierre Fabre, Astellas, Exelixis, Bayer, and Roche; has received fellowship and travel grants from Bayer, Novartis, Ferring, Astellas, Sanofi Aventis, and Janssen; has received grant and research support from Pierre Fabre; has received honoraria from AstraZeneca; and is associated with Amgen. Joniau is a company consultant for Astellas, Ipsen, Bayer, Sanofi, and Janssen; has received company speaker honoraria from Astellas, Amgen, Bayer, Sanofi, Janssen, and Ipsen; has participated in trials for Astellas, Janssen, and Bayer; has received fellowship and travel grants from Astellas, Amgen, Bayer, Sanofi, Janssen, Ipsen, and Pfizer; and has received grant and research support from Astellas, Bayer, and Janssen. Matveev has received company speaker honoraria from Sanofi and Astellas, has participated in trials for Astellas, Pfizer and Novartis. Lam is a company consultant for and has received company speaker honoraria from Pfizer, GSK, Astellas, and Ipsen. van der Poel is a company consultant for Intuitive Surgical, has participated in trials for Astellas and Steba Biotech, and has received grant and research support from Astellas. Rouvière is a company consultant for EDAP-TMS, Bracco, and Philips; has received company speaker honoraria from EDAP-TMS, Bracco, and Philips; and has participated in trials for EDAP-TMS and Bracco. Wiegel has received company speaker honoraria from Astellas, Takeda, Hexal, Ipsen, Janssen-Cilac, and Ferring. Mottet has received grant and research support from Takeda Pharmaceutical, Millenium, Astellas, Pierre Fabre, Sanofi, and Pasteur, and has received honoraria or consultation fees from Takeda Pharaceutical, Millenium, Jansen, Astellas, BMS, Bayer, Ipsen, Ferring, Novartis, Nuclétron, Pierre Fabre, Sanofi, and Zeneca. van den Bergh, Van den Broeck, Cumberbatch, Fossati, Gross, Henry, van der Kwast, Sylvester, Yuan, Schoots, Moldovan, and Marconi have nothing to disclose.
Funding/Support and role of the sponsor: None.
A correlation with radical prostatectomy specimens has demonstrated that multiparametric magnetic resonance imaging (mpMRI) has excellent sensitivity in detecting prostate cancer (PCa) with a Gleason score of ≥7 1 2 3 . As a result, prostate mpMRI is increasingly used in patients with a suspicion of PCa to localise abnormal areas before biopsy. A large body of literature has shown that targeted biopsies of suspicious lesions seen on mpMRI (TBx) improved the detection of clinically significant PCa (csPCa), at least in the repeat biopsy setting 4 5 6 . As a result, it is now recommended that an mpMRI is performed before repeat biopsy to allow TBx of suspicious lesions in addition to standard biopsies [7] .
Some authors have recently suggested that, besides improving csPCa detection, mpMRI could also be used as a triage test so that patients with negative mpMRI findings could obviate biopsy. Such a strategy remains highly controversial [8] and depends upon the negative predictive value (NPV) of mpMRI. Therefore, the European Association of Urology Prostate Cancer Guidelines Panel undertook this systematic review and meta-analysis to assess the NPV of mpMRI in patients with a suspicion of PCa and, thus, its potential role in eliminating unnecessary prostate biopsy.
Our primary aim was to systematically evaluate the performance of negative prebiopsy prostate mpMRI in predicting a negative biopsy result for overall PCa and csPCa in biopsy-naïve men and in men with previously negative biopsies. A further objective was to explore and define factors that may contribute to relevant thresholds in order to provide guidance for future studies.
The review was performed according to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) statement [9] . The review protocol was published in PROSPERO database ( http://www.crd.york.ac.uk/PROSPERO; registration number CRD42015021929). Databases searched included the Embase and OVID Medline databases, the Cochrane database of systematic reviews, and the Cochrane Central Register for Clinical Trials, covering from January 1, 2000 to February 13, 2016. Systematic or standard prostate biopsies were used as reference standards, with positive or negative cases of PCa being determined by histopathological examination. The detailed search strategy is presented in Supplement 1.
Included studies focused on men who were assessed for suspected PCa by mpMRI before undergoing prostate biopsy. Studies enrolling both biopsy-naïve men and men who had undergone previous negative biopsies were included. Prebiopsy prostate mpMRI was considered the index test and comprised T2-weighted imaging (T2WI) and at least one functional imaging technique (diffusion-weighted imaging [DWI], dynamic contrast-enhanced imaging [DCEI], or magnetic resonance spectroscopic imaging [MRSI]). For inclusion, studies had to report on false negatives and true negatives, in order to calculate NPV (ie, results of systematic/standard prostate biopsies when the mpMRI was negative). When available, false positive and true positive findings were also noted to calculate the positive predictive value (PPV) and the cancer prevalence. There was restriction neither on the biopsy technique (transrectal or transperineal) nor on the number of biopsy cores. Studies using radical prostatectomy specimens as reference standards were excluded, as were studies evaluating men with histologically proven PCa. Studies with less than 50 participants were excluded. No language restrictions were applied.
Two reviewers (P.C.M. and T.V.D.B.) independently screened all abstracts and full-text articles for eligibility. Disagreement was resolved by consensus or reference to an independent third party (L.M.). All screening was performed using a predefined eligibility form.
Using a data extraction form developed a priori, the same two reviewers independently extracted data concerning study methodology, patient characteristics, technical characteristics of the MR scanners, mpMRI protocol, mpMRI scoring system, definition of positive mpMRI, biopsy protocol, and definition of csPCa. Any discrepancies concerning data extraction were resolved by consensus or reference to an independent arbiter (O.R. or T.B.L.).
To assess the risk of bias (RoB), all included reports were reviewed using the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool for diagnostic accuracy studies [10] .
Outcome data regarding false negative and true negative values of mpMRI before prostate biopsy were recorded as reported by authors. When not available, data were indirectly derived from specificity, sensitivity, and prevalence values reported by authors using an online Bayesian statistics calculator ( http://www.medcalc.com/bayes.html ). Descriptive statistics were used to summarise baseline characteristics and outcomes, including median and interquartile range (IQR) for estimates of NPV across studies. A correlation between mpMRI NPV and a positive biopsy rate was established using the Pearson's correlation coefficient.
A meta-analysis was undertaken to calculate pooled NPV and PPV. To ensure appropriate clinical homogeneity of the studies included in the meta-analysis, we selected only the studies enrolling biopsy-naïve patients and/or patients with a history of negative biopsy, and fulfilling the following criteria that were defined a priori: (1) reference standard consisting of prostate biopsy with at least 10 samples on all patients; (2) mpMRI protocol comprising at least T2WI and DWI; (3) mpMRI results presented as a five-level score, using a subjective Likert scale or the Prostate Imaging Reporting Data System (PI-RADS) score [11] ; (4) definition of positive mpMRI as a score ≥3/5 or ≥4/5; and (5) results reported on a per patient basis. In addition, only studies defining csPCa as Gleason ≥7 cancers were selected for the meta-analysis assessing the mpMRI NPV for csPCa. A bivariate random-effects approach was employed using the Midas package in Stata 12 (StataCorp LP, College Station, TX, USA). Since the NPV decreases and the PPV increases as the prevalence increases, post-test probability estimates of NPV and PPV were reported for the given values of the prevalence based on Bayes’ theorem.
For other studies not included in the meta-analysis based on the criteria described above, a narrative synthesis of the data was performed. To explore and define clinical heterogeneity, subgroups were analysed at patient level based on the following variables: biopsy-naïve versus previous negative biopsy; patients with positive versus negative digital rectal examination (DRE); mpMRI performed with an endorectal versus without an endorectal coil; transrectal ultrasound (TRUS) versus template transperineal (TTP) biopsy approach; and ≤16 cores versus >16 cores as the reference standard. Studies reporting mpMRI NPV for patients with a prostate-specific antigen (PSA) level of ≤10 ng/ml were also reported separately.
The study selection process is depicted in the PRISMA flow diagram ( Fig. 1 ). A total of 2980 abstracts were retrieved. After abstract screening and removal of duplicates, 240 articles were eligible for full text screening, of which 48 studies were eligible for inclusion 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 .
Out of the 48 included studies, 42 were single-centre and six were multicentre studies. Thirty-four studies were prospective and six were retrospective, whilst the design of the rest was unclear. RoB assessment using QUADAS-2 was performed for each of the individual studies ( Fig. 2 A and B). Overall, the RoB was highly heterogeneous across studies for all criteria, except for the reference standard domain, in which RoB was low in most studies.
The 48 studies comprised a total of 9613 men who underwent prostate mpMRI followed by biopsy. The study and patient baseline characteristics are presented in Table 1 . The patient population consisted of biopsy-naive men in nine studies, men with at least one previous negative biopsy in 16 studies, and both biopsy-naïve men and men with a history of previous negative biopsy in nine studies. In 14 studies, the biopsy history of the patients was unclear.
Study | Study design | Period | Population | Pt Nb | Mean/median* age (yr) | Mean/median* PSA (ng/ml) | Mean/median* prostate volume (cm 3 ) | Magnetic field strength | MR pulse sequences | Endorectal coil | MR score | Definition of positive MRI | Reference standard |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Hauth (2015) [25] | Prospective | 2011–2013 | FB | 94 | 64 (43–83) | 9 (3–31) | 51 (17–140) | 1.5 T | T2WI/DWI/DCEI/MRSI | No | PI-RADS v1 | ≥3 | 11–13-core TRUS SBx + TBx |
Lamb (2015) [36] | Retrospective | 2013–2013 | FB & PNB | 173 | NR | NR | NR | 1.5 T | T2WI/DWI | NR | NR | NR | 12-core TRUS SBx |
Brock (2015) [15] | Prospective | 2013–2014 | PNB | 168 | 64* (IQR 59–70) | 9.2* (IQR 6.7–13.4) | 55.4* (IQR 42–80) | 3 T | T2WI/DWI/DCEI | No | PI-RADS v1 | NR | 12/24-core TRUS SBx + TBx |
Grenabo Bergdahl (2016) [22] | Prospective | 2013–2014 | FB & PNB | 83 | 69.3* (IQR 69–69.6) | 1.6* (IQR 0.9–2.7) | NR | 3 T | T2WI/DWI/DCEI/MRSI | No | PI-RADS v1 | ≥3 | 10-core TRUS SBx + TBx |
Wang (2015) [58] | Prospective | 2002–2009 | FB & PNB | 586 | 70 (26–91) | 11.11* (0.02–9794) | NR | 1.5 T | T2WI/DWI/DCEI/MRSI | Yes | PI-RADS v1 | ≥3 | TRUS SBx |
Pepe (2015) [41] | Prospective | 2011–2014 | PNB | 100 | 64* | 8.6* (4.2–10) | NR | 3 T | T2WI/DWI/DCEI/MRSI | No | PI-RADS v1 | ≥4 | TPBx + TBx |
Panebianco (2015) [39] | Prospective | 2011–2014 | FB (61.62%) & PNB (38.34%) | 925 (1140 total cohort) |
NR | NR | NR | 3 T | T2WI/DWI/DCEI | Yes | PI-RADS v1 | NR | 14-core TRUS SBx; 45-core sat TPBx + TBx |
Radtke (2015) [46] | Prospective | 2013–2013 | FB (63.3%) & PNB (36.7%) | 294 | 64* (60–71) | 7.3 (6.0) | 47 (37.5) | 3 T | T2WI/DWI/DCEI | No | PI-RADS v1 | PI-RADS ≥2; PI-RADS ≥3; PI-RADS ≥4; PI-RADS = 5; |
24-core TPBx + TBx |
Itatani (2014) [27] | Retrospective | 2004–2007 | NR | 193 | 68.9 (8.4); 70* (47–89) | 11.8 (15.9); 7.9* (1.22–159) | NR | 1.5 T | T2WI/DWI/DCEI | No | 1–5 scale (Likert) | ≥3 | 12–14-core TRUS SBx |
Porpiglia (2014) [44] | Prospective | 2011–2013 | PNB | 170 | 65* (60–70) | 6.9* (5.2–9.8) | 42* (36–48) | 1.5 T | T2WI/DWI/DCEI | Yes | Dichotomous | Positive: at least 2/3 MR seq. with suspicious findings | 18–24-core TRUS SBx (volume dependent) |
Thompson (2014) [56] | Prospective | 2012–2013 | FB (88%) & PNB (12%) | 150 | 62.4* (IQR 55.0–66.4) | 5.6* (IQR 4.5–7.5) | 40* (IQR 30–57) | 1.5 T (47%) & 3 T (53%) | T2WI/DWI/DCEI | No | PI-RADS v1 | ≥3 | Median of 30 TPBx (volume dependent) |
Pokorny (2014) [43] | Prospective | 2012–2013 | FB | 223 | 63* (IQR 57–68) | 5.3* (IQR 4.1–6.6) | 41* (IQR 30–59) | 3 T | T2WI/DWI/DCEI | No | PI-RADS v1 | ≥3 (primary); ≥4 |
12-core TRUS SBx + TBx |
Petrillo (2014) [42] | Prospective | 2009–2010 | NR | 136 | NR | NR | NR | 1.5 T | T2WI/DWI/MRSI | Yes | 1–5 scale (Likert) | ≥3 | 12–16-core TRUS SBx (volume + PSA dependent) |
Javali (2014) [29] | Retrospective | 2002–2011 | NR | 140 | Control: 62.4 (10.5); Study: 62.9 (12.1) | Control: 6.8 (2.3); Study: 6.87 (2.6) | Control: 44 (14.2); Study: 43 (18.4) | 1.5 T | T2WI/MRSI | Yes | Dichotomous | Cit/[Cho + Cr] < 1.2 | 6-core TRUS SBx ( n = 69), 12-core TRUS SBx ( n = 119) |
Abd-Alazeez (2014) [13] | Prospective | 2007–2011 | FB | 129 | 62* (41–82) | 5.8* (1.2–20) | 40* (16–137) | 1.5 & 3 T | T2WI/DWI/DCEI | No | PI-RADS v1 | ≥3 (primary); ≥4 |
20-core TPBx |
Abd-Alazeez (2014) [12] | Retrospective | NR | PNB | 54 | 64* (39–75) | 10* (2–23) | 53* (19–136) | 1.5 & 3 T | T2WI/DWI/DCEI | No | PI-RADS v1 | ≥3 (primary); ≥4 |
≥20-core TPBx + TBx ( n = 15) |
Matsuoka (2014) [37] | Prospective | 2007–2012 | NR | 135 | 67* (50–80) | 7.0* (2.9–19.8) | 25.4* (12.7–90.2) | 1.5 T | T2WI/DWI | No | 1–5 scale (Likert) | ≥3 | 14-core TRUS SBX |
Junker (2013) [30] | Retrospective | 2011–2013 | PNB | 73 | 62 (7.4) | 7.0* (5.1–12.9) | 45* (34–61) | 3 T | T2WI/DWI/DCEI | No | PI-RADS | PI-RADS ≥10 and ≥11 for all PCa PI-RADS ≥13 for significant PCa |
10-core TRUS SBx + TBx |
Busetto (2013) [16] | Prospective | 2010–2012 | PNB | 163 | 66.4 (5.3) | 6.8 (1.6) | NR | 3 T | T2WI/DWI/DCEI/MRSI | Yes | NR | NR | 10-core TRUS SBx + TBx |
Rais-Bahrami (2013) [47] | Prospective | 2007–2012 | NR | 583 | 61.3 (8.4) | 9.9 (13.1) | NR | 3 T | T2WI/DWI/DCEI/MRSI | Yes | 1–4 scale (Likert) | ≥2 ≥3 |
12-core TRUS SBx + TBx |
Kuru (2013) [34] | Prospective | 2010–2011 | FB (51%) & PNB (49%) | 347 | 65.3 (42–82) | 9.85 (0.5–104) | 48.7 (9–180) | 3 T | T2WI/DWI/DCEI | No | 1–3 scale (Likert) | ≥2 | 12–36-core TRUS SBx (volume dependent) + TBx |
Ferda (2013) [20] | Prospective | NR | NR | 164 | (49–74) | (4.2–123) | NR | 3 T | T2WI/DWI/DCEI/MRSI | No | NR | In house | TRUS SBx |
Ganie (2013) [21] | NR | 2007–2009 | PNB | 87 | NR | NR | NR | 1.5 T | T2WI/MRSI | Yes | MRSI Cho/Cit ratio | In house | 6 core TRUS SBx + MRI TBx |
Vinet (2013) [57] | Prospective | 2009–2011 | FB | 69 | NR | 5.2* (3.2–28) | NR | 1.5 T (35 pts) & 3 T (34 pts) | T2WI/DWI/DCEI | No | 1–5 scale (Likert) | ≥3 | 12-core TRUS SBx + TBx |
Numao (2013) [38] | Prospective | 2006–2010 | FB | 351 | 65* (59–70) | 6.3* (4.9–9.1) | 32* (24–42) | 1.5 T | T2WI/DWI/DCEI (no DCEI in 42 pts) | No | 1–5 scale (Likert) | ≥3 | 3D 26-core (12 TRUS SBx + 14 TPBx – 203 pts); 3D 14-core (6 TRUS SBx + 8 TPBx – 102 pts); TPBx 14 core (46 pts) |
Belas (2012) [14] | Prospective | 2010–2011 | FB | 71 | 66* (47–76) | 7* (4–10) | 45* (15–150) | 1.5 T | T2WI/DWI/DCEI | No | TZ: 0–4 scale PZ: 0–10 scale |
TZ: >2 PZ: >6 |
12-core TRUS SBx + TBx |
Ibrahiem (2012) [26] | Prospective | 2008–2009 | FB | 100 | 65.03 (7.13) | 26.3 (24.2) | 60.09 (28.7) | 1.5 T | T2WI/DWI | No | NR | In house | 12-core TRUS SBX |
Sciarra (2012) [51] | Prospective | 2008–2011 | PNB | 84 | 64.09 (46–76) | 7.07 (4.2–15.5) | NR | 3 T | T2WI/DWI/DCEI/MRSI | Yes | NR | NR | 10-core TRUS Bx + TBx |
Portalez (2012) [45] | Prospective | 2011 | PNB | 129 | 64.7 (47–79) | 9.6 (2.7–40) | 51.1 (12–192) | 1.5 T | T2WI/DWI/DCEI | Mixed | 1–5 scale (Likert) PI-RADS |
Likert ≥3 PI-RADS ≥9 |
10–12-core TRUS SBx + TBx |
Watanabe (2012) [59] | Prospective | 2004–2008 | NR | 1448 | 72 (7.5) | NR | NR | 1.5 T | T2WI/DWI | No | NR | ADC value ≤1.35 × 10 −3 mm 2 /s | 8-core TRUS SBx + TBx |
Tamada (2011) [54] | Retrospective | 2006–2009 | NR | 50 | 70 (40–84) | 6.84* (4.06–9.94) | NR | 1.5 T | T2WI/DWI/DCEI | No | NR | In house | 12-core TRUS SBx |
Choi (2011) [18] | NR | 2009–2010 | NR | 51 | 67.16 (56–90) | 14.16 (1.02–38.9) | 42.98 (13.8–77.3) | 3 T | T2WI/DWI | NR | NR | NR | 10–12-core TRUS SBx + TBx |
Iwazawa (2011) [28] | Retrospective | 2008–2009 | NR | 178 | 68.8 (41–86) | 20.51 (4.04–568.5) | NR | 1.5 T | T2WI/DWI/DCEI | NR | 1–4 scale (Likert) | NR | 10–12-core TRUS SBx (TBx included in SBx chart) |
Rouse (2011) [48] | Prospective | 2005–2007 | PNB | 114 | 63.6 (41–83) | 13.4 (0–228) | NR | 1.5 T | T2WI/DWI/DCEI | NR | 1–5 scale (Likert) | ≥3 | TRUS SBx |
Haffner (2011) [23] | Prospective | 2005–2009 | FB | 555 | 64* (47–83) | 6.75* (0.18–100) | 46* (15–200) | 1.5 T | T2WI/DCEI | No | 1–5 scale (Likert) | ≥3 | 10-core TRUS SBx + TBx |
Panebianco (2010) [40] | Prospective | 2007–2009 | PNB | 150 | 61.2 (46–78) | 9.42 (3.91) | 41.17 (7.47) | 1.5 T | T2WI/DCEI/MRSI | Yes | NR | In house | 10-core TRUS SBx (TBx included in SBx chart) |
Roy (2010) [49] | Not specified | 2011–2009 | FB (53%) & PNB (47%) | 103 | 63 (52–78) | 7* | NR | 3 T | T2WI/DWI/DCEI | Yes | NR | NR | 8-core TRUS SBx + TBx |
Testa (2010) [55] | Not specified | 2007 | PNB | 54 | 63.9 (52–76) | 11.4 (3–42) | 59.3 (30–150) | 1.5 T | T2WI/MRSI | Yes | 1–3 scale (Likert) | ≥2 | 12-core TRUS SBx + TBx |
Sciarra (2010) [52] | Prospective | 2007–2009 | PNB | 110 | 63.5 (49–74) | NR | NR | 1.5 T | T2WI/DCEI/MRSI | Yes | NR | In house | 10-core TRUS SBx + TBx |
Kitajima (2010) [31] | Prospective | 2008–2009 | NR | 53 | 69* (56–84) | 11.1* (4.2–112.1) | NR | 3 T | T2WI/DWI/DCEI | No | 1–5 scale (Likert) | ≥3 | 20-core TPBx |
Labanaris (2010) [35] | Prospective | 2004–2008 | PNB | 260 | NR | NR | NR | 1 T | T2WI/DWI/DCEI | Yes | Dichotomous | In house | 18-core TRUS SBx |
Kumar (2009) [32] | NR | NR | NR | 61 | 65.3 (9.3) | 16.5 (0.21–155) | NR | 1.5 T | T2WI/MRSI | Yes | NR | (Cit/(Cho + Cr) ≤ 1.2 | TRUS Bx |
Schmuecking (2009) [50] | NR | NR | FB & PNB | 67 | 68 | 11.5 | NR | 1.5 T | T2WI/DCEI | No | NR | NR | 20-core Bx |
Cheikh (2009) [17] | Retrospective | 2005–2008 | PNB | 93 | 63.2 (52–74) | 9.63 (1.6–40) | NR | 1.5 T | T2WI/DCEI | No | Dichotomous | In house | 12-core TRUS SBx + TBx |
Cirillo (2008) [19] | Prospective | 2004–2006 | PNB | 54 | 65.5 (5.2) | 10.8 (7.5) | NR | 1.5 T | T2WI/MRSI | Yes | Dichotomous | In house | 10-core TRUS SBx + TBx |
Kumar (2007) [33] | Prospective | 2003–2005 | NR | 83 | NR | NR | NR | 1.5 T | T2WI/MRSI | Yes | NR | NR | 12-core TRUS SBx + TBx |
Squillaci (2005) [53] | Prospective | 2004–2005 | NR | 65 | NR | NR | NR | 1.5 T | T2WI/DCEI/MRSI | No | 1–3 scale (Likert) | ≥2 | 10-core TRUS SBx + TBx |
Hara (2005) [24] | Prospective | 2003–2004 | FB | 90 | 67.2 (NR) | NR | NR | 1.5 T | T2WI/DCEI | No | 1–3 scale (Likert) | ≥2 = 3 |
14-core TRUS SBx |
The magnetic field strength was 1, 1.5, and 3 T in one, 28, and 15 studies, respectively. Four studies used both 1.5 and 3 T MR systems. DWI and DCEI were used in 36 and 35 studies, respectively. Nineteen studies also added MRSI. An endorectal coil was used in 18 studies. The definition of positive mpMRI varied across studies. The PI-RADS v1 score was used in 12 studies, a five-level subjective (Likert) score was used in eight studies, and one study reported data based on the two scoring systems. In-house criteria were used in 13 studies for defining positive mpMRI, and five studies used a dichotomous definition. Nine studies did not report on the criteria for positive mpMRI. No study used the PI-RADS v2 score.
Regarding the reference standard, TRUS-guided biopsies were used in 39 studies, TTP biopsies in six studies, and mixed TRUS-guided and TTP biopsies in two studies. In one study, the biopsy approach was unclear. The number of cores per biopsy procedure was ≤16 in 30 studies, >16 in nine studies, and variable among patients in three studies. For six studies, the number of biopsy cores taken was unclear.
At patient level, the median biopsy positivity rate (ie, cancer prevalence) was 50.4% (IQR, 36.4–57.7%) for overall cancer and 32.9% (IQR, 28.1–37.2%) for csPCa ( Table 2 ). The median mpMRI NPV was 82.4% (IQR, 69.0–92.4%) for overall cancer and 88.1% (IQR, 85.7–92.3) for csPCa. NPV significantly decreased when cancer prevalence increased, both for overall cancer ( r = –0.64, p < 0.0001) and csPCa ( r = –0.75, p = 0.032; Fig. 3 ). In addition, NPV was highly dependent on the definition used for csPCa, with differences of up to 21% when several definitions were used in the same dataset [12 13 38 47 48] .
Study | Overall PCa prevalence (%) | Reporting level | Multiparametric MRI performance for PCa detection | Definition of csPCa | csPCa prevalence | Multiparametric MRI performance for csPCa detection | ||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
TN | FN | TP | FP | NPV | PPV | TN | FN | TP | FP | NPV | PPV | |||||
Hauth (2015) [25] | 45.7 | Patient | 6 | 1 | 42 | 45 | 85.7% | 48.3% | Low grade: GS ≤ 6 High grade: GS ≥ 7 |
NR | NR | NR | NR | NR | NR | NR |
Lesion | 59 | 13 | 55 | 73 | 81.9% | 43% | ||||||||||
Lamb (2015) [36] | 65.9 | Patient | 23 | 22 | 92 | 36 | 51.1% | 71.9% | GS ≥ 7 | 50.9% | 31 | 14 | 71 | 57 | 68.9% | 55.5% |
Brock (2015) [15] | 42.3 | Patient | 17 | 7 | 56 | 88 | 70.8% | SBx: 38.8% TBx: 22.2% Duo: 44.4% |
Epstein: GS > 6 and/or max CCL ≥50% | 24.4% | SBx: 21 | SBx: 3 | SBx: 38 TBx: 27 duo: 47 |
SBx: 106 TBx: 117 duo: 97 |
87.5% | SBx: 26.4% TBx: 18.8% duo: 32.6% |
Grenabo Bergdahl (2016) [22] | 33.7 | Patient | 36 | 7 | 19 | 21 | 83.7% | 47.5% | Clinically insignificant PCa: T1c, PSAd < 0.15, GS < 7, ≤2 positive cores, and unilateral cancer | NR | NR | NR | NR | NR | NR | NR |
Wang (2015) [58] | 58 | Patient | 165 | 8 | 332 | 81 | 95.4% | 80.4% | NR | NR | NR | NR | NR | NR | NR | NR |
Pepe (2015) [41] | 37 | Patient | 23 | 8 | 29 | 40 | 74.2% | 42% | GS ≥ 7 or GS 6 with CCL ≥ 50% | NR | NR | NR | NR | NR | 100% | 55.8% |
Panebianco (2015) [39] | 74.7 | Patient | Group A (satBx): 104 | Group A (satBx): 43 | Group A: 186 | Group A: 22 | Group A (satBx): 70.7% | Group A: 89.4% | NR | 60% | Group A: 147 | Group A: 0 | Group A: 183 | Group A: 25 | Group A: 100% | Group A: 88% |
Group B (TRUSGB NR TRUS G satBx): 93 | Group B (TRUSGB NR TRUS G satBx): 37 | Group B: 417 before and 425 after satBx | Group B: 23/440 and 15/440 after satBx. | Group B (TRUSGB–TRUS G satBx): 71.5% | Group B: 94.8% before and 96.6% after satBx | 71.9% | Group B: 130 | Group B: 0 | Group B: 410 |
Group B: 30 | Group B: 100% | Group B: 93.2% | ||||
Radtke (2015) [46] | 51 | Patient | ≥2/5: 80 ≥3: 103 ≥4: 138 = 5: 142 |
≥2/5: 18 ≥3/5: 38 ≥4/5: 78 = 5/5: 126 |
≥2/5: 132 ≥3/5: 112 ≥4/5: 72 = 5/5: 24 |
≥2/5: 64 ≥3/5: 41 ≥4/5: 6 = 5/5: 2 |
≥2/5: 81.6% ≥ 3/5: 73.1% ≥ 4/5: 63.9% = 5/5: 53% |
≥2/5: 67.4% ≥ 3/5: 73.2% ≥ 4/5: 92.3% = 5/5: 92.3% |
GS ≥ 7 | 29.3% | ≥2/5: 91 ≥3/5: 124 ≥4/5: 183 = 5/5: 203 |
≥2/5: 7 ≥3/5: 17 ≥4/5: 33 = 5/5: 65 |
≥2/5: 79 ≥3/5: 69 ≥4/5: 53 = 5/5: 21 |
≥2/5: 117 ≥3/5: 84 ≥4/5: 25 = 5/5: 5 |
≥2/5: 92.2% ≥3/5: 87.9% ≥4/5: 84.7% = 5/5: 75.8% |
≥2/5: 40.3% ≥3/5: 45.1% ≥4/5: 68% = 5/5: 80.7% |
Itatani (2014) [27] | 13 | Patient | 168 | 25 | NR | NR | 87% | NR | (1) PSAd ≥ 0.1 or GP 4/5 or ≥ 3/6 pos cores; max CCL < 50% (2) PSAd ≥ 0.15 or GP 4/5 or max core length invasion < 3 mm (min 6 cores) |
NR | NR | NR | NR | NR | NR | NR |
Porpiglia (2014) [44] | 30.6 | Patient | 107 | 5 | 47 | 11 | 95.5% | 81% | NR | NR | NR | NR | NR | NR | NR | NR |
Thompson (2014) [56] | 61.3 | Patient | 35 | 16 | 76 | 23 | 68.6% | 76.7% | Moderate or high risk Moderate risk: GS 7 (GP4 >5%) and <50% of positive cores or GS 6–7 (GP4 ≤ 5%) and either ≥30% of positive cores or max core length invasion ≥8 mm High risk: GS ≥ 7 (GP4 > 5%); ≥50% + cores or GS ≥ 8 |
34% | 49 | 2 | 49 | 50 | 96% | 49.5% |
Pokorny (2014) [43] | 63.7 | Patient | ≥3/5: 56 ≥4/5: 74 |
≥3/5: 25 ≥4/5: 40 |
≥3/5: 101 ≥4/5: 86 |
≥3/5: 41 ≥4/5: 23 |
≥3/5: 69.1% ≥4/5: 64.9% |
≥3/5: 71.1% ≥4/5: 78.9% |
NR | NR | NR | NR | NR | NR | NR | NR |
Petrillo (2014) [42] | 18.4 | Patient | 56 | 4 | 21 | 55 | 93% | 28% | NR | NR | NR | NR | NR | NR | NR | NR |
Javali (2014) [29] | 16.4 | Patient | 49 | 1 | 22 | 68 | 98% | 24.4% | NR | NR | NR | NR | NR | NR | NR | NR |
Abd-Alazeez (2014) [13] | 54.7 | Lobe | ≥3/5: 33 | ≥3/5: 14 | ≥3/5: 127 | ≥3/5: 84 | ≥3/5: 70% | ≥3/5: 60% | Def 1: GS ≥ 4 + 3 and/or max CCL ≥ 6 mm Def 2: GS ≥ 3 + 4 and/or max CCL ≥ 4 mm Def 3: GS ≥ 4 + 3 Def 4: GS ≥ 3 + 4 Def 5: max CCL ≥ 6 mm Def 6: max CCL ≥ 4 mm |
Def 1: NR Def 2: 44.2% Def 3: 23.2% Def 4: 36% Def 5: 32.9% Def 6: 39.5% |
Def 1: 46 Def 2: 42 Def 3: 47 Def 4: 43 Def 5: 46 Def 6: 43 |
Def 1: 1 Def 2: 5 Def 3: 0 Def 4: 4 Def 5: 1 Def 6: 4 |
Def 1: 45 Def 2: 72 Def 3: 13 Def 4: 50 Def 5: 39 Def 6: 59 |
Def 1: 166 Def2: 139 Def 3: 198 Def 4: 161 Def 5: 172 Def 6: 152 |
Def 1: 98 Def 2: 89 Def 3: 100 Def 4: 92 Def 5: 98 Def 6: 91 |
Def 1: 21 Def 2: 34 Deg 3: 6 Def 4: 24 Def 5: 19 Def 6: 28 |
≥4/5: 87 | ≥3/5: 62 | ≥3/5: 79 | ≥3/5: 30 | ≥3/5: 58% | ≥3/5: 73% | Def 1: 140 Def 2: 124 Def 3: 148 Def 4: 133 Def 5: 141 Def 6: 131 |
Def 1: 9 Def 2: 25 Def 3: 1 Def 4: 16 Def 5: 8 Def 6: 18 |
Def 1: 37 Def 2: 52 Def 3: 12 Def 4: 38 Def 5: 32 Def 6: 45 |
Def 1: 72 Def 2: 57 Def 3: 97 Def 4: 71 Def 5: 77 Def 6: 64 |
Def 1: 94 Def 2: 83 Def 3: 99 Def 4: 89 Def 5: 95 Def 6: 88 |
Def 1: 34 Def 2: 48 Def 3: 11 Def 4: 35 Def 5: 30 Def 6: 42 |
|||||
Abd-Alazeez (2014) [12] | 47.2 | Lobe | ≥3/5: 26 | ≥3/5: 13 | ≥3/5: 38 | ≥3/5: 31 | ≥3/5: 66% | ≥3/5: 55% | Def 1: GS ≥ 4 + 3 and/or max CCL ≥ 6 mm Def 2: GS ≥ 3 + 4 and/or max CCL ≥ 4 mm Def 3: GS ≥ 4 + 3 Def 4: GS ≥ 3 + 4 Def 5: max CCL ≥ 6 mm Def 6: max CCL ≥ 4 mm |
Def 1: 18.5% Def 2: 31.5% Def 3: 4.6% Def 4: 21.3% Def 5: 16.7% Def 6: 25% |
Def 1: 37 Def 2: 31 Def 3: 39 Def 4: 36 Def 5: 37 Def 6: 32 |
Def 1: 2 Def 2: 8 Def 3: 0 Def 4: 3 Def 5: 2 Def 6: 7 |
Def 1: 18 Def 2: 26 Def 3: 5 Def 4: 20 Def 5: 16 Def 6: 20 |
Def 1: 51 Def 2: 43 Def 3: 64 Def 4: 49 Def 5: 53 Def 6: 49 |
Def 1: 95 Def 2: 79 Def 3: 100 Def 4: 92 Def 5: 95 Def 6: 82 |
Def 1: 26 Def 2: 38 Def 3: 7 Def 4: 29 Def 5: 23 Def 6: 29 |
≥4/5: 49 | ≥4/5: 25 | ≥4/5: 26 | ≥4/5: 8 | ≥4/5: 66% | ≥4/5: 76% | Def 1: 70 Def 2: 63 Def 3: 73 Def 4: 68 Def 5: 70 Def 6: 64 |
Def 1: 4 Def 2: 11 Def 3: 1 Def 4: 6 Def 5: 4 Def 6: 10 |
Def 1: 16 Def 2: 23 Def 3: 4 Def 4: 17 Def 5: 14 Def 6: 17 |
Def 1: 18; Def 2: 11 Def 3: 30 Def 4: 17 Def 5: 20 Def 6: 17 |
Def 1: 94 Def 2: 85 Def 3: 99 Def 4: 92 Def 5: 94 Def 6: 86 |
Def 1: 47 Def 2: 67 Def 3: 12 Def 4: 50 Def 5: 41 Def 6: 49 |
|||||
Matsuoka (2014) [37] | 64.8 | Lobe | 46 | 49 | 149 | 26 | 48.4% | 85.1% | NR | NR | NR | NR | NR | NR | NR | NR |
Junker (2013) [30] | 53.4 | Patient | ≥10/15: 21 ≥11/15: 28 |
≥10/15: 4 ≥11/15: 12 |
≥10/15: 35 ≥11/15: 27 |
≥10/15: 13 ≥11/15: 6 |
≥10/15: 84% ≥11/15: 70% |
≥10/15: 72.9% ≥11/15: 81.8% |
GS ≥ 4 + 3 | 13.7% | ≥13: 54 | ≥13: 2 | ≥13: 8 | ≥13: 9 | ≥13: 96.4% | ≥13: 47% |
Busetto (2013) [16] | 41.7 | Patient | 59 | 7 | 61 | 36 | 89% | 63% | NR | NR | NR | NR | NR | NR | NR | NR |
Rais-Bahrami (2013) [47] | 54.2 | Patient | ≥2/4 : 80 | ≥2/4: 275 | ≥2/4: 187 | ≥2/4: 275 | ≥2/4: 66% | ≥2/4: 59% | GS ≥ 7: GS ≥ 8 |
31.7% | NR | NR | NR | NR | GS ≥ 7: 91% GS ≥ 8: 91% |
GS ≥ 7: 38% GS ≥ 8: 18% |
≥3/4: 251 | ≥3/4: 76 | ≥3/4: 16 | ≥3/4: 76 | ≥3/4: 51% | ≥3/4: 82% | NR | NR | NR | NR | GS ≥ 7: 75% GS ≥ 8: 91% |
GS ≥ 7: 67% GS ≥ 8: 41% |
|||||
Kuru (2013) [34] | 57.6 | Patient | 80 | 14 | 67 | 186 | 85.1% | 73.5% | NR | NR | NR | NR | NR | NR | NR | NR |
Ferda (2013) [20] | 51.2 | Patient | 52 | 2 | 82 | 28 | 96.3% | 74.5% | NR | NR | NR | NR | NR | NR | NR | NR |
Ganie (2013) [21] | 74.7 | Patient | 13 | 3 | 62 | 9 | 59.1% | 95.4% | NR | NR | NR | NR | NR | NR | NR | NR |
Vinet (2013) [57] | 49.3 | Patient | ≥3/5: 11 | ≥3/5: 6 | ≥3/5: 28 | ≥3/5: 24 | ≥3/5: 64.7% | ≥3/5: 53.8% | NR | NR | NR | NR | NR | NR | NR | NR |
≥4/5: 22 | ≥4/5: 11 | ≥4/5: 23 | ≥4/5: 13 | ≥4/5: 66.7% | ≥4/5: 63.8% | NR | NR | NR | NR | NR | NR | NR | NR | |||
Numao (2013) [38] | 45 | Patient | 137 | 57 | 101 | 56 | 70.6% | 64.3% | Def 1: GS ≥4 + 3 and/or ≥20% positive cores and/or max CCL ≥5 mm Def 2: GS ≥ 3 + 4 and/or ≥20% + cores and/or max CCL ≥5 mm Def 3: GS ≥ 3 + 4 and/or ≥20% + cores |
Def 1: 33.3% Def 2:37.8% Def 3: 35.8% |
Def 1: 74 Def 2: 65 Def 3: 69 |
Def 1: 83 Def 2: 92 Def 3: 88 |
Def 1: 160 Def 2: 153 Def 3: 156 |
Def 1: 34 Def 2: 41 Def 3: 38 |
Def 1: 82.4% Def 2: 78.8% Def 3: 80.4% |
Def 1: 58.8% Def 2: 58.5% Def 3: 56% |
Belas (2012) [14] | 53.5 | Patient | 22 | 12 | 23 | 13 | 64.7% | 63.8% | NR | NR | NR | NR | NR | NR | NR | NR |
Ibrahiem (2012) [26] | 73.9 | Patient | 14 | 11 | 57 | 10 | 56% | 85.1% | NR | NR | NR | NR | NR | NR | NR | NR |
Sciarra (2012) [51] | 34.5 | Patient | 41 | 4 | 25 | 14 | 91.1% | 64.1% | NR | NR | NR | NR | NR | NR | NR | NR |
Portalez (2012) [45] | 48.1 | Lesion | Likert: 357 | Likert: 50 | Likert: 81 | Likert: 50 | Likert: 95% | Likert: 38% | Max CCL >3 mm and/or GG 4/5 | NR | NR | NR | NR | NR | NR | NR |
PI-RADS: 404 | PI-RADS: 47 | PI-RADS: 34 | PI-RADS: 47 | PI-RADS: 95% | PI-RADS: 58% | |||||||||||
Watanabe (2012) [59] | 48.1 | Patient | 485 | 73 | 624 | 266 | 86.9% | 70.1% | NR | NR | NR | NR | NR | NR | NR | NR |
Tamada (2011) [54] | 70 | Patient | 12 | 6 | 29 | 3 | 67% | 91% | NR | NR | NR | NR | NR | NR | NR | NR |
Region | 277 | 48 | 55 | 20 | 85% | 73% | ||||||||||
Choi (2011) [18] | 70.6 | Patient | 9 | 5 | 31 | 6 | 64.2% | 75.7% | NR | NR | NR | NR | NR | NR | NR | NR |
Iwazawa (2011) [28] | 40.5 | Region | 887 | 86 | 232 | 219 | 91.1% | 51.4% | NR | NR | NR | NR | NR | NR | NR | NR |
Rouse (2011) [48] | 33.7 | Sextant | 145 | 11 | 74 | 22 | 92.9% | 77.1% | GS ≥ 7: Def 1: ≥3 mm Def 2: ≥5 mm |
Def 1: 26.6% Def 2: 26.2% |
Def 1: 153 Def 2: 153 |
Def 1: 3 Def 2: 3 |
Def 1: 64 Def 1: 63 |
Def 1: 32 Def 2: 33 |
Def 1: 98.1% Def 2: 98.1% |
Def 1: 68.1% Def 2: 67% |
59.6 | Patient | 24 | 14 | 54 | 22 | 63.2% | 71.1% | Def 1: 41.2% Def 2: 36.8% |
Def 1: 30 Def 2: 31 |
Def 1: 4 Def 2: 3 |
Def 1: 43 Def 2: 39 |
Def 1: 4 Def 2: 3 |
Def 1: 88.2% Def 2: 91.2% |
Def 1: 53.8% Def 2: 48.8% |
||
Haffner (2011) [23] | 54.4 | Patient | 154 | 50 | 240 | 111 | 75.4% | 68.3% | NR | NR | NR | NR | NR | NR | NR | NR |
Panebianco (2010) [40] | 42.7 | Patient | NR | NR | NR | NR | 95.1% | 88.2% | NR | NR | NR | NR | NR | NR | NR | NR |
Roy (2010) [49] | 55.9 | Patient | NR | NR | NR | NR | 71% | 75% | NR | NR | NR | NR | NR | NR | NR | NR |
Testa (2010) [55] | 40.7 | Patient | NR | NR | NR | NR | 79.3% | 64% | NR | NR | NR | NR | NR | NR | NR | NR |
Sciarra (2010) [52] | 50 | Patient | 61 | 4 | 66 | 9 | 93.8% | 88% | NR | NR | NR | NR | NR | NR | NR | NR |
Kitajima (2010) [31] | 56.6 | Patient | 311 | 19 | 80 | 14 | 92.2% | 85.1% | NR | NR | NR | NR | NR | NR | NR | NR |
Labanaris (2010) [35] | 73.9 | Patient | 17 | 73 | 96 | 74 | 81.11% | 56.47% | NR | NR | NR | NR | NR | NR | NR | NR |
Kumar (2009) [32] | 21.7 | Patient | 39 | 3 | 10 | 8 | 92.8% | 55% | NR | NR | NR | NR | NR | NR | NR | NR |
Schmuecking (2009) [50] | NR | Lobe | NR | NR | NR | NR | 96% | 61% | NR | NR | NR | NR | NR | NR | NR | NR |
Cheikh (2009) [17] | 24.7 | Patient | 36 | 12 | 11 | 34 | 80% | 22.9% | NR | NR | NR | NR | NR | NR | NR | NR |
Cirillo (2008) [19] | 31.5 | Patient | 19 | 0 | 17 | 18 | 100% | 48.6% | NR | NR | NR | NR | NR | NR | NR | NR |
Kumar (2007) [33] | 13.3 | Patient | 39 | 0 | 11 | 33 | 100% | 25% | NR | NR | NR | NR | NR | NR | NR | NR |
Squillaci (2005) [53] | 50.8 | Patient | 29% | 8% | 25% | 3% | 89% | 80% | NR | NR | NR | NR | NR | NR | NR | NR |
Hara (2005) [24] | 41.5 | Patient | ≥2/3: 40 = 3/3: 47 |
≥2/3: 4 = 3/3: 8 |
≥2/3 30 = 3/3: 26 |
≥2/3: 8 = 3/3: 1 |
≥2/3: 90% = 3/3: 85% |
≥2/3: 78.9% = 3/3: 96.3% |
NR | NR | NR | NR | NR | NR | NR | NR |
Cancer prevalence tended to be higher and mpMRI NPV lower in the biopsy-naïve group as compared with the repeat biopsy group, in men with positive DRE as compared with men with negative DRE and when an endorectal coil was not used ( Table 3 ). There were no clear differences in the prevalence and NPV of the other analysed subgroups (TRUS-guided vs TTP biopsy, biopsy procedures with ≤16 cores vs >16 cores; Table 3 ). However, comparisons must be interpreted with care, due to the small number of studies in some subgroups. In patients with a PSA level of ≤10 ng/ml, the median NPV for overall PCa was 86.3% (IQR, 73.3–93.6%) for a median cancer prevalence of 35.4% (IQR, 27.6–42.5%).
Nb of studies | Median PCa prevalence | Median mpMRI NPV | Nb of studies | Median csPCa prevalence | Median mpMRI NPV | |
---|---|---|---|---|---|---|
Biopsy-naïve patients | 8 | 51.4% (45.5–56.7) | 69.9% (64.2–78) | 1 | 35.8% (NA) | 80.4% (NA) |
Repeat biopsy | 14 | 42% (35.1–52.6) | 82.6% (75.5–93.1) | 3 | 24.4% (19.1–32.8) | 88.2% (87.9–92.3) |
TRUS-guided biopsy | 36 | 49.7% (34.3–57.7) | 84.6% (68.6–92.8) | 4 | 28.1% (21.7–36.5) | 89.3% (82.9–92.4) |
TTP biopsy | 4 | 53.8% (47.5–57.8) | 73.6% (72–78.7) | 2 | 31.6% (30.5–32.8) | 92% (89.9–94) |
Biopsy with ≤16 cores | 28 | 48.7% (39.2–54.8) | 81.9% (66.8–89.3) | 5 | 28.1% (21.8–36.5) | 89.3% (82.9–92.4) |
Biopsy with >16 cores | 5 | 56.6% (51–61.3) | 81.1% (73.1–92.2) | 2 | 31.7% (30.5–32.8) | 92% (89.9–93.9) |
Positive DRE | 1 | 73.9% (NA) | 56% (NA) | 0 | – | – |
Negative DRE | 6 | 36% (34.6–46.8) | 82.7% (74.2–93.1) | 0 | – | – |
Endorectal coil | 17 | 41.7% (30.6–55.9) | 92.8% (79.3–95.4) | 1 | 31.7% (NA) | 91% (NA) |
No endorectal coil | 22 | 50.9% (41.7–56.1) | 77.7% (69.5–86.6) | 7 | 34% (26.9–46.1%) | 87.9% (78.2–92.1) |
Eight studies reported NPV at patient level for overall PCa and fulfilled the inclusion criteria for meta-analysis ( Table 4 ) [22 25 38 41 43 46 56 57] .
Study | Prevalence a (%) | Neg MRI (%) | NPV (%) | PPV (%) | Spe (%) | Se (%) | ||
---|---|---|---|---|---|---|---|---|
All PCa | Score ≥ 3/5 | Grenabo Bergdahl (2016) [22] | 31.3 | 66.9 | 83.7 | 47.5 | 63.2 | 73.1 |
Numao (2013) [38] | 45 | 29.4 | 70.6 | 64.3 | 71.0 | 63.9 | ||
Hauth (2015) [25] | 45.7 | 14.3 | 85.7 | 48.3 | 11.8 | 97.7 | ||
Vinet (2013) [57] | 49.3 | 24.6 | 64.7 | 53.8 | 31.4 | 82.4 | ||
Radtke (2015) [46] | 51 | 27 | 73 | 73.2 | 71.5 | 74.7 | ||
Thompson (2014) [56] | 61.3 | 31.4 | 68.6 | 76.8 | 60.3 | 82.6 | ||
Pokorny (2014) [43] | 63.7 | 30.9 | 69.1 | 82.4 | 69.1 | 82.4 | ||
Score ≥ 4/5 | Pepe (2015) [41] | 37 | 31 | 74.2 | 42 | 36.5 | 78.4% | |
Vinet (2013) [57] | 49.3 | 47.8 | 66.7 | 63.9 | 62.9 | 67.6% | ||
Radtke (2015) [46] | 51 | 73.5 | 63.9 | 92.3 | 95.8 | 48% | ||
Gleason ≥7 PCa | Score ≥ 3/5 | Radtke (2015) [46] | 29.3 | 27 | 87.9 | 45.1 | 59.6 | 80.2% |
a Prevalence of overall prostate cancers (10 first lines) or Gleason ≥7 cancers (last line).
PCa = prostate cancer; MRI = magnetic resonance imaging; Neg MRI = proportion of negative magnetic resonance imaging; NPV = negative predictive value; PPV = positive predictive value; Se = sensitivity; Spe = specificity.
Seven studies used a score of ≥3/5 for defining positive mpMRI ( Fig. 4 A and B) [22 25 38 43 46 56 57] . Fig. 4 C shows the conditional probability plot of 1 – NPV and PPV as a function of overall PCa prevalence. Table 5 shows NPV and PPV estimates for the given values of PCa prevalence.
PCaPrev | PPV | NPV |
---|---|---|
0.30 | 0.43 (0.34–0.53) | 0.88 (0.77–0.99) |
0.40 | 0.54 (0.45–0.64) | 0.82 (0.70–0.94) |
0.50 | 0.64 (0.55–0.73) | 0.76 (0.64–0.88) |
0.60 | 0.73 (0.65–0.80) | 0.67 (0.56–0.79) |
0.70 | 0.81 (0.75–0.87) | 0.57 (0.47–0.67) |
0.75 | 0.84 (0.79–0.89) | 0.51 (0.42–0.59) |
Only three studies used a score of ≥4/5 for defining positive mpMRI ( Table 4 ) [41 46 57] , and a formal meta-analysis could not be performed.
Only one study reporting NPV at patient level for Gleason ≥7 cancers met the selection criteria for inclusion in the meta-analysis. It reported NPV and PPV of 87.9% and 45.1%, respectively, for a prevalence of 29.3% ( Table 4 ) [46] .
We observed a large variability in reported NPV. Many factors, such as differences in mpMRI protocols, definition of negative mpMRI, or biopsy protocols, can explain this variability. However, two major causes of variability must be pointed out. First, the cancer prevalence was highly variable, ranging at patient level from 13% to 74.7% for overall PCa, and from 13.7% to 50.9% for csPCa. This variability was observed in both the biopsy-naïve and the repeat biopsy setting. As NPV depends on prevalence, this had a major impact on reported NPV ( Fig. 3 ). Second, the definition of csPCa was highly variable from one series to another, and differences of up to 21% could be observed in NPV when different definitions of csPCa were used in the same dataset [12 13 38 47 48] .
To account for clinical heterogeneity and to further explore the clinical relevance of the results, we carefully selected studies for inclusion in the meta-analysis based on stringent criteria. Particularly, we included only studies that: (1) had biopsy protocols with at least 10 cores, since it is no longer recommended to obtain less than 10 cores per biopsy; (2) used DWI, which is the most informative technique, at least for cancers in the peripheral zone [60] ; and (3) reported mpMRI findings using a five-level score, so that negative findings could be better defined. We accepted studies using a subjective (Likert) scale because experienced readers obtained equivalent [45 61 62] or better [63] results with the Likert score than with the PI-RADS v1 score. Owing to the large variations of NPV induced by differences in definitions of csPCa, we did not include different definitions in the meta-analysis since this would have introduced unacceptable clinical heterogeneity in the results, possibly resulting in erroneous and biased estimates. We, therefore, a priori restricted the definition of csPCa to cancers with a Gleason score of ≥7, given the low lethal potential of Gleason 6 cancers [64] and the lack of consensus among pathologists on the best method to measure biopsy core invasion length [65 66] .
In this more homogeneous group of studies, the prevalence range was still large (31.3–63.7%). As a result, we modelled the evolution of NPV (and PPV) as a function of overall PCa prevalence. Unfortunately, we could not duplicate this for csPCa since only one study reporting NPV for Gleason ≥7 cancers met the inclusion criteria for meta-analysis.
We included only studies that reported the results of systematic/standard biopsy in patients with negative mpMRI and used the systematic/standard biopsy as a reference standard. It is well known that TRUS-guided biopsy harbours both random and systematic errors, as evidenced by the high rates of positivity of immediate repeat biopsy after a first series of negative biopsies [67 68] , and as confirmed recently by the PROMIS trial [69] . Therefore, using TRUS-guided biopsy as a reference standard may have overestimated the NPV of mpMRI. However, studies using radical prostatectomy specimens as a reference standard have already reported mpMRI detection rates in relation to PCa Gleason score and volume [1] . In this review, we intended to address the more pragmatic question as to whether a negative mpMRI could predict a negative subsequent biopsy. This is an important question because if the NPV of mpMRI was sufficiently high in comparison with the reference standard of systematic/standard biopsies, then in practice a negative mpMRI result could indeed avoid the need for prostate biopsy. Therefore, studies reporting only biopsy results when the mpMRI was positive (eg, obtained through MRI-targeted, guided, or fusion biopsies with added systematic biopsies) were not included in this review.
It is now well established that mpMRI is a sensitive tool for detecting aggressive PCa 1 2 3 69] . However several reasons preclude its broad use as a triage test before biopsy.
Firstly, the population referred to prostate biopsy is not standardised. The large range of reported prevalence for overall PCa and csPCa suggests substantial heterogeneity in the way patients are selected for biopsy. Owing to this heterogeneity, we did not provide a pooled estimate for mpMRI NPV. The role of mpMRI as a triage test before prostate biopsy should be evaluated in the broader context of the selection of patients with a suspicion of (aggressive) PCa. In a recent retrospective study of 514 patients, mpMRI NPV for Gleason ≥7 cancers was 91% when the PSA density was ≤0.2 ng/ml/ml, and only 71% when the PSA density was >0.2 ng/ml/ml ( p = 0.003) [70] . In another series of 288 biopsy-naïve patients, no csPCa (Gleason score ≥7 or maximum cancer core length ≥4 mm) was found in 44 patients with a PSA density of <0.15 ng/ml/ml and a PI-RADS v2 score of <3/5 [71] . We believe that such prestratification of the risk of csPCa is an interesting way for rationalising the use of mpMRI before biopsy. Patients found at very low risk would be spared both mpMRI and biopsy. Patients at a low risk—for whom mpMRI would have an NPV high enough to be used as a triage test—could avoid biopsy in case of negative mpMRI. Patients at a higher risk would need biopsy even in case of negative mpMRI. Many tools can be used to risk stratify the population of patients referred to biopsy, ranging from simple parameters such as PSA density to more complicated risk calculators [72 73] . The impact of these tools on the NPV of prebiopsy mpMRI needs to be carefully evaluated, both in the biopsy-naïve and in the repeat biopsy setting. For the moment, it is impossible to make any recommendations on the best way to risk stratify patients before referring them for mpMRI.
Secondly, the large variability in the definition of csPCa precludes any definitive conclusion on the ability of mpMRI to rule out aggressive cancer. The issue of the most appropriate definition of csPCa on biopsy is complex, since biopsy results may accurately reflect neither tumour burden nor aggressiveness. Nonetheless, there is an urgent need to standardise the histological definition(s) of csPCa, to allow meaningful comparisons between studies.
Thirdly, the specificity of mpMRI remains moderate, and there is a substantial proportion of false positives in the lesions scored 3/5 or 4/5 [1 74 75] , even with the new PI-RADS v2 score [76] . In a series of 62 patients with 116 lesions biopsied under magnetic resonance/ultrasound fusion, the overall cancer detection rates for PI-RADS v2 scores of 3/5 and 4/5 were only 15.8% and 29.8%, respectively [77] . In theory, a triage test used to rule out a disease needs to be highly sensitive for this disease. However, if its specificity is too low, it will be clinically useless since most patients will be positive, whether they have the disease or not. Therefore, if mpMRI is to be used as a triage test in the future, there is a need to improve its specificity. This could be achieved by a continuous refinement of scores [78] . Promising results in characterising csPCa have also been reported with a quantitative analysis [79] .
Finally, all published studies were conducted in specialised centres. The broad use of mpMRI as a triage test assumes good interobserver reproducibility. Unfortunately, interobserver reproducibility of existing scoring systems remains moderate [62 63 80] even with the use of the PI-RADS v2 score [80 81] . Studies evaluating on a large scale the reproducibility of mpMRI findings between expert and nonexpert centres are currently lacking.
Three systematic reviews (including two meta-analyses) regarding the role of mpMRI in localised PCa have been published recently 4 5 6 . Crucially, all three reviews focused exclusively on the sensitivity of mpMRI-targeted, guided, or fusion biopsies in diagnosing overall PCa and csPCa, using TRUS-guided prostate biopsies as reference standards. The impact of systematic biopsies on the outcome was not addressed in any of the reviews, within either the index test or the reference standard. Our review had a totally different research question and objective, focusing on NPV of mpMRI to see if a negative mpMRI can avoid the need for a prostate biopsy. As MRI-targeted/guided/fusion biopsies are not relevant if the mpMRI was negative for cancer, it can be argued that the three reviews assessed a different index test altogether. As such, we believe that the findings of this review are novel and unique, and pave the way for further focused clinical studies.
The current study represents the first systematic review addressing the role of mpMRI as a triage test before biopsy. The review elements were developed in conjunction with a multidisciplinary panel of experts (EAU Prostate Cancer Guidelines Panel), which included a patient representative, and the review was performed robustly in accordance with recognised standards. However, it is limited by the major heterogeneity of the existing literature in patient population, study design, and definitions of positive mpMRI and csPCa. It highlighted further areas of research that could help in defining the best use of mpMRI in the early detection of aggressive PCa in the future.
Although mpMRI can detect aggressive PCa with excellent sensitivity, a definitive conclusion on its role as a triage test before prostate biopsy will be possible only when three main issues are addressed. Firstly, because NPV depends on prevalence, and because overall PCa and csPCa prevalence was highly variable in the published series, it becomes mandatory to define the optimal way to pre-evaluate the risk of csPCa in patients with a suspicion of PCa. Depending on the risk category, mpMRI could then be used to obviate biopsies or not. Secondly, there is a need for consensus definitions of csPCa on biopsy findings to allow interstudy comparisons. Thirdly, although efforts have been made to standardise mpMRI technical protocols and interpretation in the past few years [11 60 76] , there is still a crucial need to improve mpMRI specificity and inter-reader reproducibility.
This systematic review was performed under the auspices of:
The European Association of Urology Guidelines Office Board
The European Association of Urology Prostate Cancer Guideline Panel
Author contributions: Olivier Rouvière had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.
Study concept and design: Rouvière, Mottet, Cornford.
Acquisition of data: Rouvière, Moldovan, Van den Broeck, Yuan.
Analysis and interpretation of data: Rouvière, Moldovan, Van den Broeck, Lam.
Drafting of the manuscript: Rouvière, Moldovan, Van den Broeck, Lam.
Critical revision of the manuscript for important intellectual content: Bellmunt, van den Bergh, Bolla, Briers, Van den Broeck, Cornford, Cumberbatch, De Santis, Fossati, Gross, Henry, Joniau, Lam, Matveev, Moldovan, van der Poel, van der Kwast, Rouvière, Schoots, Wiegel, Mottet.
Statistical analysis: None.
Obtaining funding: None.
Administrative, technical, or material support: Yuan, Sylvester, Marconi.
Supervision: None.
Other: None.
Financial disclosures: Olivier Rouvière certifies that all conflicts of interest, including specific financial interests and relationships and affiliations relevant to the subject matter or materials discussed in the manuscript (eg, employment/affiliation, grants or funding, consultancies, honoraria, stock ownership or options, expert testimony, royalties, or patents filed, received, or pending), are the following: Bellmunt is a company consultant for Janssen, Astellas, Pierre Fabre, Genentech, Merck, Ipsen, Pfizer, Novartis, and Sanofi Aventis. He has received research support from Takeda, Novartis, and Sanofi, and received travel grants from Pfizer and Pierre Fabre. Bolla has received company speaker honoraria from Ipsen and Astellas, honoraria or consultation fees from Janssen, and fellowship and travel grants from Janssen, AstraZeneca, and Astellas. Briers has received grant and research support from Ipsen, European Association of Urology, and Bayer; is an ex officio board member for Europa UOMO; is an ethics committee and advisory group member for REQUITE; is a member patient advisory board member for PAGMI; and is a member of SCA and EMA PCWP. Cornford is a company consultant for Astellas, Ipsen, and Ferring. He receives company speaker honoraria from Astellas, Janssen, Ipsen, and Pfizer; participates in trials from Ferring; and receives fellowships and travel grants from Astellas and Janssen. De Santis is a company consultant for GlaxoSmithKline, Janssen, Bayer, Novartis, Pierre Fabre, Astellas, Amgen, Eisai Inc., ESSA, Merck, and Synthon; has received company speaker honoraria from Pfizer, Takeda, Sanofi Aventis, Shionogi, Celgene, and Teva OncoGenex; has participated in trials for Pierre Fabre, Astellas, Exelixis, Bayer, and Roche; has received fellowship and travel grants from Bayer, Novartis, Ferring, Astellas, Sanofi Aventis, and Janssen; has received grant and research support from Pierre Fabre; has received honoraria from AstraZeneca; and is associated with Amgen. Joniau is a company consultant for Astellas, Ipsen, Bayer, Sanofi, and Janssen; has received company speaker honoraria from Astellas, Amgen, Bayer, Sanofi, Janssen, and Ipsen; has participated in trials for Astellas, Janssen, and Bayer; has received fellowship and travel grants from Astellas, Amgen, Bayer, Sanofi, Janssen, Ipsen, and Pfizer; and has received grant and research support from Astellas, Bayer, and Janssen. Matveev has received company speaker honoraria from Sanofi and Astellas, has participated in trials for Astellas, Pfizer and Novartis. Lam is a company consultant for and has received company speaker honoraria from Pfizer, GSK, Astellas, and Ipsen. van der Poel is a company consultant for Intuitive Surgical, has participated in trials for Astellas and Steba Biotech, and has received grant and research support from Astellas. Rouvière is a company consultant for EDAP-TMS, Bracco, and Philips; has received company speaker honoraria from EDAP-TMS, Bracco, and Philips; and has participated in trials for EDAP-TMS and Bracco. Wiegel has received company speaker honoraria from Astellas, Takeda, Hexal, Ipsen, Janssen-Cilac, and Ferring. Mottet has received grant and research support from Takeda Pharmaceutical, Millenium, Astellas, Pierre Fabre, Sanofi, and Pasteur, and has received honoraria or consultation fees from Takeda Pharaceutical, Millenium, Jansen, Astellas, BMS, Bayer, Ipsen, Ferring, Novartis, Nuclétron, Pierre Fabre, Sanofi, and Zeneca. van den Bergh, Van den Broeck, Cumberbatch, Fossati, Gross, Henry, van der Kwast, Sylvester, Yuan, Schoots, Moldovan, and Marconi have nothing to disclose.
Funding/Support and role of the sponsor: None.
A correlation with radical prostatectomy specimens has demonstrated that multiparametric magnetic resonance imaging (mpMRI) has excellent sensitivity in detecting prostate cancer (PCa) with a Gleason score of ≥7 1 2 3 . As a result, prostate mpMRI is increasingly used in patients with a suspicion of PCa to localise abnormal areas before biopsy. A large body of literature has shown that targeted biopsies of suspicious lesions seen on mpMRI (TBx) improved the detection of clinically significant PCa (csPCa), at least in the repeat biopsy setting 4 5 6 . As a result, it is now recommended that an mpMRI is performed before repeat biopsy to allow TBx of suspicious lesions in addition to standard biopsies [7] .
Some authors have recently suggested that, besides improving csPCa detection, mpMRI could also be used as a triage test so that patients with negative mpMRI findings could obviate biopsy. Such a strategy remains highly controversial [8] and depends upon the negative predictive value (NPV) of mpMRI. Therefore, the European Association of Urology Prostate Cancer Guidelines Panel undertook this systematic review and meta-analysis to assess the NPV of mpMRI in patients with a suspicion of PCa and, thus, its potential role in eliminating unnecessary prostate biopsy.
Our primary aim was to systematically evaluate the performance of negative prebiopsy prostate mpMRI in predicting a negative biopsy result for overall PCa and csPCa in biopsy-naïve men and in men with previously negative biopsies. A further objective was to explore and define factors that may contribute to relevant thresholds in order to provide guidance for future studies.
The review was performed according to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) statement [9] . The review protocol was published in PROSPERO database ( http://www.crd.york.ac.uk/PROSPERO; registration number CRD42015021929). Databases searched included the Embase and OVID Medline databases, the Cochrane database of systematic reviews, and the Cochrane Central Register for Clinical Trials, covering from January 1, 2000 to February 13, 2016. Systematic or standard prostate biopsies were used as reference standards, with positive or negative cases of PCa being determined by histopathological examination. The detailed search strategy is presented in Supplement 1.
Included studies focused on men who were assessed for suspected PCa by mpMRI before undergoing prostate biopsy. Studies enrolling both biopsy-naïve men and men who had undergone previous negative biopsies were included. Prebiopsy prostate mpMRI was considered the index test and comprised T2-weighted imaging (T2WI) and at least one functional imaging technique (diffusion-weighted imaging [DWI], dynamic contrast-enhanced imaging [DCEI], or magnetic resonance spectroscopic imaging [MRSI]). For inclusion, studies had to report on false negatives and true negatives, in order to calculate NPV (ie, results of systematic/standard prostate biopsies when the mpMRI was negative). When available, false positive and true positive findings were also noted to calculate the positive predictive value (PPV) and the cancer prevalence. There was restriction neither on the biopsy technique (transrectal or transperineal) nor on the number of biopsy cores. Studies using radical prostatectomy specimens as reference standards were excluded, as were studies evaluating men with histologically proven PCa. Studies with less than 50 participants were excluded. No language restrictions were applied.
Two reviewers (P.C.M. and T.V.D.B.) independently screened all abstracts and full-text articles for eligibility. Disagreement was resolved by consensus or reference to an independent third party (L.M.). All screening was performed using a predefined eligibility form.
Using a data extraction form developed a priori, the same two reviewers independently extracted data concerning study methodology, patient characteristics, technical characteristics of the MR scanners, mpMRI protocol, mpMRI scoring system, definition of positive mpMRI, biopsy protocol, and definition of csPCa. Any discrepancies concerning data extraction were resolved by consensus or reference to an independent arbiter (O.R. or T.B.L.).
To assess the risk of bias (RoB), all included reports were reviewed using the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool for diagnostic accuracy studies [10] .
Outcome data regarding false negative and true negative values of mpMRI before prostate biopsy were recorded as reported by authors. When not available, data were indirectly derived from specificity, sensitivity, and prevalence values reported by authors using an online Bayesian statistics calculator ( http://www.medcalc.com/bayes.html ). Descriptive statistics were used to summarise baseline characteristics and outcomes, including median and interquartile range (IQR) for estimates of NPV across studies. A correlation between mpMRI NPV and a positive biopsy rate was established using the Pearson's correlation coefficient.
A meta-analysis was undertaken to calculate pooled NPV and PPV. To ensure appropriate clinical homogeneity of the studies included in the meta-analysis, we selected only the studies enrolling biopsy-naïve patients and/or patients with a history of negative biopsy, and fulfilling the following criteria that were defined a priori: (1) reference standard consisting of prostate biopsy with at least 10 samples on all patients; (2) mpMRI protocol comprising at least T2WI and DWI; (3) mpMRI results presented as a five-level score, using a subjective Likert scale or the Prostate Imaging Reporting Data System (PI-RADS) score [11] ; (4) definition of positive mpMRI as a score ≥3/5 or ≥4/5; and (5) results reported on a per patient basis. In addition, only studies defining csPCa as Gleason ≥7 cancers were selected for the meta-analysis assessing the mpMRI NPV for csPCa. A bivariate random-effects approach was employed using the Midas package in Stata 12 (StataCorp LP, College Station, TX, USA). Since the NPV decreases and the PPV increases as the prevalence increases, post-test probability estimates of NPV and PPV were reported for the given values of the prevalence based on Bayes’ theorem.
For other studies not included in the meta-analysis based on the criteria described above, a narrative synthesis of the data was performed. To explore and define clinical heterogeneity, subgroups were analysed at patient level based on the following variables: biopsy-naïve versus previous negative biopsy; patients with positive versus negative digital rectal examination (DRE); mpMRI performed with an endorectal versus without an endorectal coil; transrectal ultrasound (TRUS) versus template transperineal (TTP) biopsy approach; and ≤16 cores versus >16 cores as the reference standard. Studies reporting mpMRI NPV for patients with a prostate-specific antigen (PSA) level of ≤10 ng/ml were also reported separately.
The study selection process is depicted in the PRISMA flow diagram ( Fig. 1 ). A total of 2980 abstracts were retrieved. After abstract screening and removal of duplicates, 240 articles were eligible for full text screening, of which 48 studies were eligible for inclusion 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 .
Out of the 48 included studies, 42 were single-centre and six were multicentre studies. Thirty-four studies were prospective and six were retrospective, whilst the design of the rest was unclear. RoB assessment using QUADAS-2 was performed for each of the individual studies ( Fig. 2 A and B). Overall, the RoB was highly heterogeneous across studies for all criteria, except for the reference standard domain, in which RoB was low in most studies.
The 48 studies comprised a total of 9613 men who underwent prostate mpMRI followed by biopsy. The study and patient baseline characteristics are presented in Table 1 . The patient population consisted of biopsy-naive men in nine studies, men with at least one previous negative biopsy in 16 studies, and both biopsy-naïve men and men with a history of previous negative biopsy in nine studies. In 14 studies, the biopsy history of the patients was unclear.
Study | Study design | Period | Population | Pt Nb | Mean/median* age (yr) | Mean/median* PSA (ng/ml) | Mean/median* prostate volume (cm 3 ) | Magnetic field strength | MR pulse sequences | Endorectal coil | MR score | Definition of positive MRI | Reference standard |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Hauth (2015) [25] | Prospective | 2011–2013 | FB | 94 | 64 (43–83) | 9 (3–31) | 51 (17–140) | 1.5 T | T2WI/DWI/DCEI/MRSI | No | PI-RADS v1 | ≥3 | 11–13-core TRUS SBx + TBx |
Lamb (2015) [36] | Retrospective | 2013–2013 | FB & PNB | 173 | NR | NR | NR | 1.5 T | T2WI/DWI | NR | NR | NR | 12-core TRUS SBx |
Brock (2015) [15] | Prospective | 2013–2014 | PNB | 168 | 64* (IQR 59–70) | 9.2* (IQR 6.7–13.4) | 55.4* (IQR 42–80) | 3 T | T2WI/DWI/DCEI | No | PI-RADS v1 | NR | 12/24-core TRUS SBx + TBx |
Grenabo Bergdahl (2016) [22] | Prospective | 2013–2014 | FB & PNB | 83 | 69.3* (IQR 69–69.6) | 1.6* (IQR 0.9–2.7) | NR | 3 T | T2WI/DWI/DCEI/MRSI | No | PI-RADS v1 | ≥3 | 10-core TRUS SBx + TBx |
Wang (2015) [58] | Prospective | 2002–2009 | FB & PNB | 586 | 70 (26–91) | 11.11* (0.02–9794) | NR | 1.5 T | T2WI/DWI/DCEI/MRSI | Yes | PI-RADS v1 | ≥3 | TRUS SBx |
Pepe (2015) [41] | Prospective | 2011–2014 | PNB | 100 | 64* | 8.6* (4.2–10) | NR | 3 T | T2WI/DWI/DCEI/MRSI | No | PI-RADS v1 | ≥4 | TPBx + TBx |
Panebianco (2015) [39] | Prospective | 2011–2014 | FB (61.62%) & PNB (38.34%) | 925 (1140 total cohort) |
NR | NR | NR | 3 T | T2WI/DWI/DCEI | Yes | PI-RADS v1 | NR | 14-core TRUS SBx; 45-core sat TPBx + TBx |
Radtke (2015) [46] | Prospective | 2013–2013 | FB (63.3%) & PNB (36.7%) | 294 | 64* (60–71) | 7.3 (6.0) | 47 (37.5) | 3 T | T2WI/DWI/DCEI | No | PI-RADS v1 | PI-RADS ≥2; PI-RADS ≥3; PI-RADS ≥4; PI-RADS = 5; |
24-core TPBx + TBx |
Itatani (2014) [27] | Retrospective | 2004–2007 | NR | 193 | 68.9 (8.4); 70* (47–89) | 11.8 (15.9); 7.9* (1.22–159) | NR | 1.5 T | T2WI/DWI/DCEI | No | 1–5 scale (Likert) | ≥3 | 12–14-core TRUS SBx |
Porpiglia (2014) [44] | Prospective | 2011–2013 | PNB | 170 | 65* (60–70) | 6.9* (5.2–9.8) | 42* (36–48) | 1.5 T | T2WI/DWI/DCEI | Yes | Dichotomous | Positive: at least 2/3 MR seq. with suspicious findings | 18–24-core TRUS SBx (volume dependent) |
Thompson (2014) [56] | Prospective | 2012–2013 | FB (88%) & PNB (12%) | 150 | 62.4* (IQR 55.0–66.4) | 5.6* (IQR 4.5–7.5) | 40* (IQR 30–57) | 1.5 T (47%) & 3 T (53%) | T2WI/DWI/DCEI | No | PI-RADS v1 | ≥3 | Median of 30 TPBx (volume dependent) |
Pokorny (2014) [43] | Prospective | 2012–2013 | FB | 223 | 63* (IQR 57–68) | 5.3* (IQR 4.1–6.6) | 41* (IQR 30–59) | 3 T | T2WI/DWI/DCEI | No | PI-RADS v1 | ≥3 (primary); ≥4 |
12-core TRUS SBx + TBx |
Petrillo (2014) [42] | Prospective | 2009–2010 | NR | 136 | NR | NR | NR | 1.5 T | T2WI/DWI/MRSI | Yes | 1–5 scale (Likert) | ≥3 | 12–16-core TRUS SBx (volume + PSA dependent) |
Javali (2014) [29] | Retrospective | 2002–2011 | NR | 140 | Control: 62.4 (10.5); Study: 62.9 (12.1) | Control: 6.8 (2.3); Study: 6.87 (2.6) | Control: 44 (14.2); Study: 43 (18.4) | 1.5 T | T2WI/MRSI | Yes | Dichotomous | Cit/[Cho + Cr] < 1.2 | 6-core TRUS SBx ( n = 69), 12-core TRUS SBx ( n = 119) |
Abd-Alazeez (2014) [13] | Prospective | 2007–2011 | FB | 129 | 62* (41–82) | 5.8* (1.2–20) | 40* (16–137) | 1.5 & 3 T | T2WI/DWI/DCEI | No | PI-RADS v1 | ≥3 (primary); ≥4 |
20-core TPBx |
Abd-Alazeez (2014) [12] | Retrospective | NR | PNB | 54 | 64* (39–75) | 10* (2–23) | 53* (19–136) | 1.5 & 3 T | T2WI/DWI/DCEI | No | PI-RADS v1 | ≥3 (primary); ≥4 |
≥20-core TPBx + TBx ( n = 15) |
Matsuoka (2014) [37] | Prospective | 2007–2012 | NR | 135 | 67* (50–80) | 7.0* (2.9–19.8) | 25.4* (12.7–90.2) | 1.5 T | T2WI/DWI | No | 1–5 scale (Likert) | ≥3 | 14-core TRUS SBX |
Junker (2013) [30] | Retrospective | 2011–2013 | PNB | 73 | 62 (7.4) | 7.0* (5.1–12.9) | 45* (34–61) | 3 T | T2WI/DWI/DCEI | No | PI-RADS | PI-RADS ≥10 and ≥11 for all PCa PI-RADS ≥13 for significant PCa |
10-core TRUS SBx + TBx |
Busetto (2013) [16] | Prospective | 2010–2012 | PNB | 163 | 66.4 (5.3) | 6.8 (1.6) | NR | 3 T | T2WI/DWI/DCEI/MRSI | Yes | NR | NR | 10-core TRUS SBx + TBx |
Rais-Bahrami (2013) [47] | Prospective | 2007–2012 | NR | 583 | 61.3 (8.4) | 9.9 (13.1) | NR | 3 T | T2WI/DWI/DCEI/MRSI | Yes | 1–4 scale (Likert) | ≥2 ≥3 |
12-core TRUS SBx + TBx |
Kuru (2013) [34] | Prospective | 2010–2011 | FB (51%) & PNB (49%) | 347 | 65.3 (42–82) | 9.85 (0.5–104) | 48.7 (9–180) | 3 T | T2WI/DWI/DCEI | No | 1–3 scale (Likert) | ≥2 | 12–36-core TRUS SBx (volume dependent) + TBx |
Ferda (2013) [20] | Prospective | NR | NR | 164 | (49–74) | (4.2–123) | NR | 3 T | T2WI/DWI/DCEI/MRSI | No | NR | In house | TRUS SBx |
Ganie (2013) [21] | NR | 2007–2009 | PNB | 87 | NR | NR | NR | 1.5 T | T2WI/MRSI | Yes | MRSI Cho/Cit ratio | In house | 6 core TRUS SBx + MRI TBx |
Vinet (2013) [57] | Prospective | 2009–2011 | FB | 69 | NR | 5.2* (3.2–28) | NR | 1.5 T (35 pts) & 3 T (34 pts) | T2WI/DWI/DCEI | No | 1–5 scale (Likert) | ≥3 | 12-core TRUS SBx + TBx |
Numao (2013) [38] | Prospective | 2006–2010 | FB | 351 | 65* (59–70) | 6.3* (4.9–9.1) | 32* (24–42) | 1.5 T | T2WI/DWI/DCEI (no DCEI in 42 pts) | No | 1–5 scale (Likert) | ≥3 | 3D 26-core (12 TRUS SBx + 14 TPBx – 203 pts); 3D 14-core (6 TRUS SBx + 8 TPBx – 102 pts); TPBx 14 core (46 pts) |
Belas (2012) [14] | Prospective | 2010–2011 | FB | 71 | 66* (47–76) | 7* (4–10) | 45* (15–150) | 1.5 T | T2WI/DWI/DCEI | No | TZ: 0–4 scale PZ: 0–10 scale |
TZ: >2 PZ: >6 |
12-core TRUS SBx + TBx |
Ibrahiem (2012) [26] | Prospective | 2008–2009 | FB | 100 | 65.03 (7.13) | 26.3 (24.2) | 60.09 (28.7) | 1.5 T | T2WI/DWI | No | NR | In house | 12-core TRUS SBX |
Sciarra (2012) [51] | Prospective | 2008–2011 | PNB | 84 | 64.09 (46–76) | 7.07 (4.2–15.5) | NR | 3 T | T2WI/DWI/DCEI/MRSI | Yes | NR | NR | 10-core TRUS Bx + TBx |
Portalez (2012) [45] | Prospective | 2011 | PNB | 129 | 64.7 (47–79) | 9.6 (2.7–40) | 51.1 (12–192) | 1.5 T | T2WI/DWI/DCEI | Mixed | 1–5 scale (Likert) PI-RADS |
Likert ≥3 PI-RADS ≥9 |
10–12-core TRUS SBx + TBx |
Watanabe (2012) [59] | Prospective | 2004–2008 | NR | 1448 | 72 (7.5) | NR | NR | 1.5 T | T2WI/DWI | No | NR | ADC value ≤1.35 × 10 −3 mm 2 /s | 8-core TRUS SBx + TBx |
Tamada (2011) [54] | Retrospective | 2006–2009 | NR | 50 | 70 (40–84) | 6.84* (4.06–9.94) | NR | 1.5 T | T2WI/DWI/DCEI | No | NR | In house | 12-core TRUS SBx |
Choi (2011) [18] | NR | 2009–2010 | NR | 51 | 67.16 (56–90) | 14.16 (1.02–38.9) | 42.98 (13.8–77.3) | 3 T | T2WI/DWI | NR | NR | NR | 10–12-core TRUS SBx + TBx |
Iwazawa (2011) [28] | Retrospective | 2008–2009 | NR | 178 | 68.8 (41–86) | 20.51 (4.04–568.5) | NR | 1.5 T | T2WI/DWI/DCEI | NR | 1–4 scale (Likert) | NR | 10–12-core TRUS SBx (TBx included in SBx chart) |
Rouse (2011) [48] | Prospective | 2005–2007 | PNB | 114 | 63.6 (41–83) | 13.4 (0–228) | NR | 1.5 T | T2WI/DWI/DCEI | NR | 1–5 scale (Likert) | ≥3 | TRUS SBx |
Haffner (2011) [23] | Prospective | 2005–2009 | FB | 555 | 64* (47–83) | 6.75* (0.18–100) | 46* (15–200) | 1.5 T | T2WI/DCEI | No | 1–5 scale (Likert) | ≥3 | 10-core TRUS SBx + TBx |
Panebianco (2010) [40] | Prospective | 2007–2009 | PNB | 150 | 61.2 (46–78) | 9.42 (3.91) | 41.17 (7.47) | 1.5 T | T2WI/DCEI/MRSI | Yes | NR | In house | 10-core TRUS SBx (TBx included in SBx chart) |
Roy (2010) [49] | Not specified | 2011–2009 | FB (53%) & PNB (47%) | 103 | 63 (52–78) | 7* | NR | 3 T | T2WI/DWI/DCEI | Yes | NR | NR | 8-core TRUS SBx + TBx |
Testa (2010) [55] | Not specified | 2007 | PNB | 54 | 63.9 (52–76) | 11.4 (3–42) | 59.3 (30–150) | 1.5 T | T2WI/MRSI | Yes | 1–3 scale (Likert) | ≥2 | 12-core TRUS SBx + TBx |
Sciarra (2010) [52] | Prospective | 2007–2009 | PNB | 110 | 63.5 (49–74) | NR | NR | 1.5 T | T2WI/DCEI/MRSI | Yes | NR | In house | 10-core TRUS SBx + TBx |
Kitajima (2010) [31] | Prospective | 2008–2009 | NR | 53 | 69* (56–84) | 11.1* (4.2–112.1) | NR | 3 T | T2WI/DWI/DCEI | No | 1–5 scale (Likert) | ≥3 | 20-core TPBx |
Labanaris (2010) [35] | Prospective | 2004–2008 | PNB | 260 | NR | NR | NR | 1 T | T2WI/DWI/DCEI | Yes | Dichotomous | In house | 18-core TRUS SBx |
Kumar (2009) [32] | NR | NR | NR | 61 | 65.3 (9.3) | 16.5 (0.21–155) | NR | 1.5 T | T2WI/MRSI | Yes | NR | (Cit/(Cho + Cr) ≤ 1.2 | TRUS Bx |
Schmuecking (2009) [50] | NR | NR | FB & PNB | 67 | 68 | 11.5 | NR | 1.5 T | T2WI/DCEI | No | NR | NR | 20-core Bx |
Cheikh (2009) [17] | Retrospective | 2005–2008 | PNB | 93 | 63.2 (52–74) | 9.63 (1.6–40) | NR | 1.5 T | T2WI/DCEI | No | Dichotomous | In house | 12-core TRUS SBx + TBx |
Cirillo (2008) [19] | Prospective | 2004–2006 | PNB | 54 | 65.5 (5.2) | 10.8 (7.5) | NR | 1.5 T | T2WI/MRSI | Yes | Dichotomous | In house | 10-core TRUS SBx + TBx |
Kumar (2007) [33] | Prospective | 2003–2005 | NR | 83 | NR | NR | NR | 1.5 T | T2WI/MRSI | Yes | NR | NR | 12-core TRUS SBx + TBx |
Squillaci (2005) [53] | Prospective | 2004–2005 | NR | 65 | NR | NR | NR | 1.5 T | T2WI/DCEI/MRSI | No | 1–3 scale (Likert) | ≥2 | 10-core TRUS SBx + TBx |
Hara (2005) [24] | Prospective | 2003–2004 | FB | 90 | 67.2 (NR) | NR | NR | 1.5 T | T2WI/DCEI | No | 1–3 scale (Likert) | ≥2 = 3 |
14-core TRUS SBx |
The magnetic field strength was 1, 1.5, and 3 T in one, 28, and 15 studies, respectively. Four studies used both 1.5 and 3 T MR systems. DWI and DCEI were used in 36 and 35 studies, respectively. Nineteen studies also added MRSI. An endorectal coil was used in 18 studies. The definition of positive mpMRI varied across studies. The PI-RADS v1 score was used in 12 studies, a five-level subjective (Likert) score was used in eight studies, and one study reported data based on the two scoring systems. In-house criteria were used in 13 studies for defining positive mpMRI, and five studies used a dichotomous definition. Nine studies did not report on the criteria for positive mpMRI. No study used the PI-RADS v2 score.
Regarding the reference standard, TRUS-guided biopsies were used in 39 studies, TTP biopsies in six studies, and mixed TRUS-guided and TTP biopsies in two studies. In one study, the biopsy approach was unclear. The number of cores per biopsy procedure was ≤16 in 30 studies, >16 in nine studies, and variable among patients in three studies. For six studies, the number of biopsy cores taken was unclear.
At patient level, the median biopsy positivity rate (ie, cancer prevalence) was 50.4% (IQR, 36.4–57.7%) for overall cancer and 32.9% (IQR, 28.1–37.2%) for csPCa ( Table 2 ). The median mpMRI NPV was 82.4% (IQR, 69.0–92.4%) for overall cancer and 88.1% (IQR, 85.7–92.3) for csPCa. NPV significantly decreased when cancer prevalence increased, both for overall cancer ( r = –0.64, p < 0.0001) and csPCa ( r = –0.75, p = 0.032; Fig. 3 ). In addition, NPV was highly dependent on the definition used for csPCa, with differences of up to 21% when several definitions were used in the same dataset [12 13 38 47 48] .
Study | Overall PCa prevalence (%) | Reporting level | Multiparametric MRI performance for PCa detection | Definition of csPCa | csPCa prevalence | Multiparametric MRI performance for csPCa detection | ||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
TN | FN | TP | FP | NPV | PPV | TN | FN | TP | FP | NPV | PPV | |||||
Hauth (2015) [25] | 45.7 | Patient | 6 | 1 | 42 | 45 | 85.7% | 48.3% | Low grade: GS ≤ 6 High grade: GS ≥ 7 |
NR | NR | NR | NR | NR | NR | NR |
Lesion | 59 | 13 | 55 | 73 | 81.9% | 43% | ||||||||||
Lamb (2015) [36] | 65.9 | Patient | 23 | 22 | 92 | 36 | 51.1% | 71.9% | GS ≥ 7 | 50.9% | 31 | 14 | 71 | 57 | 68.9% | 55.5% |
Brock (2015) [15] | 42.3 | Patient | 17 | 7 | 56 | 88 | 70.8% | SBx: 38.8% TBx: 22.2% Duo: 44.4% |
Epstein: GS > 6 and/or max CCL ≥50% | 24.4% | SBx: 21 | SBx: 3 | SBx: 38 TBx: 27 duo: 47 |
SBx: 106 TBx: 117 duo: 97 |
87.5% | SBx: 26.4% TBx: 18.8% duo: 32.6% |
Grenabo Bergdahl (2016) [22] | 33.7 | Patient | 36 | 7 | 19 | 21 | 83.7% | 47.5% | Clinically insignificant PCa: T1c, PSAd < 0.15, GS < 7, ≤2 positive cores, and unilateral cancer | NR | NR | NR | NR | NR | NR | NR |
Wang (2015) [58] | 58 | Patient | 165 | 8 | 332 | 81 | 95.4% | 80.4% | NR | NR | NR | NR | NR | NR | NR | NR |
Pepe (2015) [41] | 37 | Patient | 23 | 8 | 29 | 40 | 74.2% | 42% | GS ≥ 7 or GS 6 with CCL ≥ 50% | NR | NR | NR | NR | NR | 100% | 55.8% |
Panebianco (2015) [39] | 74.7 | Patient | Group A (satBx): 104 | Group A (satBx): 43 | Group A: 186 | Group A: 22 | Group A (satBx): 70.7% | Group A: 89.4% | NR | 60% | Group A: 147 | Group A: 0 | Group A: 183 | Group A: 25 | Group A: 100% | Group A: 88% |
Group B (TRUSGB NR TRUS G satBx): 93 | Group B (TRUSGB NR TRUS G satBx): 37 | Group B: 417 before and 425 after satBx | Group B: 23/440 and 15/440 after satBx. | Group B (TRUSGB–TRUS G satBx): 71.5% | Group B: 94.8% before and 96.6% after satBx | 71.9% | Group B: 130 | Group B: 0 | Group B: 410 |
Group B: 30 | Group B: 100% | Group B: 93.2% | ||||
Radtke (2015) [46] | 51 | Patient | ≥2/5: 80 ≥3: 103 ≥4: 138 = 5: 142 |
≥2/5: 18 ≥3/5: 38 ≥4/5: 78 = 5/5: 126 |
≥2/5: 132 ≥3/5: 112 ≥4/5: 72 = 5/5: 24 |
≥2/5: 64 ≥3/5: 41 ≥4/5: 6 = 5/5: 2 |
≥2/5: 81.6% ≥ 3/5: 73.1% ≥ 4/5: 63.9% = 5/5: 53% |
≥2/5: 67.4% ≥ 3/5: 73.2% ≥ 4/5: 92.3% = 5/5: 92.3% |
GS ≥ 7 | 29.3% | ≥2/5: 91 ≥3/5: 124 ≥4/5: 183 = 5/5: 203 |
≥2/5: 7 ≥3/5: 17 ≥4/5: 33 = 5/5: 65 |
≥2/5: 79 ≥3/5: 69 ≥4/5: 53 = 5/5: 21 |
≥2/5: 117 ≥3/5: 84 ≥4/5: 25 = 5/5: 5 |
≥2/5: 92.2% ≥3/5: 87.9% ≥4/5: 84.7% = 5/5: 75.8% |
≥2/5: 40.3% ≥3/5: 45.1% ≥4/5: 68% = 5/5: 80.7% |
Itatani (2014) [27] | 13 | Patient | 168 | 25 | NR | NR | 87% | NR | (1) PSAd ≥ 0.1 or GP 4/5 or ≥ 3/6 pos cores; max CCL < 50% (2) PSAd ≥ 0.15 or GP 4/5 or max core length invasion < 3 mm (min 6 cores) |
NR | NR | NR | NR | NR | NR | NR |
Porpiglia (2014) [44] | 30.6 | Patient | 107 | 5 | 47 | 11 | 95.5% | 81% | NR | NR | NR | NR | NR | NR | NR | NR |
Thompson (2014) [56] | 61.3 | Patient | 35 | 16 | 76 | 23 | 68.6% | 76.7% | Moderate or high risk Moderate risk: GS 7 (GP4 >5%) and <50% of positive cores or GS 6–7 (GP4 ≤ 5%) and either ≥30% of positive cores or max core length invasion ≥8 mm High risk: GS ≥ 7 (GP4 > 5%); ≥50% + cores or GS ≥ 8 |
34% | 49 | 2 | 49 | 50 | 96% | 49.5% |
Pokorny (2014) [43] | 63.7 | Patient | ≥3/5: 56 ≥4/5: 74 |
≥3/5: 25 ≥4/5: 40 |
≥3/5: 101 ≥4/5: 86 |
≥3/5: 41 ≥4/5: 23 |
≥3/5: 69.1% ≥4/5: 64.9% |
≥3/5: 71.1% ≥4/5: 78.9% |
NR | NR | NR | NR | NR | NR | NR | NR |
Petrillo (2014) [42] | 18.4 | Patient | 56 | 4 | 21 | 55 | 93% | 28% | NR | NR | NR | NR | NR | NR | NR | NR |
Javali (2014) [29] | 16.4 | Patient | 49 | 1 | 22 | 68 | 98% | 24.4% | NR | NR | NR | NR | NR | NR | NR | NR |
Abd-Alazeez (2014) [13] | 54.7 | Lobe | ≥3/5: 33 | ≥3/5: 14 | ≥3/5: 127 | ≥3/5: 84 | ≥3/5: 70% | ≥3/5: 60% | Def 1: GS ≥ 4 + 3 and/or max CCL ≥ 6 mm Def 2: GS ≥ 3 + 4 and/or max CCL ≥ 4 mm Def 3: GS ≥ 4 + 3 Def 4: GS ≥ 3 + 4 Def 5: max CCL ≥ 6 mm Def 6: max CCL ≥ 4 mm |
Def 1: NR Def 2: 44.2% Def 3: 23.2% Def 4: 36% Def 5: 32.9% Def 6: 39.5% |
Def 1: 46 Def 2: 42 Def 3: 47 Def 4: 43 Def 5: 46 Def 6: 43 |
Def 1: 1 Def 2: 5 Def 3: 0 Def 4: 4 Def 5: 1 Def 6: 4 |
Def 1: 45 Def 2: 72 Def 3: 13 Def 4: 50 Def 5: 39 Def 6: 59 |
Def 1: 166 Def2: 139 Def 3: 198 Def 4: 161 Def 5: 172 Def 6: 152 |
Def 1: 98 Def 2: 89 Def 3: 100 Def 4: 92 Def 5: 98 Def 6: 91 |
Def 1: 21 Def 2: 34 Deg 3: 6 Def 4: 24 Def 5: 19 Def 6: 28 |
≥4/5: 87 | ≥3/5: 62 | ≥3/5: 79 | ≥3/5: 30 | ≥3/5: 58% | ≥3/5: 73% | Def 1: 140 Def 2: 124 Def 3: 148 Def 4: 133 Def 5: 141 Def 6: 131 |
Def 1: 9 Def 2: 25 Def 3: 1 Def 4: 16 Def 5: 8 Def 6: 18 |
Def 1: 37 Def 2: 52 Def 3: 12 Def 4: 38 Def 5: 32 Def 6: 45 |
Def 1: 72 Def 2: 57 Def 3: 97 Def 4: 71 Def 5: 77 Def 6: 64 |
Def 1: 94 Def 2: 83 Def 3: 99 Def 4: 89 Def 5: 95 Def 6: 88 |
Def 1: 34 Def 2: 48 Def 3: 11 Def 4: 35 Def 5: 30 Def 6: 42 |
|||||
Abd-Alazeez (2014) [12] | 47.2 | Lobe | ≥3/5: 26 | ≥3/5: 13 | ≥3/5: 38 | ≥3/5: 31 | ≥3/5: 66% | ≥3/5: 55% | Def 1: GS ≥ 4 + 3 and/or max CCL ≥ 6 mm Def 2: GS ≥ 3 + 4 and/or max CCL ≥ 4 mm Def 3: GS ≥ 4 + 3 Def 4: GS ≥ 3 + 4 Def 5: max CCL ≥ 6 mm Def 6: max CCL ≥ 4 mm |
Def 1: 18.5% Def 2: 31.5% Def 3: 4.6% Def 4: 21.3% Def 5: 16.7% Def 6: 25% |
Def 1: 37 Def 2: 31 Def 3: 39 Def 4: 36 Def 5: 37 Def 6: 32 |
Def 1: 2 Def 2: 8 Def 3: 0 Def 4: 3 Def 5: 2 Def 6: 7 |
Def 1: 18 Def 2: 26 Def 3: 5 Def 4: 20 Def 5: 16 Def 6: 20 |
Def 1: 51 Def 2: 43 Def 3: 64 Def 4: 49 Def 5: 53 Def 6: 49 |
Def 1: 95 Def 2: 79 Def 3: 100 Def 4: 92 Def 5: 95 Def 6: 82 |
Def 1: 26 Def 2: 38 Def 3: 7 Def 4: 29 Def 5: 23 Def 6: 29 |
≥4/5: 49 | ≥4/5: 25 | ≥4/5: 26 | ≥4/5: 8 | ≥4/5: 66% | ≥4/5: 76% | Def 1: 70 Def 2: 63 Def 3: 73 Def 4: 68 Def 5: 70 Def 6: 64 |
Def 1: 4 Def 2: 11 Def 3: 1 Def 4: 6 Def 5: 4 Def 6: 10 |
Def 1: 16 Def 2: 23 Def 3: 4 Def 4: 17 Def 5: 14 Def 6: 17 |
Def 1: 18; Def 2: 11 Def 3: 30 Def 4: 17 Def 5: 20 Def 6: 17 |
Def 1: 94 Def 2: 85 Def 3: 99 Def 4: 92 Def 5: 94 Def 6: 86 |
Def 1: 47 Def 2: 67 Def 3: 12 Def 4: 50 Def 5: 41 Def 6: 49 |
|||||
Matsuoka (2014) [37] | 64.8 | Lobe | 46 | 49 | 149 | 26 | 48.4% | 85.1% | NR | NR | NR | NR | NR | NR | NR | NR |
Junker (2013) [30] | 53.4 | Patient | ≥10/15: 21 ≥11/15: 28 |
≥10/15: 4 ≥11/15: 12 |
≥10/15: 35 ≥11/15: 27 |
≥10/15: 13 ≥11/15: 6 |
≥10/15: 84% ≥11/15: 70% |
≥10/15: 72.9% ≥11/15: 81.8% |
GS ≥ 4 + 3 | 13.7% | ≥13: 54 | ≥13: 2 | ≥13: 8 | ≥13: 9 | ≥13: 96.4% | ≥13: 47% |
Busetto (2013) [16] | 41.7 | Patient | 59 | 7 | 61 | 36 | 89% | 63% | NR | NR | NR | NR | NR | NR | NR | NR |
Rais-Bahrami (2013) [47] | 54.2 | Patient | ≥2/4 : 80 | ≥2/4: 275 | ≥2/4: 187 | ≥2/4: 275 | ≥2/4: 66% | ≥2/4: 59% | GS ≥ 7: GS ≥ 8 |
31.7% | NR | NR | NR | NR | GS ≥ 7: 91% GS ≥ 8: 91% |
GS ≥ 7: 38% GS ≥ 8: 18% |
≥3/4: 251 | ≥3/4: 76 | ≥3/4: 16 | ≥3/4: 76 | ≥3/4: 51% | ≥3/4: 82% | NR | NR | NR | NR | GS ≥ 7: 75% GS ≥ 8: 91% |
GS ≥ 7: 67% GS ≥ 8: 41% |
|||||
Kuru (2013) [34] | 57.6 | Patient | 80 | 14 | 67 | 186 | 85.1% | 73.5% | NR | NR | NR | NR | NR | NR | NR | NR |
Ferda (2013) [20] | 51.2 | Patient | 52 | 2 | 82 | 28 | 96.3% | 74.5% | NR | NR | NR | NR | NR | NR | NR | NR |
Ganie (2013) [21] | 74.7 | Patient | 13 | 3 | 62 | 9 | 59.1% | 95.4% | NR | NR | NR | NR | NR | NR | NR | NR |
Vinet (2013) [57] | 49.3 | Patient | ≥3/5: 11 | ≥3/5: 6 | ≥3/5: 28 | ≥3/5: 24 | ≥3/5: 64.7% | ≥3/5: 53.8% | NR | NR | NR | NR | NR | NR | NR | NR |
≥4/5: 22 | ≥4/5: 11 | ≥4/5: 23 | ≥4/5: 13 | ≥4/5: 66.7% | ≥4/5: 63.8% | NR | NR | NR | NR | NR | NR | NR | NR | |||
Numao (2013) [38] | 45 | Patient | 137 | 57 | 101 | 56 | 70.6% | 64.3% | Def 1: GS ≥4 + 3 and/or ≥20% positive cores and/or max CCL ≥5 mm Def 2: GS ≥ 3 + 4 and/or ≥20% + cores and/or max CCL ≥5 mm Def 3: GS ≥ 3 + 4 and/or ≥20% + cores |
Def 1: 33.3% Def 2:37.8% Def 3: 35.8% |
Def 1: 74 Def 2: 65 Def 3: 69 |
Def 1: 83 Def 2: 92 Def 3: 88 |
Def 1: 160 Def 2: 153 Def 3: 156 |
Def 1: 34 Def 2: 41 Def 3: 38 |
Def 1: 82.4% Def 2: 78.8% Def 3: 80.4% |
Def 1: 58.8% Def 2: 58.5% Def 3: 56% |
Belas (2012) [14] | 53.5 | Patient | 22 | 12 | 23 | 13 | 64.7% | 63.8% | NR | NR | NR | NR | NR | NR | NR | NR |
Ibrahiem (2012) [26] | 73.9 | Patient | 14 | 11 | 57 | 10 | 56% | 85.1% | NR | NR | NR | NR | NR | NR | NR | NR |
Sciarra (2012) [51] | 34.5 | Patient | 41 | 4 | 25 | 14 | 91.1% | 64.1% | NR | NR | NR | NR | NR | NR | NR | NR |
Portalez (2012) [45] | 48.1 | Lesion | Likert: 357 | Likert: 50 | Likert: 81 | Likert: 50 | Likert: 95% | Likert: 38% | Max CCL >3 mm and/or GG 4/5 | NR | NR | NR | NR | NR | NR | NR |
PI-RADS: 404 | PI-RADS: 47 | PI-RADS: 34 | PI-RADS: 47 | PI-RADS: 95% | PI-RADS: 58% | |||||||||||
Watanabe (2012) [59] | 48.1 | Patient | 485 | 73 | 624 | 266 | 86.9% | 70.1% | NR | NR | NR | NR | NR | NR | NR | NR |
Tamada (2011) [54] | 70 | Patient | 12 | 6 | 29 | 3 | 67% | 91% | NR | NR | NR | NR | NR | NR | NR | NR |
Region | 277 | 48 | 55 | 20 | 85% | 73% | ||||||||||
Choi (2011) [18] | 70.6 | Patient | 9 | 5 | 31 | 6 | 64.2% | 75.7% | NR | NR | NR | NR | NR | NR | NR | NR |
Iwazawa (2011) [28] | 40.5 | Region | 887 | 86 | 232 | 219 | 91.1% | 51.4% | NR | NR | NR | NR | NR | NR | NR | NR |
Rouse (2011) [48] | 33.7 | Sextant | 145 | 11 | 74 | 22 | 92.9% | 77.1% | GS ≥ 7: Def 1: ≥3 mm Def 2: ≥5 mm |
Def 1: 26.6% Def 2: 26.2% |
Def 1: 153 Def 2: 153 |
Def 1: 3 Def 2: 3 |
Def 1: 64 Def 1: 63 |
Def 1: 32 Def 2: 33 |
Def 1: 98.1% Def 2: 98.1% |
Def 1: 68.1% Def 2: 67% |
59.6 | Patient | 24 | 14 | 54 | 22 | 63.2% | 71.1% | Def 1: 41.2% Def 2: 36.8% |
Def 1: 30 Def 2: 31 |
Def 1: 4 Def 2: 3 |
Def 1: 43 Def 2: 39 |
Def 1: 4 Def 2: 3 |
Def 1: 88.2% Def 2: 91.2% |
Def 1: 53.8% Def 2: 48.8% |
||
Haffner (2011) [23] | 54.4 | Patient | 154 | 50 | 240 | 111 | 75.4% | 68.3% | NR | NR | NR | NR | NR | NR | NR | NR |
Panebianco (2010) [40] | 42.7 | Patient | NR | NR | NR | NR | 95.1% | 88.2% | NR | NR | NR | NR | NR | NR | NR | NR |
Roy (2010) [49] | 55.9 | Patient | NR | NR | NR | NR | 71% | 75% | NR | NR | NR | NR | NR | NR | NR | NR |
Testa (2010) [55] | 40.7 | Patient | NR | NR | NR | NR | 79.3% | 64% | NR | NR | NR | NR | NR | NR | NR | NR |
Sciarra (2010) [52] | 50 | Patient | 61 | 4 | 66 | 9 | 93.8% | 88% | NR | NR | NR | NR | NR | NR | NR | NR |
Kitajima (2010) [31] | 56.6 | Patient | 311 | 19 | 80 | 14 | 92.2% | 85.1% | NR | NR | NR | NR | NR | NR | NR | NR |
Labanaris (2010) [35] | 73.9 | Patient | 17 | 73 | 96 | 74 | 81.11% | 56.47% | NR | NR | NR | NR | NR | NR | NR | NR |
Kumar (2009) [32] | 21.7 | Patient | 39 | 3 | 10 | 8 | 92.8% | 55% | NR | NR | NR | NR | NR | NR | NR | NR |
Schmuecking (2009) [50] | NR | Lobe | NR | NR | NR | NR | 96% | 61% | NR | NR | NR | NR | NR | NR | NR | NR |
Cheikh (2009) [17] | 24.7 | Patient | 36 | 12 | 11 | 34 | 80% | 22.9% | NR | NR | NR | NR | NR | NR | NR | NR |
Cirillo (2008) [19] | 31.5 | Patient | 19 | 0 | 17 | 18 | 100% | 48.6% | NR | NR | NR | NR | NR | NR | NR | NR |
Kumar (2007) [33] | 13.3 | Patient | 39 | 0 | 11 | 33 | 100% | 25% | NR | NR | NR | NR | NR | NR | NR | NR |
Squillaci (2005) [53] | 50.8 | Patient | 29% | 8% | 25% | 3% | 89% | 80% | NR | NR | NR | NR | NR | NR | NR | NR |
Hara (2005) [24] | 41.5 | Patient | ≥2/3: 40 = 3/3: 47 |
≥2/3: 4 = 3/3: 8 |
≥2/3 30 = 3/3: 26 |
≥2/3: 8 = 3/3: 1 |
≥2/3: 90% = 3/3: 85% |
≥2/3: 78.9% = 3/3: 96.3% |
NR | NR | NR | NR | NR | NR | NR | NR |
Cancer prevalence tended to be higher and mpMRI NPV lower in the biopsy-naïve group as compared with the repeat biopsy group, in men with positive DRE as compared with men with negative DRE and when an endorectal coil was not used ( Table 3 ). There were no clear differences in the prevalence and NPV of the other analysed subgroups (TRUS-guided vs TTP biopsy, biopsy procedures with ≤16 cores vs >16 cores; Table 3 ). However, comparisons must be interpreted with care, due to the small number of studies in some subgroups. In patients with a PSA level of ≤10 ng/ml, the median NPV for overall PCa was 86.3% (IQR, 73.3–93.6%) for a median cancer prevalence of 35.4% (IQR, 27.6–42.5%).
Nb of studies | Median PCa prevalence | Median mpMRI NPV | Nb of studies | Median csPCa prevalence | Median mpMRI NPV | |
---|---|---|---|---|---|---|
Biopsy-naïve patients | 8 | 51.4% (45.5–56.7) | 69.9% (64.2–78) | 1 | 35.8% (NA) | 80.4% (NA) |
Repeat biopsy | 14 | 42% (35.1–52.6) | 82.6% (75.5–93.1) | 3 | 24.4% (19.1–32.8) | 88.2% (87.9–92.3) |
TRUS-guided biopsy | 36 | 49.7% (34.3–57.7) | 84.6% (68.6–92.8) | 4 | 28.1% (21.7–36.5) | 89.3% (82.9–92.4) |
TTP biopsy | 4 | 53.8% (47.5–57.8) | 73.6% (72–78.7) | 2 | 31.6% (30.5–32.8) | 92% (89.9–94) |
Biopsy with ≤16 cores | 28 | 48.7% (39.2–54.8) | 81.9% (66.8–89.3) | 5 | 28.1% (21.8–36.5) | 89.3% (82.9–92.4) |
Biopsy with >16 cores | 5 | 56.6% (51–61.3) | 81.1% (73.1–92.2) | 2 | 31.7% (30.5–32.8) | 92% (89.9–93.9) |
Positive DRE | 1 | 73.9% (NA) | 56% (NA) | 0 | – | – |
Negative DRE | 6 | 36% (34.6–46.8) | 82.7% (74.2–93.1) | 0 | – | – |
Endorectal coil | 17 | 41.7% (30.6–55.9) | 92.8% (79.3–95.4) | 1 | 31.7% (NA) | 91% (NA) |
No endorectal coil | 22 | 50.9% (41.7–56.1) | 77.7% (69.5–86.6) | 7 | 34% (26.9–46.1%) | 87.9% (78.2–92.1) |
Eight studies reported NPV at patient level for overall PCa and fulfilled the inclusion criteria for meta-analysis ( Table 4 ) [22 25 38 41 43 46 56 57] .
Study | Prevalence a (%) | Neg MRI (%) | NPV (%) | PPV (%) | Spe (%) | Se (%) | ||
---|---|---|---|---|---|---|---|---|
All PCa | Score ≥ 3/5 | Grenabo Bergdahl (2016) [22] | 31.3 | 66.9 | 83.7 | 47.5 | 63.2 | 73.1 |
Numao (2013) [38] | 45 | 29.4 | 70.6 | 64.3 | 71.0 | 63.9 | ||
Hauth (2015) [25] | 45.7 | 14.3 | 85.7 | 48.3 | 11.8 | 97.7 | ||
Vinet (2013) [57] | 49.3 | 24.6 | 64.7 | 53.8 | 31.4 | 82.4 | ||
Radtke (2015) [46] | 51 | 27 | 73 | 73.2 | 71.5 | 74.7 | ||
Thompson (2014) [56] | 61.3 | 31.4 | 68.6 | 76.8 | 60.3 | 82.6 | ||
Pokorny (2014) [43] | 63.7 | 30.9 | 69.1 | 82.4 | 69.1 | 82.4 | ||
Score ≥ 4/5 | Pepe (2015) [41] | 37 | 31 | 74.2 | 42 | 36.5 | 78.4% | |
Vinet (2013) [57] | 49.3 | 47.8 | 66.7 | 63.9 | 62.9 | 67.6% | ||
Radtke (2015) [46] | 51 | 73.5 | 63.9 | 92.3 | 95.8 | 48% | ||
Gleason ≥7 PCa | Score ≥ 3/5 | Radtke (2015) [46] | 29.3 | 27 | 87.9 | 45.1 | 59.6 | 80.2% |
a Prevalence of overall prostate cancers (10 first lines) or Gleason ≥7 cancers (last line).
PCa = prostate cancer; MRI = magnetic resonance imaging; Neg MRI = proportion of negative magnetic resonance imaging; NPV = negative predictive value; PPV = positive predictive value; Se = sensitivity; Spe = specificity.
Seven studies used a score of ≥3/5 for defining positive mpMRI ( Fig. 4 A and B) [22 25 38 43 46 56 57] . Fig. 4 C shows the conditional probability plot of 1 – NPV and PPV as a function of overall PCa prevalence. Table 5 shows NPV and PPV estimates for the given values of PCa prevalence.
PCaPrev | PPV | NPV |
---|---|---|
0.30 | 0.43 (0.34–0.53) | 0.88 (0.77–0.99) |
0.40 | 0.54 (0.45–0.64) | 0.82 (0.70–0.94) |
0.50 | 0.64 (0.55–0.73) | 0.76 (0.64–0.88) |
0.60 | 0.73 (0.65–0.80) | 0.67 (0.56–0.79) |
0.70 | 0.81 (0.75–0.87) | 0.57 (0.47–0.67) |
0.75 | 0.84 (0.79–0.89) | 0.51 (0.42–0.59) |
Only three studies used a score of ≥4/5 for defining positive mpMRI ( Table 4 ) [41 46 57] , and a formal meta-analysis could not be performed.
Only one study reporting NPV at patient level for Gleason ≥7 cancers met the selection criteria for inclusion in the meta-analysis. It reported NPV and PPV of 87.9% and 45.1%, respectively, for a prevalence of 29.3% ( Table 4 ) [46] .
We observed a large variability in reported NPV. Many factors, such as differences in mpMRI protocols, definition of negative mpMRI, or biopsy protocols, can explain this variability. However, two major causes of variability must be pointed out. First, the cancer prevalence was highly variable, ranging at patient level from 13% to 74.7% for overall PCa, and from 13.7% to 50.9% for csPCa. This variability was observed in both the biopsy-naïve and the repeat biopsy setting. As NPV depends on prevalence, this had a major impact on reported NPV ( Fig. 3 ). Second, the definition of csPCa was highly variable from one series to another, and differences of up to 21% could be observed in NPV when different definitions of csPCa were used in the same dataset [12 13 38 47 48] .
To account for clinical heterogeneity and to further explore the clinical relevance of the results, we carefully selected studies for inclusion in the meta-analysis based on stringent criteria. Particularly, we included only studies that: (1) had biopsy protocols with at least 10 cores, since it is no longer recommended to obtain less than 10 cores per biopsy; (2) used DWI, which is the most informative technique, at least for cancers in the peripheral zone [60] ; and (3) reported mpMRI findings using a five-level score, so that negative findings could be better defined. We accepted studies using a subjective (Likert) scale because experienced readers obtained equivalent [45 61 62] or better [63] results with the Likert score than with the PI-RADS v1 score. Owing to the large variations of NPV induced by differences in definitions of csPCa, we did not include different definitions in the meta-analysis since this would have introduced unacceptable clinical heterogeneity in the results, possibly resulting in erroneous and biased estimates. We, therefore, a priori restricted the definition of csPCa to cancers with a Gleason score of ≥7, given the low lethal potential of Gleason 6 cancers [64] and the lack of consensus among pathologists on the best method to measure biopsy core invasion length [65 66] .
In this more homogeneous group of studies, the prevalence range was still large (31.3–63.7%). As a result, we modelled the evolution of NPV (and PPV) as a function of overall PCa prevalence. Unfortunately, we could not duplicate this for csPCa since only one study reporting NPV for Gleason ≥7 cancers met the inclusion criteria for meta-analysis.
We included only studies that reported the results of systematic/standard biopsy in patients with negative mpMRI and used the systematic/standard biopsy as a reference standard. It is well known that TRUS-guided biopsy harbours both random and systematic errors, as evidenced by the high rates of positivity of immediate repeat biopsy after a first series of negative biopsies [67 68] , and as confirmed recently by the PROMIS trial [69] . Therefore, using TRUS-guided biopsy as a reference standard may have overestimated the NPV of mpMRI. However, studies using radical prostatectomy specimens as a reference standard have already reported mpMRI detection rates in relation to PCa Gleason score and volume [1] . In this review, we intended to address the more pragmatic question as to whether a negative mpMRI could predict a negative subsequent biopsy. This is an important question because if the NPV of mpMRI was sufficiently high in comparison with the reference standard of systematic/standard biopsies, then in practice a negative mpMRI result could indeed avoid the need for prostate biopsy. Therefore, studies reporting only biopsy results when the mpMRI was positive (eg, obtained through MRI-targeted, guided, or fusion biopsies with added systematic biopsies) were not included in this review.
It is now well established that mpMRI is a sensitive tool for detecting aggressive PCa 1 2 3 69] . However several reasons preclude its broad use as a triage test before biopsy.
Firstly, the population referred to prostate biopsy is not standardised. The large range of reported prevalence for overall PCa and csPCa suggests substantial heterogeneity in the way patients are selected for biopsy. Owing to this heterogeneity, we did not provide a pooled estimate for mpMRI NPV. The role of mpMRI as a triage test before prostate biopsy should be evaluated in the broader context of the selection of patients with a suspicion of (aggressive) PCa. In a recent retrospective study of 514 patients, mpMRI NPV for Gleason ≥7 cancers was 91% when the PSA density was ≤0.2 ng/ml/ml, and only 71% when the PSA density was >0.2 ng/ml/ml ( p = 0.003) [70] . In another series of 288 biopsy-naïve patients, no csPCa (Gleason score ≥7 or maximum cancer core length ≥4 mm) was found in 44 patients with a PSA density of <0.15 ng/ml/ml and a PI-RADS v2 score of <3/5 [71] . We believe that such prestratification of the risk of csPCa is an interesting way for rationalising the use of mpMRI before biopsy. Patients found at very low risk would be spared both mpMRI and biopsy. Patients at a low risk—for whom mpMRI would have an NPV high enough to be used as a triage test—could avoid biopsy in case of negative mpMRI. Patients at a higher risk would need biopsy even in case of negative mpMRI. Many tools can be used to risk stratify the population of patients referred to biopsy, ranging from simple parameters such as PSA density to more complicated risk calculators [72 73] . The impact of these tools on the NPV of prebiopsy mpMRI needs to be carefully evaluated, both in the biopsy-naïve and in the repeat biopsy setting. For the moment, it is impossible to make any recommendations on the best way to risk stratify patients before referring them for mpMRI.
Secondly, the large variability in the definition of csPCa precludes any definitive conclusion on the ability of mpMRI to rule out aggressive cancer. The issue of the most appropriate definition of csPCa on biopsy is complex, since biopsy results may accurately reflect neither tumour burden nor aggressiveness. Nonetheless, there is an urgent need to standardise the histological definition(s) of csPCa, to allow meaningful comparisons between studies.
Thirdly, the specificity of mpMRI remains moderate, and there is a substantial proportion of false positives in the lesions scored 3/5 or 4/5 [1 74 75] , even with the new PI-RADS v2 score [76] . In a series of 62 patients with 116 lesions biopsied under magnetic resonance/ultrasound fusion, the overall cancer detection rates for PI-RADS v2 scores of 3/5 and 4/5 were only 15.8% and 29.8%, respectively [77] . In theory, a triage test used to rule out a disease needs to be highly sensitive for this disease. However, if its specificity is too low, it will be clinically useless since most patients will be positive, whether they have the disease or not. Therefore, if mpMRI is to be used as a triage test in the future, there is a need to improve its specificity. This could be achieved by a continuous refinement of scores [78] . Promising results in characterising csPCa have also been reported with a quantitative analysis [79] .
Finally, all published studies were conducted in specialised centres. The broad use of mpMRI as a triage test assumes good interobserver reproducibility. Unfortunately, interobserver reproducibility of existing scoring systems remains moderate [62 63 80] even with the use of the PI-RADS v2 score [80 81] . Studies evaluating on a large scale the reproducibility of mpMRI findings between expert and nonexpert centres are currently lacking.
Three systematic reviews (including two meta-analyses) regarding the role of mpMRI in localised PCa have been published recently 4 5 6 . Crucially, all three reviews focused exclusively on the sensitivity of mpMRI-targeted, guided, or fusion biopsies in diagnosing overall PCa and csPCa, using TRUS-guided prostate biopsies as reference standards. The impact of systematic biopsies on the outcome was not addressed in any of the reviews, within either the index test or the reference standard. Our review had a totally different research question and objective, focusing on NPV of mpMRI to see if a negative mpMRI can avoid the need for a prostate biopsy. As MRI-targeted/guided/fusion biopsies are not relevant if the mpMRI was negative for cancer, it can be argued that the three reviews assessed a different index test altogether. As such, we believe that the findings of this review are novel and unique, and pave the way for further focused clinical studies.
The current study represents the first systematic review addressing the role of mpMRI as a triage test before biopsy. The review elements were developed in conjunction with a multidisciplinary panel of experts (EAU Prostate Cancer Guidelines Panel), which included a patient representative, and the review was performed robustly in accordance with recognised standards. However, it is limited by the major heterogeneity of the existing literature in patient population, study design, and definitions of positive mpMRI and csPCa. It highlighted further areas of research that could help in defining the best use of mpMRI in the early detection of aggressive PCa in the future.
Although mpMRI can detect aggressive PCa with excellent sensitivity, a definitive conclusion on its role as a triage test before prostate biopsy will be possible only when three main issues are addressed. Firstly, because NPV depends on prevalence, and because overall PCa and csPCa prevalence was highly variable in the published series, it becomes mandatory to define the optimal way to pre-evaluate the risk of csPCa in patients with a suspicion of PCa. Depending on the risk category, mpMRI could then be used to obviate biopsies or not. Secondly, there is a need for consensus definitions of csPCa on biopsy findings to allow interstudy comparisons. Thirdly, although efforts have been made to standardise mpMRI technical protocols and interpretation in the past few years [11 60 76] , there is still a crucial need to improve mpMRI specificity and inter-reader reproducibility.
This systematic review was performed under the auspices of:
The European Association of Urology Guidelines Office Board
The European Association of Urology Prostate Cancer Guideline Panel
Author contributions: Olivier Rouvière had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.
Study concept and design: Rouvière, Mottet, Cornford.
Acquisition of data: Rouvière, Moldovan, Van den Broeck, Yuan.
Analysis and interpretation of data: Rouvière, Moldovan, Van den Broeck, Lam.
Drafting of the manuscript: Rouvière, Moldovan, Van den Broeck, Lam.
Critical revision of the manuscript for important intellectual content: Bellmunt, van den Bergh, Bolla, Briers, Van den Broeck, Cornford, Cumberbatch, De Santis, Fossati, Gross, Henry, Joniau, Lam, Matveev, Moldovan, van der Poel, van der Kwast, Rouvière, Schoots, Wiegel, Mottet.
Statistical analysis: None.
Obtaining funding: None.
Administrative, technical, or material support: Yuan, Sylvester, Marconi.
Supervision: None.
Other: None.
Financial disclosures: Olivier Rouvière certifies that all conflicts of interest, including specific financial interests and relationships and affiliations relevant to the subject matter or materials discussed in the manuscript (eg, employment/affiliation, grants or funding, consultancies, honoraria, stock ownership or options, expert testimony, royalties, or patents filed, received, or pending), are the following: Bellmunt is a company consultant for Janssen, Astellas, Pierre Fabre, Genentech, Merck, Ipsen, Pfizer, Novartis, and Sanofi Aventis. He has received research support from Takeda, Novartis, and Sanofi, and received travel grants from Pfizer and Pierre Fabre. Bolla has received company speaker honoraria from Ipsen and Astellas, honoraria or consultation fees from Janssen, and fellowship and travel grants from Janssen, AstraZeneca, and Astellas. Briers has received grant and research support from Ipsen, European Association of Urology, and Bayer; is an ex officio board member for Europa UOMO; is an ethics committee and advisory group member for REQUITE; is a member patient advisory board member for PAGMI; and is a member of SCA and EMA PCWP. Cornford is a company consultant for Astellas, Ipsen, and Ferring. He receives company speaker honoraria from Astellas, Janssen, Ipsen, and Pfizer; participates in trials from Ferring; and receives fellowships and travel grants from Astellas and Janssen. De Santis is a company consultant for GlaxoSmithKline, Janssen, Bayer, Novartis, Pierre Fabre, Astellas, Amgen, Eisai Inc., ESSA, Merck, and Synthon; has received company speaker honoraria from Pfizer, Takeda, Sanofi Aventis, Shionogi, Celgene, and Teva OncoGenex; has participated in trials for Pierre Fabre, Astellas, Exelixis, Bayer, and Roche; has received fellowship and travel grants from Bayer, Novartis, Ferring, Astellas, Sanofi Aventis, and Janssen; has received grant and research support from Pierre Fabre; has received honoraria from AstraZeneca; and is associated with Amgen. Joniau is a company consultant for Astellas, Ipsen, Bayer, Sanofi, and Janssen; has received company speaker honoraria from Astellas, Amgen, Bayer, Sanofi, Janssen, and Ipsen; has participated in trials for Astellas, Janssen, and Bayer; has received fellowship and travel grants from Astellas, Amgen, Bayer, Sanofi, Janssen, Ipsen, and Pfizer; and has received grant and research support from Astellas, Bayer, and Janssen. Matveev has received company speaker honoraria from Sanofi and Astellas, has participated in trials for Astellas, Pfizer and Novartis. Lam is a company consultant for and has received company speaker honoraria from Pfizer, GSK, Astellas, and Ipsen. van der Poel is a company consultant for Intuitive Surgical, has participated in trials for Astellas and Steba Biotech, and has received grant and research support from Astellas. Rouvière is a company consultant for EDAP-TMS, Bracco, and Philips; has received company speaker honoraria from EDAP-TMS, Bracco, and Philips; and has participated in trials for EDAP-TMS and Bracco. Wiegel has received company speaker honoraria from Astellas, Takeda, Hexal, Ipsen, Janssen-Cilac, and Ferring. Mottet has received grant and research support from Takeda Pharmaceutical, Millenium, Astellas, Pierre Fabre, Sanofi, and Pasteur, and has received honoraria or consultation fees from Takeda Pharaceutical, Millenium, Jansen, Astellas, BMS, Bayer, Ipsen, Ferring, Novartis, Nuclétron, Pierre Fabre, Sanofi, and Zeneca. van den Bergh, Van den Broeck, Cumberbatch, Fossati, Gross, Henry, van der Kwast, Sylvester, Yuan, Schoots, Moldovan, and Marconi have nothing to disclose.
Funding/Support and role of the sponsor: None.
A correlation with radical prostatectomy specimens has demonstrated that multiparametric magnetic resonance imaging (mpMRI) has excellent sensitivity in detecting prostate cancer (PCa) with a Gleason score of ≥7 1 2 3 . As a result, prostate mpMRI is increasingly used in patients with a suspicion of PCa to localise abnormal areas before biopsy. A large body of literature has shown that targeted biopsies of suspicious lesions seen on mpMRI (TBx) improved the detection of clinically significant PCa (csPCa), at least in the repeat biopsy setting 4 5 6 . As a result, it is now recommended that an mpMRI is performed before repeat biopsy to allow TBx of suspicious lesions in addition to standard biopsies [7] .
Some authors have recently suggested that, besides improving csPCa detection, mpMRI could also be used as a triage test so that patients with negative mpMRI findings could obviate biopsy. Such a strategy remains highly controversial [8] and depends upon the negative predictive value (NPV) of mpMRI. Therefore, the European Association of Urology Prostate Cancer Guidelines Panel undertook this systematic review and meta-analysis to assess the NPV of mpMRI in patients with a suspicion of PCa and, thus, its potential role in eliminating unnecessary prostate biopsy.
Our primary aim was to systematically evaluate the performance of negative prebiopsy prostate mpMRI in predicting a negative biopsy result for overall PCa and csPCa in biopsy-naïve men and in men with previously negative biopsies. A further objective was to explore and define factors that may contribute to relevant thresholds in order to provide guidance for future studies.
The review was performed according to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) statement [9] . The review protocol was published in PROSPERO database ( http://www.crd.york.ac.uk/PROSPERO; registration number CRD42015021929). Databases searched included the Embase and OVID Medline databases, the Cochrane database of systematic reviews, and the Cochrane Central Register for Clinical Trials, covering from January 1, 2000 to February 13, 2016. Systematic or standard prostate biopsies were used as reference standards, with positive or negative cases of PCa being determined by histopathological examination. The detailed search strategy is presented in Supplement 1.
Included studies focused on men who were assessed for suspected PCa by mpMRI before undergoing prostate biopsy. Studies enrolling both biopsy-naïve men and men who had undergone previous negative biopsies were included. Prebiopsy prostate mpMRI was considered the index test and comprised T2-weighted imaging (T2WI) and at least one functional imaging technique (diffusion-weighted imaging [DWI], dynamic contrast-enhanced imaging [DCEI], or magnetic resonance spectroscopic imaging [MRSI]). For inclusion, studies had to report on false negatives and true negatives, in order to calculate NPV (ie, results of systematic/standard prostate biopsies when the mpMRI was negative). When available, false positive and true positive findings were also noted to calculate the positive predictive value (PPV) and the cancer prevalence. There was restriction neither on the biopsy technique (transrectal or transperineal) nor on the number of biopsy cores. Studies using radical prostatectomy specimens as reference standards were excluded, as were studies evaluating men with histologically proven PCa. Studies with less than 50 participants were excluded. No language restrictions were applied.
Two reviewers (P.C.M. and T.V.D.B.) independently screened all abstracts and full-text articles for eligibility. Disagreement was resolved by consensus or reference to an independent third party (L.M.). All screening was performed using a predefined eligibility form.
Using a data extraction form developed a priori, the same two reviewers independently extracted data concerning study methodology, patient characteristics, technical characteristics of the MR scanners, mpMRI protocol, mpMRI scoring system, definition of positive mpMRI, biopsy protocol, and definition of csPCa. Any discrepancies concerning data extraction were resolved by consensus or reference to an independent arbiter (O.R. or T.B.L.).
To assess the risk of bias (RoB), all included reports were reviewed using the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool for diagnostic accuracy studies [10] .
Outcome data regarding false negative and true negative values of mpMRI before prostate biopsy were recorded as reported by authors. When not available, data were indirectly derived from specificity, sensitivity, and prevalence values reported by authors using an online Bayesian statistics calculator ( http://www.medcalc.com/bayes.html ). Descriptive statistics were used to summarise baseline characteristics and outcomes, including median and interquartile range (IQR) for estimates of NPV across studies. A correlation between mpMRI NPV and a positive biopsy rate was established using the Pearson's correlation coefficient.
A meta-analysis was undertaken to calculate pooled NPV and PPV. To ensure appropriate clinical homogeneity of the studies included in the meta-analysis, we selected only the studies enrolling biopsy-naïve patients and/or patients with a history of negative biopsy, and fulfilling the following criteria that were defined a priori: (1) reference standard consisting of prostate biopsy with at least 10 samples on all patients; (2) mpMRI protocol comprising at least T2WI and DWI; (3) mpMRI results presented as a five-level score, using a subjective Likert scale or the Prostate Imaging Reporting Data System (PI-RADS) score [11] ; (4) definition of positive mpMRI as a score ≥3/5 or ≥4/5; and (5) results reported on a per patient basis. In addition, only studies defining csPCa as Gleason ≥7 cancers were selected for the meta-analysis assessing the mpMRI NPV for csPCa. A bivariate random-effects approach was employed using the Midas package in Stata 12 (StataCorp LP, College Station, TX, USA). Since the NPV decreases and the PPV increases as the prevalence increases, post-test probability estimates of NPV and PPV were reported for the given values of the prevalence based on Bayes’ theorem.
For other studies not included in the meta-analysis based on the criteria described above, a narrative synthesis of the data was performed. To explore and define clinical heterogeneity, subgroups were analysed at patient level based on the following variables: biopsy-naïve versus previous negative biopsy; patients with positive versus negative digital rectal examination (DRE); mpMRI performed with an endorectal versus without an endorectal coil; transrectal ultrasound (TRUS) versus template transperineal (TTP) biopsy approach; and ≤16 cores versus >16 cores as the reference standard. Studies reporting mpMRI NPV for patients with a prostate-specific antigen (PSA) level of ≤10 ng/ml were also reported separately.
The study selection process is depicted in the PRISMA flow diagram ( Fig. 1 ). A total of 2980 abstracts were retrieved. After abstract screening and removal of duplicates, 240 articles were eligible for full text screening, of which 48 studies were eligible for inclusion 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 .
Out of the 48 included studies, 42 were single-centre and six were multicentre studies. Thirty-four studies were prospective and six were retrospective, whilst the design of the rest was unclear. RoB assessment using QUADAS-2 was performed for each of the individual studies ( Fig. 2 A and B). Overall, the RoB was highly heterogeneous across studies for all criteria, except for the reference standard domain, in which RoB was low in most studies.
The 48 studies comprised a total of 9613 men who underwent prostate mpMRI followed by biopsy. The study and patient baseline characteristics are presented in Table 1 . The patient population consisted of biopsy-naive men in nine studies, men with at least one previous negative biopsy in 16 studies, and both biopsy-naïve men and men with a history of previous negative biopsy in nine studies. In 14 studies, the biopsy history of the patients was unclear.
Study | Study design | Period | Population | Pt Nb | Mean/median* age (yr) | Mean/median* PSA (ng/ml) | Mean/median* prostate volume (cm 3 ) | Magnetic field strength | MR pulse sequences | Endorectal coil | MR score | Definition of positive MRI | Reference standard |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Hauth (2015) [25] | Prospective | 2011–2013 | FB | 94 | 64 (43–83) | 9 (3–31) | 51 (17–140) | 1.5 T | T2WI/DWI/DCEI/MRSI | No | PI-RADS v1 | ≥3 | 11–13-core TRUS SBx + TBx |
Lamb (2015) [36] | Retrospective | 2013–2013 | FB & PNB | 173 | NR | NR | NR | 1.5 T | T2WI/DWI | NR | NR | NR | 12-core TRUS SBx |
Brock (2015) [15] | Prospective | 2013–2014 | PNB | 168 | 64* (IQR 59–70) | 9.2* (IQR 6.7–13.4) | 55.4* (IQR 42–80) | 3 T | T2WI/DWI/DCEI | No | PI-RADS v1 | NR | 12/24-core TRUS SBx + TBx |
Grenabo Bergdahl (2016) [22] | Prospective | 2013–2014 | FB & PNB | 83 | 69.3* (IQR 69–69.6) | 1.6* (IQR 0.9–2.7) | NR | 3 T | T2WI/DWI/DCEI/MRSI | No | PI-RADS v1 | ≥3 | 10-core TRUS SBx + TBx |
Wang (2015) [58] | Prospective | 2002–2009 | FB & PNB | 586 | 70 (26–91) | 11.11* (0.02–9794) | NR | 1.5 T | T2WI/DWI/DCEI/MRSI | Yes | PI-RADS v1 | ≥3 | TRUS SBx |
Pepe (2015) [41] | Prospective | 2011–2014 | PNB | 100 | 64* | 8.6* (4.2–10) | NR | 3 T | T2WI/DWI/DCEI/MRSI | No | PI-RADS v1 | ≥4 | TPBx + TBx |
Panebianco (2015) [39] | Prospective | 2011–2014 | FB (61.62%) & PNB (38.34%) | 925 (1140 total cohort) |
NR | NR | NR | 3 T | T2WI/DWI/DCEI | Yes | PI-RADS v1 | NR | 14-core TRUS SBx; 45-core sat TPBx + TBx |
Radtke (2015) [46] | Prospective | 2013–2013 | FB (63.3%) & PNB (36.7%) | 294 | 64* (60–71) | 7.3 (6.0) | 47 (37.5) | 3 T | T2WI/DWI/DCEI | No | PI-RADS v1 | PI-RADS ≥2; PI-RADS ≥3; PI-RADS ≥4; PI-RADS = 5; |
24-core TPBx + TBx |
Itatani (2014) [27] | Retrospective | 2004–2007 | NR | 193 | 68.9 (8.4); 70* (47–89) | 11.8 (15.9); 7.9* (1.22–159) | NR | 1.5 T | T2WI/DWI/DCEI | No | 1–5 scale (Likert) | ≥3 | 12–14-core TRUS SBx |
Porpiglia (2014) [44] | Prospective | 2011–2013 | PNB | 170 | 65* (60–70) | 6.9* (5.2–9.8) | 42* (36–48) | 1.5 T | T2WI/DWI/DCEI | Yes | Dichotomous | Positive: at least 2/3 MR seq. with suspicious findings | 18–24-core TRUS SBx (volume dependent) |
Thompson (2014) [56] | Prospective | 2012–2013 | FB (88%) & PNB (12%) | 150 | 62.4* (IQR 55.0–66.4) | 5.6* (IQR 4.5–7.5) | 40* (IQR 30–57) | 1.5 T (47%) & 3 T (53%) | T2WI/DWI/DCEI | No | PI-RADS v1 | ≥3 | Median of 30 TPBx (volume dependent) |
Pokorny (2014) [43] | Prospective | 2012–2013 | FB | 223 | 63* (IQR 57–68) | 5.3* (IQR 4.1–6.6) | 41* (IQR 30–59) | 3 T | T2WI/DWI/DCEI | No | PI-RADS v1 | ≥3 (primary); ≥4 |
12-core TRUS SBx + TBx |
Petrillo (2014) [42] | Prospective | 2009–2010 | NR | 136 | NR | NR | NR | 1.5 T | T2WI/DWI/MRSI | Yes | 1–5 scale (Likert) | ≥3 | 12–16-core TRUS SBx (volume + PSA dependent) |
Javali (2014) [29] | Retrospective | 2002–2011 | NR | 140 | Control: 62.4 (10.5); Study: 62.9 (12.1) | Control: 6.8 (2.3); Study: 6.87 (2.6) | Control: 44 (14.2); Study: 43 (18.4) | 1.5 T | T2WI/MRSI | Yes | Dichotomous | Cit/[Cho + Cr] < 1.2 | 6-core TRUS SBx ( n = 69), 12-core TRUS SBx ( n = 119) |
Abd-Alazeez (2014) [13] | Prospective | 2007–2011 | FB | 129 | 62* (41–82) | 5.8* (1.2–20) | 40* (16–137) | 1.5 & 3 T | T2WI/DWI/DCEI | No | PI-RADS v1 | ≥3 (primary); ≥4 |
20-core TPBx |
Abd-Alazeez (2014) [12] | Retrospective | NR | PNB | 54 | 64* (39–75) | 10* (2–23) | 53* (19–136) | 1.5 & 3 T | T2WI/DWI/DCEI | No | PI-RADS v1 | ≥3 (primary); ≥4 |
≥20-core TPBx + TBx ( n = 15) |
Matsuoka (2014) [37] | Prospective | 2007–2012 | NR | 135 | 67* (50–80) | 7.0* (2.9–19.8) | 25.4* (12.7–90.2) | 1.5 T | T2WI/DWI | No | 1–5 scale (Likert) | ≥3 | 14-core TRUS SBX |
Junker (2013) [30] | Retrospective | 2011–2013 | PNB | 73 | 62 (7.4) | 7.0* (5.1–12.9) | 45* (34–61) | 3 T | T2WI/DWI/DCEI | No | PI-RADS | PI-RADS ≥10 and ≥11 for all PCa PI-RADS ≥13 for significant PCa |
10-core TRUS SBx + TBx |
Busetto (2013) [16] | Prospective | 2010–2012 | PNB | 163 | 66.4 (5.3) | 6.8 (1.6) | NR | 3 T | T2WI/DWI/DCEI/MRSI | Yes | NR | NR | 10-core TRUS SBx + TBx |
Rais-Bahrami (2013) [47] | Prospective | 2007–2012 | NR | 583 | 61.3 (8.4) | 9.9 (13.1) | NR | 3 T | T2WI/DWI/DCEI/MRSI | Yes | 1–4 scale (Likert) | ≥2 ≥3 |
12-core TRUS SBx + TBx |
Kuru (2013) [34] | Prospective | 2010–2011 | FB (51%) & PNB (49%) | 347 | 65.3 (42–82) | 9.85 (0.5–104) | 48.7 (9–180) | 3 T | T2WI/DWI/DCEI | No | 1–3 scale (Likert) | ≥2 | 12–36-core TRUS SBx (volume dependent) + TBx |
Ferda (2013) [20] | Prospective | NR | NR | 164 | (49–74) | (4.2–123) | NR | 3 T | T2WI/DWI/DCEI/MRSI | No | NR | In house | TRUS SBx |
Ganie (2013) [21] | NR | 2007–2009 | PNB | 87 | NR | NR | NR | 1.5 T | T2WI/MRSI | Yes | MRSI Cho/Cit ratio | In house | 6 core TRUS SBx + MRI TBx |
Vinet (2013) [57] | Prospective | 2009–2011 | FB | 69 | NR | 5.2* (3.2–28) | NR | 1.5 T (35 pts) & 3 T (34 pts) | T2WI/DWI/DCEI | No | 1–5 scale (Likert) | ≥3 | 12-core TRUS SBx + TBx |
Numao (2013) [38] | Prospective | 2006–2010 | FB | 351 | 65* (59–70) | 6.3* (4.9–9.1) | 32* (24–42) | 1.5 T | T2WI/DWI/DCEI (no DCEI in 42 pts) | No | 1–5 scale (Likert) | ≥3 | 3D 26-core (12 TRUS SBx + 14 TPBx – 203 pts); 3D 14-core (6 TRUS SBx + 8 TPBx – 102 pts); TPBx 14 core (46 pts) |
Belas (2012) [14] | Prospective | 2010–2011 | FB | 71 | 66* (47–76) | 7* (4–10) | 45* (15–150) | 1.5 T | T2WI/DWI/DCEI | No | TZ: 0–4 scale PZ: 0–10 scale |
TZ: >2 PZ: >6 |
12-core TRUS SBx + TBx |
Ibrahiem (2012) [26] | Prospective | 2008–2009 | FB | 100 | 65.03 (7.13) | 26.3 (24.2) | 60.09 (28.7) | 1.5 T | T2WI/DWI | No | NR | In house | 12-core TRUS SBX |
Sciarra (2012) [51] | Prospective | 2008–2011 | PNB | 84 | 64.09 (46–76) | 7.07 (4.2–15.5) | NR | 3 T | T2WI/DWI/DCEI/MRSI | Yes | NR | NR | 10-core TRUS Bx + TBx |
Portalez (2012) [45] | Prospective | 2011 | PNB | 129 | 64.7 (47–79) | 9.6 (2.7–40) | 51.1 (12–192) | 1.5 T | T2WI/DWI/DCEI | Mixed | 1–5 scale (Likert) PI-RADS |
Likert ≥3 PI-RADS ≥9 |
10–12-core TRUS SBx + TBx |
Watanabe (2012) [59] | Prospective | 2004–2008 | NR | 1448 | 72 (7.5) | NR | NR | 1.5 T | T2WI/DWI | No | NR | ADC value ≤1.35 × 10 −3 mm 2 /s | 8-core TRUS SBx + TBx |
Tamada (2011) [54] | Retrospective | 2006–2009 | NR | 50 | 70 (40–84) | 6.84* (4.06–9.94) | NR | 1.5 T | T2WI/DWI/DCEI | No | NR | In house | 12-core TRUS SBx |
Choi (2011) [18] | NR | 2009–2010 | NR | 51 | 67.16 (56–90) | 14.16 (1.02–38.9) | 42.98 (13.8–77.3) | 3 T | T2WI/DWI | NR | NR | NR | 10–12-core TRUS SBx + TBx |
Iwazawa (2011) [28] | Retrospective | 2008–2009 | NR | 178 | 68.8 (41–86) | 20.51 (4.04–568.5) | NR | 1.5 T | T2WI/DWI/DCEI | NR | 1–4 scale (Likert) | NR | 10–12-core TRUS SBx (TBx included in SBx chart) |
Rouse (2011) [48] | Prospective | 2005–2007 | PNB | 114 | 63.6 (41–83) | 13.4 (0–228) | NR | 1.5 T | T2WI/DWI/DCEI | NR | 1–5 scale (Likert) | ≥3 | TRUS SBx |
Haffner (2011) [23] | Prospective | 2005–2009 | FB | 555 | 64* (47–83) | 6.75* (0.18–100) | 46* (15–200) | 1.5 T | T2WI/DCEI | No | 1–5 scale (Likert) | ≥3 | 10-core TRUS SBx + TBx |
Panebianco (2010) [40] | Prospective | 2007–2009 | PNB | 150 | 61.2 (46–78) | 9.42 (3.91) | 41.17 (7.47) | 1.5 T | T2WI/DCEI/MRSI | Yes | NR | In house | 10-core TRUS SBx (TBx included in SBx chart) |
Roy (2010) [49] | Not specified | 2011–2009 | FB (53%) & PNB (47%) | 103 | 63 (52–78) | 7* | NR | 3 T | T2WI/DWI/DCEI | Yes | NR | NR | 8-core TRUS SBx + TBx |
Testa (2010) [55] | Not specified | 2007 | PNB | 54 | 63.9 (52–76) | 11.4 (3–42) | 59.3 (30–150) | 1.5 T | T2WI/MRSI | Yes | 1–3 scale (Likert) | ≥2 | 12-core TRUS SBx + TBx |
Sciarra (2010) [52] | Prospective | 2007–2009 | PNB | 110 | 63.5 (49–74) | NR | NR | 1.5 T | T2WI/DCEI/MRSI | Yes | NR | In house | 10-core TRUS SBx + TBx |
Kitajima (2010) [31] | Prospective | 2008–2009 | NR | 53 | 69* (56–84) | 11.1* (4.2–112.1) | NR | 3 T | T2WI/DWI/DCEI | No | 1–5 scale (Likert) | ≥3 | 20-core TPBx |
Labanaris (2010) [35] | Prospective | 2004–2008 | PNB | 260 | NR | NR | NR | 1 T | T2WI/DWI/DCEI | Yes | Dichotomous | In house | 18-core TRUS SBx |
Kumar (2009) [32] | NR | NR | NR | 61 | 65.3 (9.3) | 16.5 (0.21–155) | NR | 1.5 T | T2WI/MRSI | Yes | NR | (Cit/(Cho + Cr) ≤ 1.2 | TRUS Bx |
Schmuecking (2009) [50] | NR | NR | FB & PNB | 67 | 68 | 11.5 | NR | 1.5 T | T2WI/DCEI | No | NR | NR | 20-core Bx |
Cheikh (2009) [17] | Retrospective | 2005–2008 | PNB | 93 | 63.2 (52–74) | 9.63 (1.6–40) | NR | 1.5 T | T2WI/DCEI | No | Dichotomous | In house | 12-core TRUS SBx + TBx |
Cirillo (2008) [19] | Prospective | 2004–2006 | PNB | 54 | 65.5 (5.2) | 10.8 (7.5) | NR | 1.5 T | T2WI/MRSI | Yes | Dichotomous | In house | 10-core TRUS SBx + TBx |
Kumar (2007) [33] | Prospective | 2003–2005 | NR | 83 | NR | NR | NR | 1.5 T | T2WI/MRSI | Yes | NR | NR | 12-core TRUS SBx + TBx |
Squillaci (2005) [53] | Prospective | 2004–2005 | NR | 65 | NR | NR | NR | 1.5 T | T2WI/DCEI/MRSI | No | 1–3 scale (Likert) | ≥2 | 10-core TRUS SBx + TBx |
Hara (2005) [24] | Prospective | 2003–2004 | FB | 90 | 67.2 (NR) | NR | NR | 1.5 T | T2WI/DCEI | No | 1–3 scale (Likert) | ≥2 = 3 |
14-core TRUS SBx |
The magnetic field strength was 1, 1.5, and 3 T in one, 28, and 15 studies, respectively. Four studies used both 1.5 and 3 T MR systems. DWI and DCEI were used in 36 and 35 studies, respectively. Nineteen studies also added MRSI. An endorectal coil was used in 18 studies. The definition of positive mpMRI varied across studies. The PI-RADS v1 score was used in 12 studies, a five-level subjective (Likert) score was used in eight studies, and one study reported data based on the two scoring systems. In-house criteria were used in 13 studies for defining positive mpMRI, and five studies used a dichotomous definition. Nine studies did not report on the criteria for positive mpMRI. No study used the PI-RADS v2 score.
Regarding the reference standard, TRUS-guided biopsies were used in 39 studies, TTP biopsies in six studies, and mixed TRUS-guided and TTP biopsies in two studies. In one study, the biopsy approach was unclear. The number of cores per biopsy procedure was ≤16 in 30 studies, >16 in nine studies, and variable among patients in three studies. For six studies, the number of biopsy cores taken was unclear.
At patient level, the median biopsy positivity rate (ie, cancer prevalence) was 50.4% (IQR, 36.4–57.7%) for overall cancer and 32.9% (IQR, 28.1–37.2%) for csPCa ( Table 2 ). The median mpMRI NPV was 82.4% (IQR, 69.0–92.4%) for overall cancer and 88.1% (IQR, 85.7–92.3) for csPCa. NPV significantly decreased when cancer prevalence increased, both for overall cancer ( r = –0.64, p < 0.0001) and csPCa ( r = –0.75, p = 0.032; Fig. 3 ). In addition, NPV was highly dependent on the definition used for csPCa, with differences of up to 21% when several definitions were used in the same dataset [12 13 38 47 48] .
Study | Overall PCa prevalence (%) | Reporting level | Multiparametric MRI performance for PCa detection | Definition of csPCa | csPCa prevalence | Multiparametric MRI performance for csPCa detection | ||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
TN | FN | TP | FP | NPV | PPV | TN | FN | TP | FP | NPV | PPV | |||||
Hauth (2015) [25] | 45.7 | Patient | 6 | 1 | 42 | 45 | 85.7% | 48.3% | Low grade: GS ≤ 6 High grade: GS ≥ 7 |
NR | NR | NR | NR | NR | NR | NR |
Lesion | 59 | 13 | 55 | 73 | 81.9% | 43% | ||||||||||
Lamb (2015) [36] | 65.9 | Patient | 23 | 22 | 92 | 36 | 51.1% | 71.9% | GS ≥ 7 | 50.9% | 31 | 14 | 71 | 57 | 68.9% | 55.5% |
Brock (2015) [15] | 42.3 | Patient | 17 | 7 | 56 | 88 | 70.8% | SBx: 38.8% TBx: 22.2% Duo: 44.4% |
Epstein: GS > 6 and/or max CCL ≥50% | 24.4% | SBx: 21 | SBx: 3 | SBx: 38 TBx: 27 duo: 47 |
SBx: 106 TBx: 117 duo: 97 |
87.5% | SBx: 26.4% TBx: 18.8% duo: 32.6% |
Grenabo Bergdahl (2016) [22] | 33.7 | Patient | 36 | 7 | 19 | 21 | 83.7% | 47.5% | Clinically insignificant PCa: T1c, PSAd < 0.15, GS < 7, ≤2 positive cores, and unilateral cancer | NR | NR | NR | NR | NR | NR | NR |
Wang (2015) [58] | 58 | Patient | 165 | 8 | 332 | 81 | 95.4% | 80.4% | NR | NR | NR | NR | NR | NR | NR | NR |
Pepe (2015) [41] | 37 | Patient | 23 | 8 | 29 | 40 | 74.2% | 42% | GS ≥ 7 or GS 6 with CCL ≥ 50% | NR | NR | NR | NR | NR | 100% | 55.8% |
Panebianco (2015) [39] | 74.7 | Patient | Group A (satBx): 104 | Group A (satBx): 43 | Group A: 186 | Group A: 22 | Group A (satBx): 70.7% | Group A: 89.4% | NR | 60% | Group A: 147 | Group A: 0 | Group A: 183 | Group A: 25 | Group A: 100% | Group A: 88% |
Group B (TRUSGB NR TRUS G satBx): 93 | Group B (TRUSGB NR TRUS G satBx): 37 | Group B: 417 before and 425 after satBx | Group B: 23/440 and 15/440 after satBx. | Group B (TRUSGB–TRUS G satBx): 71.5% | Group B: 94.8% before and 96.6% after satBx | 71.9% | Group B: 130 | Group B: 0 | Group B: 410 |
Group B: 30 | Group B: 100% | Group B: 93.2% | ||||
Radtke (2015) [46] | 51 | Patient | ≥2/5: 80 ≥3: 103 ≥4: 138 = 5: 142 |
≥2/5: 18 ≥3/5: 38 ≥4/5: 78 = 5/5: 126 |
≥2/5: 132 ≥3/5: 112 ≥4/5: 72 = 5/5: 24 |
≥2/5: 64 ≥3/5: 41 ≥4/5: 6 = 5/5: 2 |
≥2/5: 81.6% ≥ 3/5: 73.1% ≥ 4/5: 63.9% = 5/5: 53% |
≥2/5: 67.4% ≥ 3/5: 73.2% ≥ 4/5: 92.3% = 5/5: 92.3% |
GS ≥ 7 | 29.3% | ≥2/5: 91 ≥3/5: 124 ≥4/5: 183 = 5/5: 203 |
≥2/5: 7 ≥3/5: 17 ≥4/5: 33 = 5/5: 65 |
≥2/5: 79 ≥3/5: 69 ≥4/5: 53 = 5/5: 21 |
≥2/5: 117 ≥3/5: 84 ≥4/5: 25 = 5/5: 5 |
≥2/5: 92.2% ≥3/5: 87.9% ≥4/5: 84.7% = 5/5: 75.8% |
≥2/5: 40.3% ≥3/5: 45.1% ≥4/5: 68% = 5/5: 80.7% |
Itatani (2014) [27] | 13 | Patient | 168 | 25 | NR | NR | 87% | NR | (1) PSAd ≥ 0.1 or GP 4/5 or ≥ 3/6 pos cores; max CCL < 50% (2) PSAd ≥ 0.15 or GP 4/5 or max core length invasion < 3 mm (min 6 cores) |
NR | NR | NR | NR | NR | NR | NR |
Porpiglia (2014) [44] | 30.6 | Patient | 107 | 5 | 47 | 11 | 95.5% | 81% | NR | NR | NR | NR | NR | NR | NR | NR |
Thompson (2014) [56] | 61.3 | Patient | 35 | 16 | 76 | 23 | 68.6% | 76.7% | Moderate or high risk Moderate risk: GS 7 (GP4 >5%) and <50% of positive cores or GS 6–7 (GP4 ≤ 5%) and either ≥30% of positive cores or max core length invasion ≥8 mm High risk: GS ≥ 7 (GP4 > 5%); ≥50% + cores or GS ≥ 8 |
34% | 49 | 2 | 49 | 50 | 96% | 49.5% |
Pokorny (2014) [43] | 63.7 | Patient | ≥3/5: 56 ≥4/5: 74 |
≥3/5: 25 ≥4/5: 40 |
≥3/5: 101 ≥4/5: 86 |
≥3/5: 41 ≥4/5: 23 |
≥3/5: 69.1% ≥4/5: 64.9% |
≥3/5: 71.1% ≥4/5: 78.9% |
NR | NR | NR | NR | NR | NR | NR | NR |
Petrillo (2014) [42] | 18.4 | Patient | 56 | 4 | 21 | 55 | 93% | 28% | NR | NR | NR | NR | NR | NR | NR | NR |
Javali (2014) [29] | 16.4 | Patient | 49 | 1 | 22 | 68 | 98% | 24.4% | NR | NR | NR | NR | NR | NR | NR | NR |
Abd-Alazeez (2014) [13] | 54.7 | Lobe | ≥3/5: 33 | ≥3/5: 14 | ≥3/5: 127 | ≥3/5: 84 | ≥3/5: 70% | ≥3/5: 60% | Def 1: GS ≥ 4 + 3 and/or max CCL ≥ 6 mm Def 2: GS ≥ 3 + 4 and/or max CCL ≥ 4 mm Def 3: GS ≥ 4 + 3 Def 4: GS ≥ 3 + 4 Def 5: max CCL ≥ 6 mm Def 6: max CCL ≥ 4 mm |
Def 1: NR Def 2: 44.2% Def 3: 23.2% Def 4: 36% Def 5: 32.9% Def 6: 39.5% |
Def 1: 46 Def 2: 42 Def 3: 47 Def 4: 43 Def 5: 46 Def 6: 43 |
Def 1: 1 Def 2: 5 Def 3: 0 Def 4: 4 Def 5: 1 Def 6: 4 |
Def 1: 45 Def 2: 72 Def 3: 13 Def 4: 50 Def 5: 39 Def 6: 59 |
Def 1: 166 Def2: 139 Def 3: 198 Def 4: 161 Def 5: 172 Def 6: 152 |
Def 1: 98 Def 2: 89 Def 3: 100 Def 4: 92 Def 5: 98 Def 6: 91 |
Def 1: 21 Def 2: 34 Deg 3: 6 Def 4: 24 Def 5: 19 Def 6: 28 |
≥4/5: 87 | ≥3/5: 62 | ≥3/5: 79 | ≥3/5: 30 | ≥3/5: 58% | ≥3/5: 73% | Def 1: 140 Def 2: 124 Def 3: 148 Def 4: 133 Def 5: 141 Def 6: 131 |
Def 1: 9 Def 2: 25 Def 3: 1 Def 4: 16 Def 5: 8 Def 6: 18 |
Def 1: 37 Def 2: 52 Def 3: 12 Def 4: 38 Def 5: 32 Def 6: 45 |
Def 1: 72 Def 2: 57 Def 3: 97 Def 4: 71 Def 5: 77 Def 6: 64 |
Def 1: 94 Def 2: 83 Def 3: 99 Def 4: 89 Def 5: 95 Def 6: 88 |
Def 1: 34 Def 2: 48 Def 3: 11 Def 4: 35 Def 5: 30 Def 6: 42 |
|||||
Abd-Alazeez (2014) [12] | 47.2 | Lobe | ≥3/5: 26 | ≥3/5: 13 | ≥3/5: 38 | ≥3/5: 31 | ≥3/5: 66% | ≥3/5: 55% | Def 1: GS ≥ 4 + 3 and/or max CCL ≥ 6 mm Def 2: GS ≥ 3 + 4 and/or max CCL ≥ 4 mm Def 3: GS ≥ 4 + 3 Def 4: GS ≥ 3 + 4 Def 5: max CCL ≥ 6 mm Def 6: max CCL ≥ 4 mm |
Def 1: 18.5% Def 2: 31.5% Def 3: 4.6% Def 4: 21.3% Def 5: 16.7% Def 6: 25% |
Def 1: 37 Def 2: 31 Def 3: 39 Def 4: 36 Def 5: 37 Def 6: 32 |
Def 1: 2 Def 2: 8 Def 3: 0 Def 4: 3 Def 5: 2 Def 6: 7 |
Def 1: 18 Def 2: 26 Def 3: 5 Def 4: 20 Def 5: 16 Def 6: 20 |
Def 1: 51 Def 2: 43 Def 3: 64 Def 4: 49 Def 5: 53 Def 6: 49 |
Def 1: 95 Def 2: 79 Def 3: 100 Def 4: 92 Def 5: 95 Def 6: 82 |
Def 1: 26 Def 2: 38 Def 3: 7 Def 4: 29 Def 5: 23 Def 6: 29 |
≥4/5: 49 | ≥4/5: 25 | ≥4/5: 26 | ≥4/5: 8 | ≥4/5: 66% | ≥4/5: 76% | Def 1: 70 Def 2: 63 Def 3: 73 Def 4: 68 Def 5: 70 Def 6: 64 |
Def 1: 4 Def 2: 11 Def 3: 1 Def 4: 6 Def 5: 4 Def 6: 10 |
Def 1: 16 Def 2: 23 Def 3: 4 Def 4: 17 Def 5: 14 Def 6: 17 |
Def 1: 18; Def 2: 11 Def 3: 30 Def 4: 17 Def 5: 20 Def 6: 17 |
Def 1: 94 Def 2: 85 Def 3: 99 Def 4: 92 Def 5: 94 Def 6: 86 |
Def 1: 47 Def 2: 67 Def 3: 12 Def 4: 50 Def 5: 41 Def 6: 49 |
|||||
Matsuoka (2014) [37] | 64.8 | Lobe | 46 | 49 | 149 | 26 | 48.4% | 85.1% | NR | NR | NR | NR | NR | NR | NR | NR |
Junker (2013) [30] | 53.4 | Patient | ≥10/15: 21 ≥11/15: 28 |
≥10/15: 4 ≥11/15: 12 |
≥10/15: 35 ≥11/15: 27 |
≥10/15: 13 ≥11/15: 6 |
≥10/15: 84% ≥11/15: 70% |
≥10/15: 72.9% ≥11/15: 81.8% |
GS ≥ 4 + 3 | 13.7% | ≥13: 54 | ≥13: 2 | ≥13: 8 | ≥13: 9 | ≥13: 96.4% | ≥13: 47% |
Busetto (2013) [16] | 41.7 | Patient | 59 | 7 | 61 | 36 | 89% | 63% | NR | NR | NR | NR | NR | NR | NR | NR |
Rais-Bahrami (2013) [47] | 54.2 | Patient | ≥2/4 : 80 | ≥2/4: 275 | ≥2/4: 187 | ≥2/4: 275 | ≥2/4: 66% | ≥2/4: 59% | GS ≥ 7: GS ≥ 8 |
31.7% | NR | NR | NR | NR | GS ≥ 7: 91% GS ≥ 8: 91% |
GS ≥ 7: 38% GS ≥ 8: 18% |
≥3/4: 251 | ≥3/4: 76 | ≥3/4: 16 | ≥3/4: 76 | ≥3/4: 51% | ≥3/4: 82% | NR | NR | NR | NR | GS ≥ 7: 75% GS ≥ 8: 91% |
GS ≥ 7: 67% GS ≥ 8: 41% |
|||||
Kuru (2013) [34] | 57.6 | Patient | 80 | 14 | 67 | 186 | 85.1% | 73.5% | NR | NR | NR | NR | NR | NR | NR | NR |
Ferda (2013) [20] | 51.2 | Patient | 52 | 2 | 82 | 28 | 96.3% | 74.5% | NR | NR | NR | NR | NR | NR | NR | NR |
Ganie (2013) [21] | 74.7 | Patient | 13 | 3 | 62 | 9 | 59.1% | 95.4% | NR | NR | NR | NR | NR | NR | NR | NR |
Vinet (2013) [57] | 49.3 | Patient | ≥3/5: 11 | ≥3/5: 6 | ≥3/5: 28 | ≥3/5: 24 | ≥3/5: 64.7% | ≥3/5: 53.8% | NR | NR | NR | NR | NR | NR | NR | NR |
≥4/5: 22 | ≥4/5: 11 | ≥4/5: 23 | ≥4/5: 13 | ≥4/5: 66.7% | ≥4/5: 63.8% | NR | NR | NR | NR | NR | NR | NR | NR | |||
Numao (2013) [38] | 45 | Patient | 137 | 57 | 101 | 56 | 70.6% | 64.3% | Def 1: GS ≥4 + 3 and/or ≥20% positive cores and/or max CCL ≥5 mm Def 2: GS ≥ 3 + 4 and/or ≥20% + cores and/or max CCL ≥5 mm Def 3: GS ≥ 3 + 4 and/or ≥20% + cores |
Def 1: 33.3% Def 2:37.8% Def 3: 35.8% |
Def 1: 74 Def 2: 65 Def 3: 69 |
Def 1: 83 Def 2: 92 Def 3: 88 |
Def 1: 160 Def 2: 153 Def 3: 156 |
Def 1: 34 Def 2: 41 Def 3: 38 |
Def 1: 82.4% Def 2: 78.8% Def 3: 80.4% |
Def 1: 58.8% Def 2: 58.5% Def 3: 56% |
Belas (2012) [14] | 53.5 | Patient | 22 | 12 | 23 | 13 | 64.7% | 63.8% | NR | NR | NR | NR | NR | NR | NR | NR |
Ibrahiem (2012) [26] | 73.9 | Patient | 14 | 11 | 57 | 10 | 56% | 85.1% | NR | NR | NR | NR | NR | NR | NR | NR |
Sciarra (2012) [51] | 34.5 | Patient | 41 | 4 | 25 | 14 | 91.1% | 64.1% | NR | NR | NR | NR | NR | NR | NR | NR |
Portalez (2012) [45] | 48.1 | Lesion | Likert: 357 | Likert: 50 | Likert: 81 | Likert: 50 | Likert: 95% | Likert: 38% | Max CCL >3 mm and/or GG 4/5 | NR | NR | NR | NR | NR | NR | NR |
PI-RADS: 404 | PI-RADS: 47 | PI-RADS: 34 | PI-RADS: 47 | PI-RADS: 95% | PI-RADS: 58% | |||||||||||
Watanabe (2012) [59] | 48.1 | Patient | 485 | 73 | 624 | 266 | 86.9% | 70.1% | NR | NR | NR | NR | NR | NR | NR | NR |
Tamada (2011) [54] | 70 | Patient | 12 | 6 | 29 | 3 | 67% | 91% | NR | NR | NR | NR | NR | NR | NR | NR |
Region | 277 | 48 | 55 | 20 | 85% | 73% | ||||||||||
Choi (2011) [18] | 70.6 | Patient | 9 | 5 | 31 | 6 | 64.2% | 75.7% | NR | NR | NR | NR | NR | NR | NR | NR |
Iwazawa (2011) [28] | 40.5 | Region | 887 | 86 | 232 | 219 | 91.1% | 51.4% | NR | NR | NR | NR | NR | NR | NR | NR |
Rouse (2011) [48] | 33.7 | Sextant | 145 | 11 | 74 | 22 | 92.9% | 77.1% | GS ≥ 7: Def 1: ≥3 mm Def 2: ≥5 mm |
Def 1: 26.6% Def 2: 26.2% |
Def 1: 153 Def 2: 153 |
Def 1: 3 Def 2: 3 |
Def 1: 64 Def 1: 63 |
Def 1: 32 Def 2: 33 |
Def 1: 98.1% Def 2: 98.1% |
Def 1: 68.1% Def 2: 67% |
59.6 | Patient | 24 | 14 | 54 | 22 | 63.2% | 71.1% | Def 1: 41.2% Def 2: 36.8% |
Def 1: 30 Def 2: 31 |
Def 1: 4 Def 2: 3 |
Def 1: 43 Def 2: 39 |
Def 1: 4 Def 2: 3 |
Def 1: 88.2% Def 2: 91.2% |
Def 1: 53.8% Def 2: 48.8% |
||
Haffner (2011) [23] | 54.4 | Patient | 154 | 50 | 240 | 111 | 75.4% | 68.3% | NR | NR | NR | NR | NR | NR | NR | NR |
Panebianco (2010) [40] | 42.7 | Patient | NR | NR | NR | NR | 95.1% | 88.2% | NR | NR | NR | NR | NR | NR | NR | NR |
Roy (2010) [49] | 55.9 | Patient | NR | NR | NR | NR | 71% | 75% | NR | NR | NR | NR | NR | NR | NR | NR |
Testa (2010) [55] | 40.7 | Patient | NR | NR | NR | NR | 79.3% | 64% | NR | NR | NR | NR | NR | NR | NR | NR |
Sciarra (2010) [52] | 50 | Patient | 61 | 4 | 66 | 9 | 93.8% | 88% | NR | NR | NR | NR | NR | NR | NR | NR |
Kitajima (2010) [31] | 56.6 | Patient | 311 | 19 | 80 | 14 | 92.2% | 85.1% | NR | NR | NR | NR | NR | NR | NR | NR |
Labanaris (2010) [35] | 73.9 | Patient | 17 | 73 | 96 | 74 | 81.11% | 56.47% | NR | NR | NR | NR | NR | NR | NR | NR |
Kumar (2009) [32] | 21.7 | Patient | 39 | 3 | 10 | 8 | 92.8% | 55% | NR | NR | NR | NR | NR | NR | NR | NR |
Schmuecking (2009) [50] | NR | Lobe | NR | NR | NR | NR | 96% | 61% | NR | NR | NR | NR | NR | NR | NR | NR |
Cheikh (2009) [17] | 24.7 | Patient | 36 | 12 | 11 | 34 | 80% | 22.9% | NR | NR | NR | NR | NR | NR | NR | NR |
Cirillo (2008) [19] | 31.5 | Patient | 19 | 0 | 17 | 18 | 100% | 48.6% | NR | NR | NR | NR | NR | NR | NR | NR |
Kumar (2007) [33] | 13.3 | Patient | 39 | 0 | 11 | 33 | 100% | 25% | NR | NR | NR | NR | NR | NR | NR | NR |
Squillaci (2005) [53] | 50.8 | Patient | 29% | 8% | 25% | 3% | 89% | 80% | NR | NR | NR | NR | NR | NR | NR | NR |
Hara (2005) [24] | 41.5 | Patient | ≥2/3: 40 = 3/3: 47 |
≥2/3: 4 = 3/3: 8 |
≥2/3 30 = 3/3: 26 |
≥2/3: 8 = 3/3: 1 |
≥2/3: 90% = 3/3: 85% |
≥2/3: 78.9% = 3/3: 96.3% |
NR | NR | NR | NR | NR | NR | NR | NR |
Cancer prevalence tended to be higher and mpMRI NPV lower in the biopsy-naïve group as compared with the repeat biopsy group, in men with positive DRE as compared with men with negative DRE and when an endorectal coil was not used ( Table 3 ). There were no clear differences in the prevalence and NPV of the other analysed subgroups (TRUS-guided vs TTP biopsy, biopsy procedures with ≤16 cores vs >16 cores; Table 3 ). However, comparisons must be interpreted with care, due to the small number of studies in some subgroups. In patients with a PSA level of ≤10 ng/ml, the median NPV for overall PCa was 86.3% (IQR, 73.3–93.6%) for a median cancer prevalence of 35.4% (IQR, 27.6–42.5%).
Nb of studies | Median PCa prevalence | Median mpMRI NPV | Nb of studies | Median csPCa prevalence | Median mpMRI NPV | |
---|---|---|---|---|---|---|
Biopsy-naïve patients | 8 | 51.4% (45.5–56.7) | 69.9% (64.2–78) | 1 | 35.8% (NA) | 80.4% (NA) |
Repeat biopsy | 14 | 42% (35.1–52.6) | 82.6% (75.5–93.1) | 3 | 24.4% (19.1–32.8) | 88.2% (87.9–92.3) |
TRUS-guided biopsy | 36 | 49.7% (34.3–57.7) | 84.6% (68.6–92.8) | 4 | 28.1% (21.7–36.5) | 89.3% (82.9–92.4) |
TTP biopsy | 4 | 53.8% (47.5–57.8) | 73.6% (72–78.7) | 2 | 31.6% (30.5–32.8) | 92% (89.9–94) |
Biopsy with ≤16 cores | 28 | 48.7% (39.2–54.8) | 81.9% (66.8–89.3) | 5 | 28.1% (21.8–36.5) | 89.3% (82.9–92.4) |
Biopsy with >16 cores | 5 | 56.6% (51–61.3) | 81.1% (73.1–92.2) | 2 | 31.7% (30.5–32.8) | 92% (89.9–93.9) |
Positive DRE | 1 | 73.9% (NA) | 56% (NA) | 0 | – | – |
Negative DRE | 6 | 36% (34.6–46.8) | 82.7% (74.2–93.1) | 0 | – | – |
Endorectal coil | 17 | 41.7% (30.6–55.9) | 92.8% (79.3–95.4) | 1 | 31.7% (NA) | 91% (NA) |
No endorectal coil | 22 | 50.9% (41.7–56.1) | 77.7% (69.5–86.6) | 7 | 34% (26.9–46.1%) | 87.9% (78.2–92.1) |
Eight studies reported NPV at patient level for overall PCa and fulfilled the inclusion criteria for meta-analysis ( Table 4 ) [22 25 38 41 43 46 56 57] .
Study | Prevalence a (%) | Neg MRI (%) | NPV (%) | PPV (%) | Spe (%) | Se (%) | ||
---|---|---|---|---|---|---|---|---|
All PCa | Score ≥ 3/5 | Grenabo Bergdahl (2016) [22] | 31.3 | 66.9 | 83.7 | 47.5 | 63.2 | 73.1 |
Numao (2013) [38] | 45 | 29.4 | 70.6 | 64.3 | 71.0 | 63.9 | ||
Hauth (2015) [25] | 45.7 | 14.3 | 85.7 | 48.3 | 11.8 | 97.7 | ||
Vinet (2013) [57] | 49.3 | 24.6 | 64.7 | 53.8 | 31.4 | 82.4 | ||
Radtke (2015) [46] | 51 | 27 | 73 | 73.2 | 71.5 | 74.7 | ||
Thompson (2014) [56] | 61.3 | 31.4 | 68.6 | 76.8 | 60.3 | 82.6 | ||
Pokorny (2014) [43] | 63.7 | 30.9 | 69.1 | 82.4 | 69.1 | 82.4 | ||
Score ≥ 4/5 | Pepe (2015) [41] | 37 | 31 | 74.2 | 42 | 36.5 | 78.4% | |
Vinet (2013) [57] | 49.3 | 47.8 | 66.7 | 63.9 | 62.9 | 67.6% | ||
Radtke (2015) [46] | 51 | 73.5 | 63.9 | 92.3 | 95.8 | 48% | ||
Gleason ≥7 PCa | Score ≥ 3/5 | Radtke (2015) [46] | 29.3 | 27 | 87.9 | 45.1 | 59.6 | 80.2% |
a Prevalence of overall prostate cancers (10 first lines) or Gleason ≥7 cancers (last line).
PCa = prostate cancer; MRI = magnetic resonance imaging; Neg MRI = proportion of negative magnetic resonance imaging; NPV = negative predictive value; PPV = positive predictive value; Se = sensitivity; Spe = specificity.
Seven studies used a score of ≥3/5 for defining positive mpMRI ( Fig. 4 A and B) [22 25 38 43 46 56 57] . Fig. 4 C shows the conditional probability plot of 1 – NPV and PPV as a function of overall PCa prevalence. Table 5 shows NPV and PPV estimates for the given values of PCa prevalence.
PCaPrev | PPV | NPV |
---|---|---|
0.30 | 0.43 (0.34–0.53) | 0.88 (0.77–0.99) |
0.40 | 0.54 (0.45–0.64) | 0.82 (0.70–0.94) |
0.50 | 0.64 (0.55–0.73) | 0.76 (0.64–0.88) |
0.60 | 0.73 (0.65–0.80) | 0.67 (0.56–0.79) |
0.70 | 0.81 (0.75–0.87) | 0.57 (0.47–0.67) |
0.75 | 0.84 (0.79–0.89) | 0.51 (0.42–0.59) |
Only three studies used a score of ≥4/5 for defining positive mpMRI ( Table 4 ) [41 46 57] , and a formal meta-analysis could not be performed.
Only one study reporting NPV at patient level for Gleason ≥7 cancers met the selection criteria for inclusion in the meta-analysis. It reported NPV and PPV of 87.9% and 45.1%, respectively, for a prevalence of 29.3% ( Table 4 ) [46] .
We observed a large variability in reported NPV. Many factors, such as differences in mpMRI protocols, definition of negative mpMRI, or biopsy protocols, can explain this variability. However, two major causes of variability must be pointed out. First, the cancer prevalence was highly variable, ranging at patient level from 13% to 74.7% for overall PCa, and from 13.7% to 50.9% for csPCa. This variability was observed in both the biopsy-naïve and the repeat biopsy setting. As NPV depends on prevalence, this had a major impact on reported NPV ( Fig. 3 ). Second, the definition of csPCa was highly variable from one series to another, and differences of up to 21% could be observed in NPV when different definitions of csPCa were used in the same dataset [12 13 38 47 48] .
To account for clinical heterogeneity and to further explore the clinical relevance of the results, we carefully selected studies for inclusion in the meta-analysis based on stringent criteria. Particularly, we included only studies that: (1) had biopsy protocols with at least 10 cores, since it is no longer recommended to obtain less than 10 cores per biopsy; (2) used DWI, which is the most informative technique, at least for cancers in the peripheral zone [60] ; and (3) reported mpMRI findings using a five-level score, so that negative findings could be better defined. We accepted studies using a subjective (Likert) scale because experienced readers obtained equivalent [45 61 62] or better [63] results with the Likert score than with the PI-RADS v1 score. Owing to the large variations of NPV induced by differences in definitions of csPCa, we did not include different definitions in the meta-analysis since this would have introduced unacceptable clinical heterogeneity in the results, possibly resulting in erroneous and biased estimates. We, therefore, a priori restricted the definition of csPCa to cancers with a Gleason score of ≥7, given the low lethal potential of Gleason 6 cancers [64] and the lack of consensus among pathologists on the best method to measure biopsy core invasion length [65 66] .
In this more homogeneous group of studies, the prevalence range was still large (31.3–63.7%). As a result, we modelled the evolution of NPV (and PPV) as a function of overall PCa prevalence. Unfortunately, we could not duplicate this for csPCa since only one study reporting NPV for Gleason ≥7 cancers met the inclusion criteria for meta-analysis.
We included only studies that reported the results of systematic/standard biopsy in patients with negative mpMRI and used the systematic/standard biopsy as a reference standard. It is well known that TRUS-guided biopsy harbours both random and systematic errors, as evidenced by the high rates of positivity of immediate repeat biopsy after a first series of negative biopsies [67 68] , and as confirmed recently by the PROMIS trial [69] . Therefore, using TRUS-guided biopsy as a reference standard may have overestimated the NPV of mpMRI. However, studies using radical prostatectomy specimens as a reference standard have already reported mpMRI detection rates in relation to PCa Gleason score and volume [1] . In this review, we intended to address the more pragmatic question as to whether a negative mpMRI could predict a negative subsequent biopsy. This is an important question because if the NPV of mpMRI was sufficiently high in comparison with the reference standard of systematic/standard biopsies, then in practice a negative mpMRI result could indeed avoid the need for prostate biopsy. Therefore, studies reporting only biopsy results when the mpMRI was positive (eg, obtained through MRI-targeted, guided, or fusion biopsies with added systematic biopsies) were not included in this review.
It is now well established that mpMRI is a sensitive tool for detecting aggressive PCa 1 2 3 69] . However several reasons preclude its broad use as a triage test before biopsy.
Firstly, the population referred to prostate biopsy is not standardised. The large range of reported prevalence for overall PCa and csPCa suggests substantial heterogeneity in the way patients are selected for biopsy. Owing to this heterogeneity, we did not provide a pooled estimate for mpMRI NPV. The role of mpMRI as a triage test before prostate biopsy should be evaluated in the broader context of the selection of patients with a suspicion of (aggressive) PCa. In a recent retrospective study of 514 patients, mpMRI NPV for Gleason ≥7 cancers was 91% when the PSA density was ≤0.2 ng/ml/ml, and only 71% when the PSA density was >0.2 ng/ml/ml ( p = 0.003) [70] . In another series of 288 biopsy-naïve patients, no csPCa (Gleason score ≥7 or maximum cancer core length ≥4 mm) was found in 44 patients with a PSA density of <0.15 ng/ml/ml and a PI-RADS v2 score of <3/5 [71] . We believe that such prestratification of the risk of csPCa is an interesting way for rationalising the use of mpMRI before biopsy. Patients found at very low risk would be spared both mpMRI and biopsy. Patients at a low risk—for whom mpMRI would have an NPV high enough to be used as a triage test—could avoid biopsy in case of negative mpMRI. Patients at a higher risk would need biopsy even in case of negative mpMRI. Many tools can be used to risk stratify the population of patients referred to biopsy, ranging from simple parameters such as PSA density to more complicated risk calculators [72 73] . The impact of these tools on the NPV of prebiopsy mpMRI needs to be carefully evaluated, both in the biopsy-naïve and in the repeat biopsy setting. For the moment, it is impossible to make any recommendations on the best way to risk stratify patients before referring them for mpMRI.
Secondly, the large variability in the definition of csPCa precludes any definitive conclusion on the ability of mpMRI to rule out aggressive cancer. The issue of the most appropriate definition of csPCa on biopsy is complex, since biopsy results may accurately reflect neither tumour burden nor aggressiveness. Nonetheless, there is an urgent need to standardise the histological definition(s) of csPCa, to allow meaningful comparisons between studies.
Thirdly, the specificity of mpMRI remains moderate, and there is a substantial proportion of false positives in the lesions scored 3/5 or 4/5 [1 74 75] , even with the new PI-RADS v2 score [76] . In a series of 62 patients with 116 lesions biopsied under magnetic resonance/ultrasound fusion, the overall cancer detection rates for PI-RADS v2 scores of 3/5 and 4/5 were only 15.8% and 29.8%, respectively [77] . In theory, a triage test used to rule out a disease needs to be highly sensitive for this disease. However, if its specificity is too low, it will be clinically useless since most patients will be positive, whether they have the disease or not. Therefore, if mpMRI is to be used as a triage test in the future, there is a need to improve its specificity. This could be achieved by a continuous refinement of scores [78] . Promising results in characterising csPCa have also been reported with a quantitative analysis [79] .
Finally, all published studies were conducted in specialised centres. The broad use of mpMRI as a triage test assumes good interobserver reproducibility. Unfortunately, interobserver reproducibility of existing scoring systems remains moderate [62 63 80] even with the use of the PI-RADS v2 score [80 81] . Studies evaluating on a large scale the reproducibility of mpMRI findings between expert and nonexpert centres are currently lacking.
Three systematic reviews (including two meta-analyses) regarding the role of mpMRI in localised PCa have been published recently 4 5 6 . Crucially, all three reviews focused exclusively on the sensitivity of mpMRI-targeted, guided, or fusion biopsies in diagnosing overall PCa and csPCa, using TRUS-guided prostate biopsies as reference standards. The impact of systematic biopsies on the outcome was not addressed in any of the reviews, within either the index test or the reference standard. Our review had a totally different research question and objective, focusing on NPV of mpMRI to see if a negative mpMRI can avoid the need for a prostate biopsy. As MRI-targeted/guided/fusion biopsies are not relevant if the mpMRI was negative for cancer, it can be argued that the three reviews assessed a different index test altogether. As such, we believe that the findings of this review are novel and unique, and pave the way for further focused clinical studies.
The current study represents the first systematic review addressing the role of mpMRI as a triage test before biopsy. The review elements were developed in conjunction with a multidisciplinary panel of experts (EAU Prostate Cancer Guidelines Panel), which included a patient representative, and the review was performed robustly in accordance with recognised standards. However, it is limited by the major heterogeneity of the existing literature in patient population, study design, and definitions of positive mpMRI and csPCa. It highlighted further areas of research that could help in defining the best use of mpMRI in the early detection of aggressive PCa in the future.
Although mpMRI can detect aggressive PCa with excellent sensitivity, a definitive conclusion on its role as a triage test before prostate biopsy will be possible only when three main issues are addressed. Firstly, because NPV depends on prevalence, and because overall PCa and csPCa prevalence was highly variable in the published series, it becomes mandatory to define the optimal way to pre-evaluate the risk of csPCa in patients with a suspicion of PCa. Depending on the risk category, mpMRI could then be used to obviate biopsies or not. Secondly, there is a need for consensus definitions of csPCa on biopsy findings to allow interstudy comparisons. Thirdly, although efforts have been made to standardise mpMRI technical protocols and interpretation in the past few years [11 60 76] , there is still a crucial need to improve mpMRI specificity and inter-reader reproducibility.
This systematic review was performed under the auspices of:
The European Association of Urology Guidelines Office Board
The European Association of Urology Prostate Cancer Guideline Panel
Author contributions: Olivier Rouvière had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.
Study concept and design: Rouvière, Mottet, Cornford.
Acquisition of data: Rouvière, Moldovan, Van den Broeck, Yuan.
Analysis and interpretation of data: Rouvière, Moldovan, Van den Broeck, Lam.
Drafting of the manuscript: Rouvière, Moldovan, Van den Broeck, Lam.
Critical revision of the manuscript for important intellectual content: Bellmunt, van den Bergh, Bolla, Briers, Van den Broeck, Cornford, Cumberbatch, De Santis, Fossati, Gross, Henry, Joniau, Lam, Matveev, Moldovan, van der Poel, van der Kwast, Rouvière, Schoots, Wiegel, Mottet.
Statistical analysis: None.
Obtaining funding: None.
Administrative, technical, or material support: Yuan, Sylvester, Marconi.
Supervision: None.
Other: None.
Financial disclosures: Olivier Rouvière certifies that all conflicts of interest, including specific financial interests and relationships and affiliations relevant to the subject matter or materials discussed in the manuscript (eg, employment/affiliation, grants or funding, consultancies, honoraria, stock ownership or options, expert testimony, royalties, or patents filed, received, or pending), are the following: Bellmunt is a company consultant for Janssen, Astellas, Pierre Fabre, Genentech, Merck, Ipsen, Pfizer, Novartis, and Sanofi Aventis. He has received research support from Takeda, Novartis, and Sanofi, and received travel grants from Pfizer and Pierre Fabre. Bolla has received company speaker honoraria from Ipsen and Astellas, honoraria or consultation fees from Janssen, and fellowship and travel grants from Janssen, AstraZeneca, and Astellas. Briers has received grant and research support from Ipsen, European Association of Urology, and Bayer; is an ex officio board member for Europa UOMO; is an ethics committee and advisory group member for REQUITE; is a member patient advisory board member for PAGMI; and is a member of SCA and EMA PCWP. Cornford is a company consultant for Astellas, Ipsen, and Ferring. He receives company speaker honoraria from Astellas, Janssen, Ipsen, and Pfizer; participates in trials from Ferring; and receives fellowships and travel grants from Astellas and Janssen. De Santis is a company consultant for GlaxoSmithKline, Janssen, Bayer, Novartis, Pierre Fabre, Astellas, Amgen, Eisai Inc., ESSA, Merck, and Synthon; has received company speaker honoraria from Pfizer, Takeda, Sanofi Aventis, Shionogi, Celgene, and Teva OncoGenex; has participated in trials for Pierre Fabre, Astellas, Exelixis, Bayer, and Roche; has received fellowship and travel grants from Bayer, Novartis, Ferring, Astellas, Sanofi Aventis, and Janssen; has received grant and research support from Pierre Fabre; has received honoraria from AstraZeneca; and is associated with Amgen. Joniau is a company consultant for Astellas, Ipsen, Bayer, Sanofi, and Janssen; has received company speaker honoraria from Astellas, Amgen, Bayer, Sanofi, Janssen, and Ipsen; has participated in trials for Astellas, Janssen, and Bayer; has received fellowship and travel grants from Astellas, Amgen, Bayer, Sanofi, Janssen, Ipsen, and Pfizer; and has received grant and research support from Astellas, Bayer, and Janssen. Matveev has received company speaker honoraria from Sanofi and Astellas, has participated in trials for Astellas, Pfizer and Novartis. Lam is a company consultant for and has received company speaker honoraria from Pfizer, GSK, Astellas, and Ipsen. van der Poel is a company consultant for Intuitive Surgical, has participated in trials for Astellas and Steba Biotech, and has received grant and research support from Astellas. Rouvière is a company consultant for EDAP-TMS, Bracco, and Philips; has received company speaker honoraria from EDAP-TMS, Bracco, and Philips; and has participated in trials for EDAP-TMS and Bracco. Wiegel has received company speaker honoraria from Astellas, Takeda, Hexal, Ipsen, Janssen-Cilac, and Ferring. Mottet has received grant and research support from Takeda Pharmaceutical, Millenium, Astellas, Pierre Fabre, Sanofi, and Pasteur, and has received honoraria or consultation fees from Takeda Pharaceutical, Millenium, Jansen, Astellas, BMS, Bayer, Ipsen, Ferring, Novartis, Nuclétron, Pierre Fabre, Sanofi, and Zeneca. van den Bergh, Van den Broeck, Cumberbatch, Fossati, Gross, Henry, van der Kwast, Sylvester, Yuan, Schoots, Moldovan, and Marconi have nothing to disclose.
Funding/Support and role of the sponsor: None.
A correlation with radical prostatectomy specimens has demonstrated that multiparametric magnetic resonance imaging (mpMRI) has excellent sensitivity in detecting prostate cancer (PCa) with a Gleason score of ≥7 1 2 3 . As a result, prostate mpMRI is increasingly used in patients with a suspicion of PCa to localise abnormal areas before biopsy. A large body of literature has shown that targeted biopsies of suspicious lesions seen on mpMRI (TBx) improved the detection of clinically significant PCa (csPCa), at least in the repeat biopsy setting 4 5 6 . As a result, it is now recommended that an mpMRI is performed before repeat biopsy to allow TBx of suspicious lesions in addition to standard biopsies [7] .
Some authors have recently suggested that, besides improving csPCa detection, mpMRI could also be used as a triage test so that patients with negative mpMRI findings could obviate biopsy. Such a strategy remains highly controversial [8] and depends upon the negative predictive value (NPV) of mpMRI. Therefore, the European Association of Urology Prostate Cancer Guidelines Panel undertook this systematic review and meta-analysis to assess the NPV of mpMRI in patients with a suspicion of PCa and, thus, its potential role in eliminating unnecessary prostate biopsy.
Our primary aim was to systematically evaluate the performance of negative prebiopsy prostate mpMRI in predicting a negative biopsy result for overall PCa and csPCa in biopsy-naïve men and in men with previously negative biopsies. A further objective was to explore and define factors that may contribute to relevant thresholds in order to provide guidance for future studies.
The review was performed according to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) statement [9] . The review protocol was published in PROSPERO database ( http://www.crd.york.ac.uk/PROSPERO; registration number CRD42015021929). Databases searched included the Embase and OVID Medline databases, the Cochrane database of systematic reviews, and the Cochrane Central Register for Clinical Trials, covering from January 1, 2000 to February 13, 2016. Systematic or standard prostate biopsies were used as reference standards, with positive or negative cases of PCa being determined by histopathological examination. The detailed search strategy is presented in Supplement 1.
Included studies focused on men who were assessed for suspected PCa by mpMRI before undergoing prostate biopsy. Studies enrolling both biopsy-naïve men and men who had undergone previous negative biopsies were included. Prebiopsy prostate mpMRI was considered the index test and comprised T2-weighted imaging (T2WI) and at least one functional imaging technique (diffusion-weighted imaging [DWI], dynamic contrast-enhanced imaging [DCEI], or magnetic resonance spectroscopic imaging [MRSI]). For inclusion, studies had to report on false negatives and true negatives, in order to calculate NPV (ie, results of systematic/standard prostate biopsies when the mpMRI was negative). When available, false positive and true positive findings were also noted to calculate the positive predictive value (PPV) and the cancer prevalence. There was restriction neither on the biopsy technique (transrectal or transperineal) nor on the number of biopsy cores. Studies using radical prostatectomy specimens as reference standards were excluded, as were studies evaluating men with histologically proven PCa. Studies with less than 50 participants were excluded. No language restrictions were applied.
Two reviewers (P.C.M. and T.V.D.B.) independently screened all abstracts and full-text articles for eligibility. Disagreement was resolved by consensus or reference to an independent third party (L.M.). All screening was performed using a predefined eligibility form.
Using a data extraction form developed a priori, the same two reviewers independently extracted data concerning study methodology, patient characteristics, technical characteristics of the MR scanners, mpMRI protocol, mpMRI scoring system, definition of positive mpMRI, biopsy protocol, and definition of csPCa. Any discrepancies concerning data extraction were resolved by consensus or reference to an independent arbiter (O.R. or T.B.L.).
To assess the risk of bias (RoB), all included reports were reviewed using the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool for diagnostic accuracy studies [10] .
Outcome data regarding false negative and true negative values of mpMRI before prostate biopsy were recorded as reported by authors. When not available, data were indirectly derived from specificity, sensitivity, and prevalence values reported by authors using an online Bayesian statistics calculator ( http://www.medcalc.com/bayes.html ). Descriptive statistics were used to summarise baseline characteristics and outcomes, including median and interquartile range (IQR) for estimates of NPV across studies. A correlation between mpMRI NPV and a positive biopsy rate was established using the Pearson's correlation coefficient.
A meta-analysis was undertaken to calculate pooled NPV and PPV. To ensure appropriate clinical homogeneity of the studies included in the meta-analysis, we selected only the studies enrolling biopsy-naïve patients and/or patients with a history of negative biopsy, and fulfilling the following criteria that were defined a priori: (1) reference standard consisting of prostate biopsy with at least 10 samples on all patients; (2) mpMRI protocol comprising at least T2WI and DWI; (3) mpMRI results presented as a five-level score, using a subjective Likert scale or the Prostate Imaging Reporting Data System (PI-RADS) score [11] ; (4) definition of positive mpMRI as a score ≥3/5 or ≥4/5; and (5) results reported on a per patient basis. In addition, only studies defining csPCa as Gleason ≥7 cancers were selected for the meta-analysis assessing the mpMRI NPV for csPCa. A bivariate random-effects approach was employed using the Midas package in Stata 12 (StataCorp LP, College Station, TX, USA). Since the NPV decreases and the PPV increases as the prevalence increases, post-test probability estimates of NPV and PPV were reported for the given values of the prevalence based on Bayes’ theorem.
For other studies not included in the meta-analysis based on the criteria described above, a narrative synthesis of the data was performed. To explore and define clinical heterogeneity, subgroups were analysed at patient level based on the following variables: biopsy-naïve versus previous negative biopsy; patients with positive versus negative digital rectal examination (DRE); mpMRI performed with an endorectal versus without an endorectal coil; transrectal ultrasound (TRUS) versus template transperineal (TTP) biopsy approach; and ≤16 cores versus >16 cores as the reference standard. Studies reporting mpMRI NPV for patients with a prostate-specific antigen (PSA) level of ≤10 ng/ml were also reported separately.
The study selection process is depicted in the PRISMA flow diagram ( Fig. 1 ). A total of 2980 abstracts were retrieved. After abstract screening and removal of duplicates, 240 articles were eligible for full text screening, of which 48 studies were eligible for inclusion 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 .
Out of the 48 included studies, 42 were single-centre and six were multicentre studies. Thirty-four studies were prospective and six were retrospective, whilst the design of the rest was unclear. RoB assessment using QUADAS-2 was performed for each of the individual studies ( Fig. 2 A and B). Overall, the RoB was highly heterogeneous across studies for all criteria, except for the reference standard domain, in which RoB was low in most studies.
The 48 studies comprised a total of 9613 men who underwent prostate mpMRI followed by biopsy. The study and patient baseline characteristics are presented in Table 1 . The patient population consisted of biopsy-naive men in nine studies, men with at least one previous negative biopsy in 16 studies, and both biopsy-naïve men and men with a history of previous negative biopsy in nine studies. In 14 studies, the biopsy history of the patients was unclear.
Study | Study design | Period | Population | Pt Nb | Mean/median* age (yr) | Mean/median* PSA (ng/ml) | Mean/median* prostate volume (cm 3 ) | Magnetic field strength | MR pulse sequences | Endorectal coil | MR score | Definition of positive MRI | Reference standard |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Hauth (2015) [25] | Prospective | 2011–2013 | FB | 94 | 64 (43–83) | 9 (3–31) | 51 (17–140) | 1.5 T | T2WI/DWI/DCEI/MRSI | No | PI-RADS v1 | ≥3 | 11–13-core TRUS SBx + TBx |
Lamb (2015) [36] | Retrospective | 2013–2013 | FB & PNB | 173 | NR | NR | NR | 1.5 T | T2WI/DWI | NR | NR | NR | 12-core TRUS SBx |
Brock (2015) [15] | Prospective | 2013–2014 | PNB | 168 | 64* (IQR 59–70) | 9.2* (IQR 6.7–13.4) | 55.4* (IQR 42–80) | 3 T | T2WI/DWI/DCEI | No | PI-RADS v1 | NR | 12/24-core TRUS SBx + TBx |
Grenabo Bergdahl (2016) [22] | Prospective | 2013–2014 | FB & PNB | 83 | 69.3* (IQR 69–69.6) | 1.6* (IQR 0.9–2.7) | NR | 3 T | T2WI/DWI/DCEI/MRSI | No | PI-RADS v1 | ≥3 | 10-core TRUS SBx + TBx |
Wang (2015) [58] | Prospective | 2002–2009 | FB & PNB | 586 | 70 (26–91) | 11.11* (0.02–9794) | NR | 1.5 T | T2WI/DWI/DCEI/MRSI | Yes | PI-RADS v1 | ≥3 | TRUS SBx |
Pepe (2015) [41] | Prospective | 2011–2014 | PNB | 100 | 64* | 8.6* (4.2–10) | NR | 3 T | T2WI/DWI/DCEI/MRSI | No | PI-RADS v1 | ≥4 | TPBx + TBx |
Panebianco (2015) [39] | Prospective | 2011–2014 | FB (61.62%) & PNB (38.34%) | 925 (1140 total cohort) |
NR | NR | NR | 3 T | T2WI/DWI/DCEI | Yes | PI-RADS v1 | NR | 14-core TRUS SBx; 45-core sat TPBx + TBx |
Radtke (2015) [46] | Prospective | 2013–2013 | FB (63.3%) & PNB (36.7%) | 294 | 64* (60–71) | 7.3 (6.0) | 47 (37.5) | 3 T | T2WI/DWI/DCEI | No | PI-RADS v1 | PI-RADS ≥2; PI-RADS ≥3; PI-RADS ≥4; PI-RADS = 5; |
24-core TPBx + TBx |
Itatani (2014) [27] | Retrospective | 2004–2007 | NR | 193 | 68.9 (8.4); 70* (47–89) | 11.8 (15.9); 7.9* (1.22–159) | NR | 1.5 T | T2WI/DWI/DCEI | No | 1–5 scale (Likert) | ≥3 | 12–14-core TRUS SBx |
Porpiglia (2014) [44] | Prospective | 2011–2013 | PNB | 170 | 65* (60–70) | 6.9* (5.2–9.8) | 42* (36–48) | 1.5 T | T2WI/DWI/DCEI | Yes | Dichotomous | Positive: at least 2/3 MR seq. with suspicious findings | 18–24-core TRUS SBx (volume dependent) |
Thompson (2014) [56] | Prospective | 2012–2013 | FB (88%) & PNB (12%) | 150 | 62.4* (IQR 55.0–66.4) | 5.6* (IQR 4.5–7.5) | 40* (IQR 30–57) | 1.5 T (47%) & 3 T (53%) | T2WI/DWI/DCEI | No | PI-RADS v1 | ≥3 | Median of 30 TPBx (volume dependent) |
Pokorny (2014) [43] | Prospective | 2012–2013 | FB | 223 | 63* (IQR 57–68) | 5.3* (IQR 4.1–6.6) | 41* (IQR 30–59) | 3 T | T2WI/DWI/DCEI | No | PI-RADS v1 | ≥3 (primary); ≥4 |
12-core TRUS SBx + TBx |
Petrillo (2014) [42] | Prospective | 2009–2010 | NR | 136 | NR | NR | NR | 1.5 T | T2WI/DWI/MRSI | Yes | 1–5 scale (Likert) | ≥3 | 12–16-core TRUS SBx (volume + PSA dependent) |
Javali (2014) [29] | Retrospective | 2002–2011 | NR | 140 | Control: 62.4 (10.5); Study: 62.9 (12.1) | Control: 6.8 (2.3); Study: 6.87 (2.6) | Control: 44 (14.2); Study: 43 (18.4) | 1.5 T | T2WI/MRSI | Yes | Dichotomous | Cit/[Cho + Cr] < 1.2 | 6-core TRUS SBx ( n = 69), 12-core TRUS SBx ( n = 119) |
Abd-Alazeez (2014) [13] | Prospective | 2007–2011 | FB | 129 | 62* (41–82) | 5.8* (1.2–20) | 40* (16–137) | 1.5 & 3 T | T2WI/DWI/DCEI | No | PI-RADS v1 | ≥3 (primary); ≥4 |
20-core TPBx |
Abd-Alazeez (2014) [12] | Retrospective | NR | PNB | 54 | 64* (39–75) | 10* (2–23) | 53* (19–136) | 1.5 & 3 T | T2WI/DWI/DCEI | No | PI-RADS v1 | ≥3 (primary); ≥4 |
≥20-core TPBx + TBx ( n = 15) |
Matsuoka (2014) [37] | Prospective | 2007–2012 | NR | 135 | 67* (50–80) | 7.0* (2.9–19.8) | 25.4* (12.7–90.2) | 1.5 T | T2WI/DWI | No | 1–5 scale (Likert) | ≥3 | 14-core TRUS SBX |
Junker (2013) [30] | Retrospective | 2011–2013 | PNB | 73 | 62 (7.4) | 7.0* (5.1–12.9) | 45* (34–61) | 3 T | T2WI/DWI/DCEI | No | PI-RADS | PI-RADS ≥10 and ≥11 for all PCa PI-RADS ≥13 for significant PCa |
10-core TRUS SBx + TBx |
Busetto (2013) [16] | Prospective | 2010–2012 | PNB | 163 | 66.4 (5.3) | 6.8 (1.6) | NR | 3 T | T2WI/DWI/DCEI/MRSI | Yes | NR | NR | 10-core TRUS SBx + TBx |
Rais-Bahrami (2013) [47] | Prospective | 2007–2012 | NR | 583 | 61.3 (8.4) | 9.9 (13.1) | NR | 3 T | T2WI/DWI/DCEI/MRSI | Yes | 1–4 scale (Likert) | ≥2 ≥3 |
12-core TRUS SBx + TBx |
Kuru (2013) [34] | Prospective | 2010–2011 | FB (51%) & PNB (49%) | 347 | 65.3 (42–82) | 9.85 (0.5–104) | 48.7 (9–180) | 3 T | T2WI/DWI/DCEI | No | 1–3 scale (Likert) | ≥2 | 12–36-core TRUS SBx (volume dependent) + TBx |
Ferda (2013) [20] | Prospective | NR | NR | 164 | (49–74) | (4.2–123) | NR | 3 T | T2WI/DWI/DCEI/MRSI | No | NR | In house | TRUS SBx |
Ganie (2013) [21] | NR | 2007–2009 | PNB | 87 | NR | NR | NR | 1.5 T | T2WI/MRSI | Yes | MRSI Cho/Cit ratio | In house | 6 core TRUS SBx + MRI TBx |
Vinet (2013) [57] | Prospective | 2009–2011 | FB | 69 | NR | 5.2* (3.2–28) | NR | 1.5 T (35 pts) & 3 T (34 pts) | T2WI/DWI/DCEI | No | 1–5 scale (Likert) | ≥3 | 12-core TRUS SBx + TBx |
Numao (2013) [38] | Prospective | 2006–2010 | FB | 351 | 65* (59–70) | 6.3* (4.9–9.1) | 32* (24–42) | 1.5 T | T2WI/DWI/DCEI (no DCEI in 42 pts) | No | 1–5 scale (Likert) | ≥3 | 3D 26-core (12 TRUS SBx + 14 TPBx – 203 pts); 3D 14-core (6 TRUS SBx + 8 TPBx – 102 pts); TPBx 14 core (46 pts) |
Belas (2012) [14] | Prospective | 2010–2011 | FB | 71 | 66* (47–76) | 7* (4–10) | 45* (15–150) | 1.5 T | T2WI/DWI/DCEI | No | TZ: 0–4 scale PZ: 0–10 scale |
TZ: >2 PZ: >6 |
12-core TRUS SBx + TBx |
Ibrahiem (2012) [26] | Prospective | 2008–2009 | FB | 100 | 65.03 (7.13) | 26.3 (24.2) | 60.09 (28.7) | 1.5 T | T2WI/DWI | No | NR | In house | 12-core TRUS SBX |
Sciarra (2012) [51] | Prospective | 2008–2011 | PNB | 84 | 64.09 (46–76) | 7.07 (4.2–15.5) | NR | 3 T | T2WI/DWI/DCEI/MRSI | Yes | NR | NR | 10-core TRUS Bx + TBx |
Portalez (2012) [45] | Prospective | 2011 | PNB | 129 | 64.7 (47–79) | 9.6 (2.7–40) | 51.1 (12–192) | 1.5 T | T2WI/DWI/DCEI | Mixed | 1–5 scale (Likert) PI-RADS |
Likert ≥3 PI-RADS ≥9 |
10–12-core TRUS SBx + TBx |
Watanabe (2012) [59] | Prospective | 2004–2008 | NR | 1448 | 72 (7.5) | NR | NR | 1.5 T | T2WI/DWI | No | NR | ADC value ≤1.35 × 10 −3 mm 2 /s | 8-core TRUS SBx + TBx |
Tamada (2011) [54] | Retrospective | 2006–2009 | NR | 50 | 70 (40–84) | 6.84* (4.06–9.94) | NR | 1.5 T | T2WI/DWI/DCEI | No | NR | In house | 12-core TRUS SBx |
Choi (2011) [18] | NR | 2009–2010 | NR | 51 | 67.16 (56–90) | 14.16 (1.02–38.9) | 42.98 (13.8–77.3) | 3 T | T2WI/DWI | NR | NR | NR | 10–12-core TRUS SBx + TBx |
Iwazawa (2011) [28] | Retrospective | 2008–2009 | NR | 178 | 68.8 (41–86) | 20.51 (4.04–568.5) | NR | 1.5 T | T2WI/DWI/DCEI | NR | 1–4 scale (Likert) | NR | 10–12-core TRUS SBx (TBx included in SBx chart) |
Rouse (2011) [48] | Prospective | 2005–2007 | PNB | 114 | 63.6 (41–83) | 13.4 (0–228) | NR | 1.5 T | T2WI/DWI/DCEI | NR | 1–5 scale (Likert) | ≥3 | TRUS SBx |
Haffner (2011) [23] | Prospective | 2005–2009 | FB | 555 | 64* (47–83) | 6.75* (0.18–100) | 46* (15–200) | 1.5 T | T2WI/DCEI | No | 1–5 scale (Likert) | ≥3 | 10-core TRUS SBx + TBx |
Panebianco (2010) [40] | Prospective | 2007–2009 | PNB | 150 | 61.2 (46–78) | 9.42 (3.91) | 41.17 (7.47) | 1.5 T | T2WI/DCEI/MRSI | Yes | NR | In house | 10-core TRUS SBx (TBx included in SBx chart) |
Roy (2010) [49] | Not specified | 2011–2009 | FB (53%) & PNB (47%) | 103 | 63 (52–78) | 7* | NR | 3 T | T2WI/DWI/DCEI | Yes | NR | NR | 8-core TRUS SBx + TBx |
Testa (2010) [55] | Not specified | 2007 | PNB | 54 | 63.9 (52–76) | 11.4 (3–42) | 59.3 (30–150) | 1.5 T | T2WI/MRSI | Yes | 1–3 scale (Likert) | ≥2 | 12-core TRUS SBx + TBx |
Sciarra (2010) [52] | Prospective | 2007–2009 | PNB | 110 | 63.5 (49–74) | NR | NR | 1.5 T | T2WI/DCEI/MRSI | Yes | NR | In house | 10-core TRUS SBx + TBx |
Kitajima (2010) [31] | Prospective | 2008–2009 | NR | 53 | 69* (56–84) | 11.1* (4.2–112.1) | NR | 3 T | T2WI/DWI/DCEI | No | 1–5 scale (Likert) | ≥3 | 20-core TPBx |
Labanaris (2010) [35] | Prospective | 2004–2008 | PNB | 260 | NR | NR | NR | 1 T | T2WI/DWI/DCEI | Yes | Dichotomous | In house | 18-core TRUS SBx |
Kumar (2009) [32] | NR | NR | NR | 61 | 65.3 (9.3) | 16.5 (0.21–155) | NR | 1.5 T | T2WI/MRSI | Yes | NR | (Cit/(Cho + Cr) ≤ 1.2 | TRUS Bx |
Schmuecking (2009) [50] | NR | NR | FB & PNB | 67 | 68 | 11.5 | NR | 1.5 T | T2WI/DCEI | No | NR | NR | 20-core Bx |
Cheikh (2009) [17] | Retrospective | 2005–2008 | PNB | 93 | 63.2 (52–74) | 9.63 (1.6–40) | NR | 1.5 T | T2WI/DCEI | No | Dichotomous | In house | 12-core TRUS SBx + TBx |
Cirillo (2008) [19] | Prospective | 2004–2006 | PNB | 54 | 65.5 (5.2) | 10.8 (7.5) | NR | 1.5 T | T2WI/MRSI | Yes | Dichotomous | In house | 10-core TRUS SBx + TBx |
Kumar (2007) [33] | Prospective | 2003–2005 | NR | 83 | NR | NR | NR | 1.5 T | T2WI/MRSI | Yes | NR | NR | 12-core TRUS SBx + TBx |
Squillaci (2005) [53] | Prospective | 2004–2005 | NR | 65 | NR | NR | NR | 1.5 T | T2WI/DCEI/MRSI | No | 1–3 scale (Likert) | ≥2 | 10-core TRUS SBx + TBx |
Hara (2005) [24] | Prospective | 2003–2004 | FB | 90 | 67.2 (NR) | NR | NR | 1.5 T | T2WI/DCEI | No | 1–3 scale (Likert) | ≥2 = 3 |
14-core TRUS SBx |
The magnetic field strength was 1, 1.5, and 3 T in one, 28, and 15 studies, respectively. Four studies used both 1.5 and 3 T MR systems. DWI and DCEI were used in 36 and 35 studies, respectively. Nineteen studies also added MRSI. An endorectal coil was used in 18 studies. The definition of positive mpMRI varied across studies. The PI-RADS v1 score was used in 12 studies, a five-level subjective (Likert) score was used in eight studies, and one study reported data based on the two scoring systems. In-house criteria were used in 13 studies for defining positive mpMRI, and five studies used a dichotomous definition. Nine studies did not report on the criteria for positive mpMRI. No study used the PI-RADS v2 score.
Regarding the reference standard, TRUS-guided biopsies were used in 39 studies, TTP biopsies in six studies, and mixed TRUS-guided and TTP biopsies in two studies. In one study, the biopsy approach was unclear. The number of cores per biopsy procedure was ≤16 in 30 studies, >16 in nine studies, and variable among patients in three studies. For six studies, the number of biopsy cores taken was unclear.
At patient level, the median biopsy positivity rate (ie, cancer prevalence) was 50.4% (IQR, 36.4–57.7%) for overall cancer and 32.9% (IQR, 28.1–37.2%) for csPCa ( Table 2 ). The median mpMRI NPV was 82.4% (IQR, 69.0–92.4%) for overall cancer and 88.1% (IQR, 85.7–92.3) for csPCa. NPV significantly decreased when cancer prevalence increased, both for overall cancer ( r = –0.64, p < 0.0001) and csPCa ( r = –0.75, p = 0.032; Fig. 3 ). In addition, NPV was highly dependent on the definition used for csPCa, with differences of up to 21% when several definitions were used in the same dataset [12 13 38 47 48] .
Study | Overall PCa prevalence (%) | Reporting level | Multiparametric MRI performance for PCa detection | Definition of csPCa | csPCa prevalence | Multiparametric MRI performance for csPCa detection | ||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
TN | FN | TP | FP | NPV | PPV | TN | FN | TP | FP | NPV | PPV | |||||
Hauth (2015) [25] | 45.7 | Patient | 6 | 1 | 42 | 45 | 85.7% | 48.3% | Low grade: GS ≤ 6 High grade: GS ≥ 7 |
NR | NR | NR | NR | NR | NR | NR |
Lesion | 59 | 13 | 55 | 73 | 81.9% | 43% | ||||||||||
Lamb (2015) [36] | 65.9 | Patient | 23 | 22 | 92 | 36 | 51.1% | 71.9% | GS ≥ 7 | 50.9% | 31 | 14 | 71 | 57 | 68.9% | 55.5% |
Brock (2015) [15] | 42.3 | Patient | 17 | 7 | 56 | 88 | 70.8% | SBx: 38.8% TBx: 22.2% Duo: 44.4% |
Epstein: GS > 6 and/or max CCL ≥50% | 24.4% | SBx: 21 | SBx: 3 | SBx: 38 TBx: 27 duo: 47 |
SBx: 106 TBx: 117 duo: 97 |
87.5% | SBx: 26.4% TBx: 18.8% duo: 32.6% |
Grenabo Bergdahl (2016) [22] | 33.7 | Patient | 36 | 7 | 19 | 21 | 83.7% | 47.5% | Clinically insignificant PCa: T1c, PSAd < 0.15, GS < 7, ≤2 positive cores, and unilateral cancer | NR | NR | NR | NR | NR | NR | NR |
Wang (2015) [58] | 58 | Patient | 165 | 8 | 332 | 81 | 95.4% | 80.4% | NR | NR | NR | NR | NR | NR | NR | NR |
Pepe (2015) [41] | 37 | Patient | 23 | 8 | 29 | 40 | 74.2% | 42% | GS ≥ 7 or GS 6 with CCL ≥ 50% | NR | NR | NR | NR | NR | 100% | 55.8% |
Panebianco (2015) [39] | 74.7 | Patient | Group A (satBx): 104 | Group A (satBx): 43 | Group A: 186 | Group A: 22 | Group A (satBx): 70.7% | Group A: 89.4% | NR | 60% | Group A: 147 | Group A: 0 | Group A: 183 | Group A: 25 | Group A: 100% | Group A: 88% |
Group B (TRUSGB NR TRUS G satBx): 93 | Group B (TRUSGB NR TRUS G satBx): 37 | Group B: 417 before and 425 after satBx | Group B: 23/440 and 15/440 after satBx. | Group B (TRUSGB–TRUS G satBx): 71.5% | Group B: 94.8% before and 96.6% after satBx | 71.9% | Group B: 130 | Group B: 0 | Group B: 410 |
Group B: 30 | Group B: 100% | Group B: 93.2% | ||||
Radtke (2015) [46] | 51 | Patient | ≥2/5: 80 ≥3: 103 ≥4: 138 = 5: 142 |
≥2/5: 18 ≥3/5: 38 ≥4/5: 78 = 5/5: 126 |
≥2/5: 132 ≥3/5: 112 ≥4/5: 72 = 5/5: 24 |
≥2/5: 64 ≥3/5: 41 ≥4/5: 6 = 5/5: 2 |
≥2/5: 81.6% ≥ 3/5: 73.1% ≥ 4/5: 63.9% = 5/5: 53% |
≥2/5: 67.4% ≥ 3/5: 73.2% ≥ 4/5: 92.3% = 5/5: 92.3% |
GS ≥ 7 | 29.3% | ≥2/5: 91 ≥3/5: 124 ≥4/5: 183 = 5/5: 203 |
≥2/5: 7 ≥3/5: 17 ≥4/5: 33 = 5/5: 65 |
≥2/5: 79 ≥3/5: 69 ≥4/5: 53 = 5/5: 21 |
≥2/5: 117 ≥3/5: 84 ≥4/5: 25 = 5/5: 5 |
≥2/5: 92.2% ≥3/5: 87.9% ≥4/5: 84.7% = 5/5: 75.8% |
≥2/5: 40.3% ≥3/5: 45.1% ≥4/5: 68% = 5/5: 80.7% |
Itatani (2014) [27] | 13 | Patient | 168 | 25 | NR | NR | 87% | NR | (1) PSAd ≥ 0.1 or GP 4/5 or ≥ 3/6 pos cores; max CCL < 50% (2) PSAd ≥ 0.15 or GP 4/5 or max core length invasion < 3 mm (min 6 cores) |
NR | NR | NR | NR | NR | NR | NR |
Porpiglia (2014) [44] | 30.6 | Patient | 107 | 5 | 47 | 11 | 95.5% | 81% | NR | NR | NR | NR | NR | NR | NR | NR |
Thompson (2014) [56] | 61.3 | Patient | 35 | 16 | 76 | 23 | 68.6% | 76.7% | Moderate or high risk Moderate risk: GS 7 (GP4 >5%) and <50% of positive cores or GS 6–7 (GP4 ≤ 5%) and either ≥30% of positive cores or max core length invasion ≥8 mm High risk: GS ≥ 7 (GP4 > 5%); ≥50% + cores or GS ≥ 8 |
34% | 49 | 2 | 49 | 50 | 96% | 49.5% |
Pokorny (2014) [43] | 63.7 | Patient | ≥3/5: 56 ≥4/5: 74 |
≥3/5: 25 ≥4/5: 40 |
≥3/5: 101 ≥4/5: 86 |
≥3/5: 41 ≥4/5: 23 |
≥3/5: 69.1% ≥4/5: 64.9% |
≥3/5: 71.1% ≥4/5: 78.9% |
NR | NR | NR | NR | NR | NR | NR | NR |
Petrillo (2014) [42] | 18.4 | Patient | 56 | 4 | 21 | 55 | 93% | 28% | NR | NR | NR | NR | NR | NR | NR | NR |
Javali (2014) [29] | 16.4 | Patient | 49 | 1 | 22 | 68 | 98% | 24.4% | NR | NR | NR | NR | NR | NR | NR | NR |
Abd-Alazeez (2014) [13] | 54.7 | Lobe | ≥3/5: 33 | ≥3/5: 14 | ≥3/5: 127 | ≥3/5: 84 | ≥3/5: 70% | ≥3/5: 60% | Def 1: GS ≥ 4 + 3 and/or max CCL ≥ 6 mm Def 2: GS ≥ 3 + 4 and/or max CCL ≥ 4 mm Def 3: GS ≥ 4 + 3 Def 4: GS ≥ 3 + 4 Def 5: max CCL ≥ 6 mm Def 6: max CCL ≥ 4 mm |
Def 1: NR Def 2: 44.2% Def 3: 23.2% Def 4: 36% Def 5: 32.9% Def 6: 39.5% |
Def 1: 46 Def 2: 42 Def 3: 47 Def 4: 43 Def 5: 46 Def 6: 43 |
Def 1: 1 Def 2: 5 Def 3: 0 Def 4: 4 Def 5: 1 Def 6: 4 |
Def 1: 45 Def 2: 72 Def 3: 13 Def 4: 50 Def 5: 39 Def 6: 59 |
Def 1: 166 Def2: 139 Def 3: 198 Def 4: 161 Def 5: 172 Def 6: 152 |
Def 1: 98 Def 2: 89 Def 3: 100 Def 4: 92 Def 5: 98 Def 6: 91 |
Def 1: 21 Def 2: 34 Deg 3: 6 Def 4: 24 Def 5: 19 Def 6: 28 |
≥4/5: 87 | ≥3/5: 62 | ≥3/5: 79 | ≥3/5: 30 | ≥3/5: 58% | ≥3/5: 73% | Def 1: 140 Def 2: 124 Def 3: 148 Def 4: 133 Def 5: 141 Def 6: 131 |
Def 1: 9 Def 2: 25 Def 3: 1 Def 4: 16 Def 5: 8 Def 6: 18 |
Def 1: 37 Def 2: 52 Def 3: 12 Def 4: 38 Def 5: 32 Def 6: 45 |
Def 1: 72 Def 2: 57 Def 3: 97 Def 4: 71 Def 5: 77 Def 6: 64 |
Def 1: 94 Def 2: 83 Def 3: 99 Def 4: 89 Def 5: 95 Def 6: 88 |
Def 1: 34 Def 2: 48 Def 3: 11 Def 4: 35 Def 5: 30 Def 6: 42 |
|||||
Abd-Alazeez (2014) [12] | 47.2 | Lobe | ≥3/5: 26 | ≥3/5: 13 | ≥3/5: 38 | ≥3/5: 31 | ≥3/5: 66% | ≥3/5: 55% | Def 1: GS ≥ 4 + 3 and/or max CCL ≥ 6 mm Def 2: GS ≥ 3 + 4 and/or max CCL ≥ 4 mm Def 3: GS ≥ 4 + 3 Def 4: GS ≥ 3 + 4 Def 5: max CCL ≥ 6 mm Def 6: max CCL ≥ 4 mm |
Def 1: 18.5% Def 2: 31.5% Def 3: 4.6% Def 4: 21.3% Def 5: 16.7% Def 6: 25% |
Def 1: 37 Def 2: 31 Def 3: 39 Def 4: 36 Def 5: 37 Def 6: 32 |
Def 1: 2 Def 2: 8 Def 3: 0 Def 4: 3 Def 5: 2 Def 6: 7 |
Def 1: 18 Def 2: 26 Def 3: 5 Def 4: 20 Def 5: 16 Def 6: 20 |
Def 1: 51 Def 2: 43 Def 3: 64 Def 4: 49 Def 5: 53 Def 6: 49 |
Def 1: 95 Def 2: 79 Def 3: 100 Def 4: 92 Def 5: 95 Def 6: 82 |
Def 1: 26 Def 2: 38 Def 3: 7 Def 4: 29 Def 5: 23 Def 6: 29 |
≥4/5: 49 | ≥4/5: 25 | ≥4/5: 26 | ≥4/5: 8 | ≥4/5: 66% | ≥4/5: 76% | Def 1: 70 Def 2: 63 Def 3: 73 Def 4: 68 Def 5: 70 Def 6: 64 |
Def 1: 4 Def 2: 11 Def 3: 1 Def 4: 6 Def 5: 4 Def 6: 10 |
Def 1: 16 Def 2: 23 Def 3: 4 Def 4: 17 Def 5: 14 Def 6: 17 |
Def 1: 18; Def 2: 11 Def 3: 30 Def 4: 17 Def 5: 20 Def 6: 17 |
Def 1: 94 Def 2: 85 Def 3: 99 Def 4: 92 Def 5: 94 Def 6: 86 |
Def 1: 47 Def 2: 67 Def 3: 12 Def 4: 50 Def 5: 41 Def 6: 49 |
|||||
Matsuoka (2014) [37] | 64.8 | Lobe | 46 | 49 | 149 | 26 | 48.4% | 85.1% | NR | NR | NR | NR | NR | NR | NR | NR |
Junker (2013) [30] | 53.4 | Patient | ≥10/15: 21 ≥11/15: 28 |
≥10/15: 4 ≥11/15: 12 |
≥10/15: 35 ≥11/15: 27 |
≥10/15: 13 ≥11/15: 6 |
≥10/15: 84% ≥11/15: 70% |
≥10/15: 72.9% ≥11/15: 81.8% |
GS ≥ 4 + 3 | 13.7% | ≥13: 54 | ≥13: 2 | ≥13: 8 | ≥13: 9 | ≥13: 96.4% | ≥13: 47% |
Busetto (2013) [16] | 41.7 | Patient | 59 | 7 | 61 | 36 | 89% | 63% | NR | NR | NR | NR | NR | NR | NR | NR |
Rais-Bahrami (2013) [47] | 54.2 | Patient | ≥2/4 : 80 | ≥2/4: 275 | ≥2/4: 187 | ≥2/4: 275 | ≥2/4: 66% | ≥2/4: 59% | GS ≥ 7: GS ≥ 8 |
31.7% | NR | NR | NR | NR | GS ≥ 7: 91% GS ≥ 8: 91% |
GS ≥ 7: 38% GS ≥ 8: 18% |
≥3/4: 251 | ≥3/4: 76 | ≥3/4: 16 | ≥3/4: 76 | ≥3/4: 51% | ≥3/4: 82% | NR | NR | NR | NR | GS ≥ 7: 75% GS ≥ 8: 91% |
GS ≥ 7: 67% GS ≥ 8: 41% |
|||||
Kuru (2013) [34] | 57.6 | Patient | 80 | 14 | 67 | 186 | 85.1% | 73.5% | NR | NR | NR | NR | NR | NR | NR | NR |
Ferda (2013) [20] | 51.2 | Patient | 52 | 2 | 82 | 28 | 96.3% | 74.5% | NR | NR | NR | NR | NR | NR | NR | NR |
Ganie (2013) [21] | 74.7 | Patient | 13 | 3 | 62 | 9 | 59.1% | 95.4% | NR | NR | NR | NR | NR | NR | NR | NR |
Vinet (2013) [57] | 49.3 | Patient | ≥3/5: 11 | ≥3/5: 6 | ≥3/5: 28 | ≥3/5: 24 | ≥3/5: 64.7% | ≥3/5: 53.8% | NR | NR | NR | NR | NR | NR | NR | NR |
≥4/5: 22 | ≥4/5: 11 | ≥4/5: 23 | ≥4/5: 13 | ≥4/5: 66.7% | ≥4/5: 63.8% | NR | NR | NR | NR | NR | NR | NR | NR | |||
Numao (2013) [38] | 45 | Patient | 137 | 57 | 101 | 56 | 70.6% | 64.3% | Def 1: GS ≥4 + 3 and/or ≥20% positive cores and/or max CCL ≥5 mm Def 2: GS ≥ 3 + 4 and/or ≥20% + cores and/or max CCL ≥5 mm Def 3: GS ≥ 3 + 4 and/or ≥20% + cores |
Def 1: 33.3% Def 2:37.8% Def 3: 35.8% |
Def 1: 74 Def 2: 65 Def 3: 69 |
Def 1: 83 Def 2: 92 Def 3: 88 |
Def 1: 160 Def 2: 153 Def 3: 156 |
Def 1: 34 Def 2: 41 Def 3: 38 |
Def 1: 82.4% Def 2: 78.8% Def 3: 80.4% |
Def 1: 58.8% Def 2: 58.5% Def 3: 56% |
Belas (2012) [14] | 53.5 | Patient | 22 | 12 | 23 | 13 | 64.7% | 63.8% | NR | NR | NR | NR | NR | NR | NR | NR |
Ibrahiem (2012) [26] | 73.9 | Patient | 14 | 11 | 57 | 10 | 56% | 85.1% | NR | NR | NR | NR | NR | NR | NR | NR |
Sciarra (2012) [51] | 34.5 | Patient | 41 | 4 | 25 | 14 | 91.1% | 64.1% | NR | NR | NR | NR | NR | NR | NR | NR |
Portalez (2012) [45] | 48.1 | Lesion | Likert: 357 | Likert: 50 | Likert: 81 | Likert: 50 | Likert: 95% | Likert: 38% | Max CCL >3 mm and/or GG 4/5 | NR | NR | NR | NR | NR | NR | NR |
PI-RADS: 404 | PI-RADS: 47 | PI-RADS: 34 | PI-RADS: 47 | PI-RADS: 95% | PI-RADS: 58% | |||||||||||
Watanabe (2012) [59] | 48.1 | Patient | 485 | 73 | 624 | 266 | 86.9% | 70.1% | NR | NR | NR | NR | NR | NR | NR | NR |
Tamada (2011) [54] | 70 | Patient | 12 | 6 | 29 | 3 | 67% | 91% | NR | NR | NR | NR | NR | NR | NR | NR |
Region | 277 | 48 | 55 | 20 | 85% | 73% | ||||||||||
Choi (2011) [18] | 70.6 | Patient | 9 | 5 | 31 | 6 | 64.2% | 75.7% | NR | NR | NR | NR | NR | NR | NR | NR |
Iwazawa (2011) [28] | 40.5 | Region | 887 | 86 | 232 | 219 | 91.1% | 51.4% | NR | NR | NR | NR | NR | NR | NR | NR |
Rouse (2011) [48] | 33.7 | Sextant | 145 | 11 | 74 | 22 | 92.9% | 77.1% | GS ≥ 7: Def 1: ≥3 mm Def 2: ≥5 mm |
Def 1: 26.6% Def 2: 26.2% |
Def 1: 153 Def 2: 153 |
Def 1: 3 Def 2: 3 |
Def 1: 64 Def 1: 63 |
Def 1: 32 Def 2: 33 |
Def 1: 98.1% Def 2: 98.1% |
Def 1: 68.1% Def 2: 67% |
59.6 | Patient | 24 | 14 | 54 | 22 | 63.2% | 71.1% | Def 1: 41.2% Def 2: 36.8% |
Def 1: 30 Def 2: 31 |
Def 1: 4 Def 2: 3 |
Def 1: 43 Def 2: 39 |
Def 1: 4 Def 2: 3 |
Def 1: 88.2% Def 2: 91.2% |
Def 1: 53.8% Def 2: 48.8% |
||
Haffner (2011) [23] | 54.4 | Patient | 154 | 50 | 240 | 111 | 75.4% | 68.3% | NR | NR | NR | NR | NR | NR | NR | NR |
Panebianco (2010) [40] | 42.7 | Patient | NR | NR | NR | NR | 95.1% | 88.2% | NR | NR | NR | NR | NR | NR | NR | NR |
Roy (2010) [49] | 55.9 | Patient | NR | NR | NR | NR | 71% | 75% | NR | NR | NR | NR | NR | NR | NR | NR |
Testa (2010) [55] | 40.7 | Patient | NR | NR | NR | NR | 79.3% | 64% | NR | NR | NR | NR | NR | NR | NR | NR |
Sciarra (2010) [52] | 50 | Patient | 61 | 4 | 66 | 9 | 93.8% | 88% | NR | NR | NR | NR | NR | NR | NR | NR |
Kitajima (2010) [31] | 56.6 | Patient | 311 | 19 | 80 | 14 | 92.2% | 85.1% | NR | NR | NR | NR | NR | NR | NR | NR |
Labanaris (2010) [35] | 73.9 | Patient | 17 | 73 | 96 | 74 | 81.11% | 56.47% | NR | NR | NR | NR | NR | NR | NR | NR |
Kumar (2009) [32] | 21.7 | Patient | 39 | 3 | 10 | 8 | 92.8% | 55% | NR | NR | NR | NR | NR | NR | NR | NR |
Schmuecking (2009) [50] | NR | Lobe | NR | NR | NR | NR | 96% | 61% | NR | NR | NR | NR | NR | NR | NR | NR |
Cheikh (2009) [17] | 24.7 | Patient | 36 | 12 | 11 | 34 | 80% | 22.9% | NR | NR | NR | NR | NR | NR | NR | NR |
Cirillo (2008) [19] | 31.5 | Patient | 19 | 0 | 17 | 18 | 100% | 48.6% | NR | NR | NR | NR | NR | NR | NR | NR |
Kumar (2007) [33] | 13.3 | Patient | 39 | 0 | 11 | 33 | 100% | 25% | NR | NR | NR | NR | NR | NR | NR | NR |
Squillaci (2005) [53] | 50.8 | Patient | 29% | 8% | 25% | 3% | 89% | 80% | NR | NR | NR | NR | NR | NR | NR | NR |
Hara (2005) [24] | 41.5 | Patient | ≥2/3: 40 = 3/3: 47 |
≥2/3: 4 = 3/3: 8 |
≥2/3 30 = 3/3: 26 |
≥2/3: 8 = 3/3: 1 |
≥2/3: 90% = 3/3: 85% |
≥2/3: 78.9% = 3/3: 96.3% |
NR | NR | NR | NR | NR | NR | NR | NR |
Cancer prevalence tended to be higher and mpMRI NPV lower in the biopsy-naïve group as compared with the repeat biopsy group, in men with positive DRE as compared with men with negative DRE and when an endorectal coil was not used ( Table 3 ). There were no clear differences in the prevalence and NPV of the other analysed subgroups (TRUS-guided vs TTP biopsy, biopsy procedures with ≤16 cores vs >16 cores; Table 3 ). However, comparisons must be interpreted with care, due to the small number of studies in some subgroups. In patients with a PSA level of ≤10 ng/ml, the median NPV for overall PCa was 86.3% (IQR, 73.3–93.6%) for a median cancer prevalence of 35.4% (IQR, 27.6–42.5%).
Nb of studies | Median PCa prevalence | Median mpMRI NPV | Nb of studies | Median csPCa prevalence | Median mpMRI NPV | |
---|---|---|---|---|---|---|
Biopsy-naïve patients | 8 | 51.4% (45.5–56.7) | 69.9% (64.2–78) | 1 | 35.8% (NA) | 80.4% (NA) |
Repeat biopsy | 14 | 42% (35.1–52.6) | 82.6% (75.5–93.1) | 3 | 24.4% (19.1–32.8) | 88.2% (87.9–92.3) |
TRUS-guided biopsy | 36 | 49.7% (34.3–57.7) | 84.6% (68.6–92.8) | 4 | 28.1% (21.7–36.5) | 89.3% (82.9–92.4) |
TTP biopsy | 4 | 53.8% (47.5–57.8) | 73.6% (72–78.7) | 2 | 31.6% (30.5–32.8) | 92% (89.9–94) |
Biopsy with ≤16 cores | 28 | 48.7% (39.2–54.8) | 81.9% (66.8–89.3) | 5 | 28.1% (21.8–36.5) | 89.3% (82.9–92.4) |
Biopsy with >16 cores | 5 | 56.6% (51–61.3) | 81.1% (73.1–92.2) | 2 | 31.7% (30.5–32.8) | 92% (89.9–93.9) |
Positive DRE | 1 | 73.9% (NA) | 56% (NA) | 0 | – | – |
Negative DRE | 6 | 36% (34.6–46.8) | 82.7% (74.2–93.1) | 0 | – | – |
Endorectal coil | 17 | 41.7% (30.6–55.9) | 92.8% (79.3–95.4) | 1 | 31.7% (NA) | 91% (NA) |
No endorectal coil | 22 | 50.9% (41.7–56.1) | 77.7% (69.5–86.6) | 7 | 34% (26.9–46.1%) | 87.9% (78.2–92.1) |
Eight studies reported NPV at patient level for overall PCa and fulfilled the inclusion criteria for meta-analysis ( Table 4 ) [22 25 38 41 43 46 56 57] .
Study | Prevalence a (%) | Neg MRI (%) | NPV (%) | PPV (%) | Spe (%) | Se (%) | ||
---|---|---|---|---|---|---|---|---|
All PCa | Score ≥ 3/5 | Grenabo Bergdahl (2016) [22] | 31.3 | 66.9 | 83.7 | 47.5 | 63.2 | 73.1 |
Numao (2013) [38] | 45 | 29.4 | 70.6 | 64.3 | 71.0 | 63.9 | ||
Hauth (2015) [25] | 45.7 | 14.3 | 85.7 | 48.3 | 11.8 | 97.7 | ||
Vinet (2013) [57] | 49.3 | 24.6 | 64.7 | 53.8 | 31.4 | 82.4 | ||
Radtke (2015) [46] | 51 | 27 | 73 | 73.2 | 71.5 | 74.7 | ||
Thompson (2014) [56] | 61.3 | 31.4 | 68.6 | 76.8 | 60.3 | 82.6 | ||
Pokorny (2014) [43] | 63.7 | 30.9 | 69.1 | 82.4 | 69.1 | 82.4 | ||
Score ≥ 4/5 | Pepe (2015) [41] | 37 | 31 | 74.2 | 42 | 36.5 | 78.4% | |
Vinet (2013) [57] | 49.3 | 47.8 | 66.7 | 63.9 | 62.9 | 67.6% | ||
Radtke (2015) [46] | 51 | 73.5 | 63.9 | 92.3 | 95.8 | 48% | ||
Gleason ≥7 PCa | Score ≥ 3/5 | Radtke (2015) [46] | 29.3 | 27 | 87.9 | 45.1 | 59.6 | 80.2% |
a Prevalence of overall prostate cancers (10 first lines) or Gleason ≥7 cancers (last line).
PCa = prostate cancer; MRI = magnetic resonance imaging; Neg MRI = proportion of negative magnetic resonance imaging; NPV = negative predictive value; PPV = positive predictive value; Se = sensitivity; Spe = specificity.
Seven studies used a score of ≥3/5 for defining positive mpMRI ( Fig. 4 A and B) [22 25 38 43 46 56 57] . Fig. 4 C shows the conditional probability plot of 1 – NPV and PPV as a function of overall PCa prevalence. Table 5 shows NPV and PPV estimates for the given values of PCa prevalence.
PCaPrev | PPV | NPV |
---|---|---|
0.30 | 0.43 (0.34–0.53) | 0.88 (0.77–0.99) |
0.40 | 0.54 (0.45–0.64) | 0.82 (0.70–0.94) |
0.50 | 0.64 (0.55–0.73) | 0.76 (0.64–0.88) |
0.60 | 0.73 (0.65–0.80) | 0.67 (0.56–0.79) |
0.70 | 0.81 (0.75–0.87) | 0.57 (0.47–0.67) |
0.75 | 0.84 (0.79–0.89) | 0.51 (0.42–0.59) |
Only three studies used a score of ≥4/5 for defining positive mpMRI ( Table 4 ) [41 46 57] , and a formal meta-analysis could not be performed.
Only one study reporting NPV at patient level for Gleason ≥7 cancers met the selection criteria for inclusion in the meta-analysis. It reported NPV and PPV of 87.9% and 45.1%, respectively, for a prevalence of 29.3% ( Table 4 ) [46] .
We observed a large variability in reported NPV. Many factors, such as differences in mpMRI protocols, definition of negative mpMRI, or biopsy protocols, can explain this variability. However, two major causes of variability must be pointed out. First, the cancer prevalence was highly variable, ranging at patient level from 13% to 74.7% for overall PCa, and from 13.7% to 50.9% for csPCa. This variability was observed in both the biopsy-naïve and the repeat biopsy setting. As NPV depends on prevalence, this had a major impact on reported NPV ( Fig. 3 ). Second, the definition of csPCa was highly variable from one series to another, and differences of up to 21% could be observed in NPV when different definitions of csPCa were used in the same dataset [12 13 38 47 48] .
To account for clinical heterogeneity and to further explore the clinical relevance of the results, we carefully selected studies for inclusion in the meta-analysis based on stringent criteria. Particularly, we included only studies that: (1) had biopsy protocols with at least 10 cores, since it is no longer recommended to obtain less than 10 cores per biopsy; (2) used DWI, which is the most informative technique, at least for cancers in the peripheral zone [60] ; and (3) reported mpMRI findings using a five-level score, so that negative findings could be better defined. We accepted studies using a subjective (Likert) scale because experienced readers obtained equivalent [45 61 62] or better [63] results with the Likert score than with the PI-RADS v1 score. Owing to the large variations of NPV induced by differences in definitions of csPCa, we did not include different definitions in the meta-analysis since this would have introduced unacceptable clinical heterogeneity in the results, possibly resulting in erroneous and biased estimates. We, therefore, a priori restricted the definition of csPCa to cancers with a Gleason score of ≥7, given the low lethal potential of Gleason 6 cancers [64] and the lack of consensus among pathologists on the best method to measure biopsy core invasion length [65 66] .
In this more homogeneous group of studies, the prevalence range was still large (31.3–63.7%). As a result, we modelled the evolution of NPV (and PPV) as a function of overall PCa prevalence. Unfortunately, we could not duplicate this for csPCa since only one study reporting NPV for Gleason ≥7 cancers met the inclusion criteria for meta-analysis.
We included only studies that reported the results of systematic/standard biopsy in patients with negative mpMRI and used the systematic/standard biopsy as a reference standard. It is well known that TRUS-guided biopsy harbours both random and systematic errors, as evidenced by the high rates of positivity of immediate repeat biopsy after a first series of negative biopsies [67 68] , and as confirmed recently by the PROMIS trial [69] . Therefore, using TRUS-guided biopsy as a reference standard may have overestimated the NPV of mpMRI. However, studies using radical prostatectomy specimens as a reference standard have already reported mpMRI detection rates in relation to PCa Gleason score and volume [1] . In this review, we intended to address the more pragmatic question as to whether a negative mpMRI could predict a negative subsequent biopsy. This is an important question because if the NPV of mpMRI was sufficiently high in comparison with the reference standard of systematic/standard biopsies, then in practice a negative mpMRI result could indeed avoid the need for prostate biopsy. Therefore, studies reporting only biopsy results when the mpMRI was positive (eg, obtained through MRI-targeted, guided, or fusion biopsies with added systematic biopsies) were not included in this review.
It is now well established that mpMRI is a sensitive tool for detecting aggressive PCa 1 2 3 69] . However several reasons preclude its broad use as a triage test before biopsy.
Firstly, the population referred to prostate biopsy is not standardised. The large range of reported prevalence for overall PCa and csPCa suggests substantial heterogeneity in the way patients are selected for biopsy. Owing to this heterogeneity, we did not provide a pooled estimate for mpMRI NPV. The role of mpMRI as a triage test before prostate biopsy should be evaluated in the broader context of the selection of patients with a suspicion of (aggressive) PCa. In a recent retrospective study of 514 patients, mpMRI NPV for Gleason ≥7 cancers was 91% when the PSA density was ≤0.2 ng/ml/ml, and only 71% when the PSA density was >0.2 ng/ml/ml ( p = 0.003) [70] . In another series of 288 biopsy-naïve patients, no csPCa (Gleason score ≥7 or maximum cancer core length ≥4 mm) was found in 44 patients with a PSA density of <0.15 ng/ml/ml and a PI-RADS v2 score of <3/5 [71] . We believe that such prestratification of the risk of csPCa is an interesting way for rationalising the use of mpMRI before biopsy. Patients found at very low risk would be spared both mpMRI and biopsy. Patients at a low risk—for whom mpMRI would have an NPV high enough to be used as a triage test—could avoid biopsy in case of negative mpMRI. Patients at a higher risk would need biopsy even in case of negative mpMRI. Many tools can be used to risk stratify the population of patients referred to biopsy, ranging from simple parameters such as PSA density to more complicated risk calculators [72 73] . The impact of these tools on the NPV of prebiopsy mpMRI needs to be carefully evaluated, both in the biopsy-naïve and in the repeat biopsy setting. For the moment, it is impossible to make any recommendations on the best way to risk stratify patients before referring them for mpMRI.
Secondly, the large variability in the definition of csPCa precludes any definitive conclusion on the ability of mpMRI to rule out aggressive cancer. The issue of the most appropriate definition of csPCa on biopsy is complex, since biopsy results may accurately reflect neither tumour burden nor aggressiveness. Nonetheless, there is an urgent need to standardise the histological definition(s) of csPCa, to allow meaningful comparisons between studies.
Thirdly, the specificity of mpMRI remains moderate, and there is a substantial proportion of false positives in the lesions scored 3/5 or 4/5 [1 74 75] , even with the new PI-RADS v2 score [76] . In a series of 62 patients with 116 lesions biopsied under magnetic resonance/ultrasound fusion, the overall cancer detection rates for PI-RADS v2 scores of 3/5 and 4/5 were only 15.8% and 29.8%, respectively [77] . In theory, a triage test used to rule out a disease needs to be highly sensitive for this disease. However, if its specificity is too low, it will be clinically useless since most patients will be positive, whether they have the disease or not. Therefore, if mpMRI is to be used as a triage test in the future, there is a need to improve its specificity. This could be achieved by a continuous refinement of scores [78] . Promising results in characterising csPCa have also been reported with a quantitative analysis [79] .
Finally, all published studies were conducted in specialised centres. The broad use of mpMRI as a triage test assumes good interobserver reproducibility. Unfortunately, interobserver reproducibility of existing scoring systems remains moderate [62 63 80] even with the use of the PI-RADS v2 score [80 81] . Studies evaluating on a large scale the reproducibility of mpMRI findings between expert and nonexpert centres are currently lacking.
Three systematic reviews (including two meta-analyses) regarding the role of mpMRI in localised PCa have been published recently 4 5 6 . Crucially, all three reviews focused exclusively on the sensitivity of mpMRI-targeted, guided, or fusion biopsies in diagnosing overall PCa and csPCa, using TRUS-guided prostate biopsies as reference standards. The impact of systematic biopsies on the outcome was not addressed in any of the reviews, within either the index test or the reference standard. Our review had a totally different research question and objective, focusing on NPV of mpMRI to see if a negative mpMRI can avoid the need for a prostate biopsy. As MRI-targeted/guided/fusion biopsies are not relevant if the mpMRI was negative for cancer, it can be argued that the three reviews assessed a different index test altogether. As such, we believe that the findings of this review are novel and unique, and pave the way for further focused clinical studies.
The current study represents the first systematic review addressing the role of mpMRI as a triage test before biopsy. The review elements were developed in conjunction with a multidisciplinary panel of experts (EAU Prostate Cancer Guidelines Panel), which included a patient representative, and the review was performed robustly in accordance with recognised standards. However, it is limited by the major heterogeneity of the existing literature in patient population, study design, and definitions of positive mpMRI and csPCa. It highlighted further areas of research that could help in defining the best use of mpMRI in the early detection of aggressive PCa in the future.
Although mpMRI can detect aggressive PCa with excellent sensitivity, a definitive conclusion on its role as a triage test before prostate biopsy will be possible only when three main issues are addressed. Firstly, because NPV depends on prevalence, and because overall PCa and csPCa prevalence was highly variable in the published series, it becomes mandatory to define the optimal way to pre-evaluate the risk of csPCa in patients with a suspicion of PCa. Depending on the risk category, mpMRI could then be used to obviate biopsies or not. Secondly, there is a need for consensus definitions of csPCa on biopsy findings to allow interstudy comparisons. Thirdly, although efforts have been made to standardise mpMRI technical protocols and interpretation in the past few years [11 60 76] , there is still a crucial need to improve mpMRI specificity and inter-reader reproducibility.
This systematic review was performed under the auspices of:
The European Association of Urology Guidelines Office Board
The European Association of Urology Prostate Cancer Guideline Panel
Author contributions: Olivier Rouvière had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.
Study concept and design: Rouvière, Mottet, Cornford.
Acquisition of data: Rouvière, Moldovan, Van den Broeck, Yuan.
Analysis and interpretation of data: Rouvière, Moldovan, Van den Broeck, Lam.
Drafting of the manuscript: Rouvière, Moldovan, Van den Broeck, Lam.
Critical revision of the manuscript for important intellectual content: Bellmunt, van den Bergh, Bolla, Briers, Van den Broeck, Cornford, Cumberbatch, De Santis, Fossati, Gross, Henry, Joniau, Lam, Matveev, Moldovan, van der Poel, van der Kwast, Rouvière, Schoots, Wiegel, Mottet.
Statistical analysis: None.
Obtaining funding: None.
Administrative, technical, or material support: Yuan, Sylvester, Marconi.
Supervision: None.
Other: None.
Financial disclosures: Olivier Rouvière certifies that all conflicts of interest, including specific financial interests and relationships and affiliations relevant to the subject matter or materials discussed in the manuscript (eg, employment/affiliation, grants or funding, consultancies, honoraria, stock ownership or options, expert testimony, royalties, or patents filed, received, or pending), are the following: Bellmunt is a company consultant for Janssen, Astellas, Pierre Fabre, Genentech, Merck, Ipsen, Pfizer, Novartis, and Sanofi Aventis. He has received research support from Takeda, Novartis, and Sanofi, and received travel grants from Pfizer and Pierre Fabre. Bolla has received company speaker honoraria from Ipsen and Astellas, honoraria or consultation fees from Janssen, and fellowship and travel grants from Janssen, AstraZeneca, and Astellas. Briers has received grant and research support from Ipsen, European Association of Urology, and Bayer; is an ex officio board member for Europa UOMO; is an ethics committee and advisory group member for REQUITE; is a member patient advisory board member for PAGMI; and is a member of SCA and EMA PCWP. Cornford is a company consultant for Astellas, Ipsen, and Ferring. He receives company speaker honoraria from Astellas, Janssen, Ipsen, and Pfizer; participates in trials from Ferring; and receives fellowships and travel grants from Astellas and Janssen. De Santis is a company consultant for GlaxoSmithKline, Janssen, Bayer, Novartis, Pierre Fabre, Astellas, Amgen, Eisai Inc., ESSA, Merck, and Synthon; has received company speaker honoraria from Pfizer, Takeda, Sanofi Aventis, Shionogi, Celgene, and Teva OncoGenex; has participated in trials for Pierre Fabre, Astellas, Exelixis, Bayer, and Roche; has received fellowship and travel grants from Bayer, Novartis, Ferring, Astellas, Sanofi Aventis, and Janssen; has received grant and research support from Pierre Fabre; has received honoraria from AstraZeneca; and is associated with Amgen. Joniau is a company consultant for Astellas, Ipsen, Bayer, Sanofi, and Janssen; has received company speaker honoraria from Astellas, Amgen, Bayer, Sanofi, Janssen, and Ipsen; has participated in trials for Astellas, Janssen, and Bayer; has received fellowship and travel grants from Astellas, Amgen, Bayer, Sanofi, Janssen, Ipsen, and Pfizer; and has received grant and research support from Astellas, Bayer, and Janssen. Matveev has received company speaker honoraria from Sanofi and Astellas, has participated in trials for Astellas, Pfizer and Novartis. Lam is a company consultant for and has received company speaker honoraria from Pfizer, GSK, Astellas, and Ipsen. van der Poel is a company consultant for Intuitive Surgical, has participated in trials for Astellas and Steba Biotech, and has received grant and research support from Astellas. Rouvière is a company consultant for EDAP-TMS, Bracco, and Philips; has received company speaker honoraria from EDAP-TMS, Bracco, and Philips; and has participated in trials for EDAP-TMS and Bracco. Wiegel has received company speaker honoraria from Astellas, Takeda, Hexal, Ipsen, Janssen-Cilac, and Ferring. Mottet has received grant and research support from Takeda Pharmaceutical, Millenium, Astellas, Pierre Fabre, Sanofi, and Pasteur, and has received honoraria or consultation fees from Takeda Pharaceutical, Millenium, Jansen, Astellas, BMS, Bayer, Ipsen, Ferring, Novartis, Nuclétron, Pierre Fabre, Sanofi, and Zeneca. van den Bergh, Van den Broeck, Cumberbatch, Fossati, Gross, Henry, van der Kwast, Sylvester, Yuan, Schoots, Moldovan, and Marconi have nothing to disclose.
Funding/Support and role of the sponsor: None.
A correlation with radical prostatectomy specimens has demonstrated that multiparametric magnetic resonance imaging (mpMRI) has excellent sensitivity in detecting prostate cancer (PCa) with a Gleason score of ≥7 1 2 3 . As a result, prostate mpMRI is increasingly used in patients with a suspicion of PCa to localise abnormal areas before biopsy. A large body of literature has shown that targeted biopsies of suspicious lesions seen on mpMRI (TBx) improved the detection of clinically significant PCa (csPCa), at least in the repeat biopsy setting 4 5 6 . As a result, it is now recommended that an mpMRI is performed before repeat biopsy to allow TBx of suspicious lesions in addition to standard biopsies [7] .
Some authors have recently suggested that, besides improving csPCa detection, mpMRI could also be used as a triage test so that patients with negative mpMRI findings could obviate biopsy. Such a strategy remains highly controversial [8] and depends upon the negative predictive value (NPV) of mpMRI. Therefore, the European Association of Urology Prostate Cancer Guidelines Panel undertook this systematic review and meta-analysis to assess the NPV of mpMRI in patients with a suspicion of PCa and, thus, its potential role in eliminating unnecessary prostate biopsy.
Our primary aim was to systematically evaluate the performance of negative prebiopsy prostate mpMRI in predicting a negative biopsy result for overall PCa and csPCa in biopsy-naïve men and in men with previously negative biopsies. A further objective was to explore and define factors that may contribute to relevant thresholds in order to provide guidance for future studies.
The review was performed according to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) statement [9] . The review protocol was published in PROSPERO database ( http://www.crd.york.ac.uk/PROSPERO; registration number CRD42015021929). Databases searched included the Embase and OVID Medline databases, the Cochrane database of systematic reviews, and the Cochrane Central Register for Clinical Trials, covering from January 1, 2000 to February 13, 2016. Systematic or standard prostate biopsies were used as reference standards, with positive or negative cases of PCa being determined by histopathological examination. The detailed search strategy is presented in Supplement 1.
Included studies focused on men who were assessed for suspected PCa by mpMRI before undergoing prostate biopsy. Studies enrolling both biopsy-naïve men and men who had undergone previous negative biopsies were included. Prebiopsy prostate mpMRI was considered the index test and comprised T2-weighted imaging (T2WI) and at least one functional imaging technique (diffusion-weighted imaging [DWI], dynamic contrast-enhanced imaging [DCEI], or magnetic resonance spectroscopic imaging [MRSI]). For inclusion, studies had to report on false negatives and true negatives, in order to calculate NPV (ie, results of systematic/standard prostate biopsies when the mpMRI was negative). When available, false positive and true positive findings were also noted to calculate the positive predictive value (PPV) and the cancer prevalence. There was restriction neither on the biopsy technique (transrectal or transperineal) nor on the number of biopsy cores. Studies using radical prostatectomy specimens as reference standards were excluded, as were studies evaluating men with histologically proven PCa. Studies with less than 50 participants were excluded. No language restrictions were applied.
Two reviewers (P.C.M. and T.V.D.B.) independently screened all abstracts and full-text articles for eligibility. Disagreement was resolved by consensus or reference to an independent third party (L.M.). All screening was performed using a predefined eligibility form.
Using a data extraction form developed a priori, the same two reviewers independently extracted data concerning study methodology, patient characteristics, technical characteristics of the MR scanners, mpMRI protocol, mpMRI scoring system, definition of positive mpMRI, biopsy protocol, and definition of csPCa. Any discrepancies concerning data extraction were resolved by consensus or reference to an independent arbiter (O.R. or T.B.L.).
To assess the risk of bias (RoB), all included reports were reviewed using the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool for diagnostic accuracy studies [10] .
Outcome data regarding false negative and true negative values of mpMRI before prostate biopsy were recorded as reported by authors. When not available, data were indirectly derived from specificity, sensitivity, and prevalence values reported by authors using an online Bayesian statistics calculator ( http://www.medcalc.com/bayes.html ). Descriptive statistics were used to summarise baseline characteristics and outcomes, including median and interquartile range (IQR) for estimates of NPV across studies. A correlation between mpMRI NPV and a positive biopsy rate was established using the Pearson's correlation coefficient.
A meta-analysis was undertaken to calculate pooled NPV and PPV. To ensure appropriate clinical homogeneity of the studies included in the meta-analysis, we selected only the studies enrolling biopsy-naïve patients and/or patients with a history of negative biopsy, and fulfilling the following criteria that were defined a priori: (1) reference standard consisting of prostate biopsy with at least 10 samples on all patients; (2) mpMRI protocol comprising at least T2WI and DWI; (3) mpMRI results presented as a five-level score, using a subjective Likert scale or the Prostate Imaging Reporting Data System (PI-RADS) score [11] ; (4) definition of positive mpMRI as a score ≥3/5 or ≥4/5; and (5) results reported on a per patient basis. In addition, only studies defining csPCa as Gleason ≥7 cancers were selected for the meta-analysis assessing the mpMRI NPV for csPCa. A bivariate random-effects approach was employed using the Midas package in Stata 12 (StataCorp LP, College Station, TX, USA). Since the NPV decreases and the PPV increases as the prevalence increases, post-test probability estimates of NPV and PPV were reported for the given values of the prevalence based on Bayes’ theorem.
For other studies not included in the meta-analysis based on the criteria described above, a narrative synthesis of the data was performed. To explore and define clinical heterogeneity, subgroups were analysed at patient level based on the following variables: biopsy-naïve versus previous negative biopsy; patients with positive versus negative digital rectal examination (DRE); mpMRI performed with an endorectal versus without an endorectal coil; transrectal ultrasound (TRUS) versus template transperineal (TTP) biopsy approach; and ≤16 cores versus >16 cores as the reference standard. Studies reporting mpMRI NPV for patients with a prostate-specific antigen (PSA) level of ≤10 ng/ml were also reported separately.
The study selection process is depicted in the PRISMA flow diagram ( Fig. 1 ). A total of 2980 abstracts were retrieved. After abstract screening and removal of duplicates, 240 articles were eligible for full text screening, of which 48 studies were eligible for inclusion 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 .
Out of the 48 included studies, 42 were single-centre and six were multicentre studies. Thirty-four studies were prospective and six were retrospective, whilst the design of the rest was unclear. RoB assessment using QUADAS-2 was performed for each of the individual studies ( Fig. 2 A and B). Overall, the RoB was highly heterogeneous across studies for all criteria, except for the reference standard domain, in which RoB was low in most studies.
The 48 studies comprised a total of 9613 men who underwent prostate mpMRI followed by biopsy. The study and patient baseline characteristics are presented in Table 1 . The patient population consisted of biopsy-naive men in nine studies, men with at least one previous negative biopsy in 16 studies, and both biopsy-naïve men and men with a history of previous negative biopsy in nine studies. In 14 studies, the biopsy history of the patients was unclear.
Study | Study design | Period | Population | Pt Nb | Mean/median* age (yr) | Mean/median* PSA (ng/ml) | Mean/median* prostate volume (cm 3 ) | Magnetic field strength | MR pulse sequences | Endorectal coil | MR score | Definition of positive MRI | Reference standard |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Hauth (2015) [25] | Prospective | 2011–2013 | FB | 94 | 64 (43–83) | 9 (3–31) | 51 (17–140) | 1.5 T | T2WI/DWI/DCEI/MRSI | No | PI-RADS v1 | ≥3 | 11–13-core TRUS SBx + TBx |
Lamb (2015) [36] | Retrospective | 2013–2013 | FB & PNB | 173 | NR | NR | NR | 1.5 T | T2WI/DWI | NR | NR | NR | 12-core TRUS SBx |
Brock (2015) [15] | Prospective | 2013–2014 | PNB | 168 | 64* (IQR 59–70) | 9.2* (IQR 6.7–13.4) | 55.4* (IQR 42–80) | 3 T | T2WI/DWI/DCEI | No | PI-RADS v1 | NR | 12/24-core TRUS SBx + TBx |
Grenabo Bergdahl (2016) [22] | Prospective | 2013–2014 | FB & PNB | 83 | 69.3* (IQR 69–69.6) | 1.6* (IQR 0.9–2.7) | NR | 3 T | T2WI/DWI/DCEI/MRSI | No | PI-RADS v1 | ≥3 | 10-core TRUS SBx + TBx |
Wang (2015) [58] | Prospective | 2002–2009 | FB & PNB | 586 | 70 (26–91) | 11.11* (0.02–9794) | NR | 1.5 T | T2WI/DWI/DCEI/MRSI | Yes | PI-RADS v1 | ≥3 | TRUS SBx |
Pepe (2015) [41] | Prospective | 2011–2014 | PNB | 100 | 64* | 8.6* (4.2–10) | NR | 3 T | T2WI/DWI/DCEI/MRSI | No | PI-RADS v1 | ≥4 | TPBx + TBx |
Panebianco (2015) [39] | Prospective | 2011–2014 | FB (61.62%) & PNB (38.34%) | 925 (1140 total cohort) |
NR | NR | NR | 3 T | T2WI/DWI/DCEI | Yes | PI-RADS v1 | NR | 14-core TRUS SBx; 45-core sat TPBx + TBx |
Radtke (2015) [46] | Prospective | 2013–2013 | FB (63.3%) & PNB (36.7%) | 294 | 64* (60–71) | 7.3 (6.0) | 47 (37.5) | 3 T | T2WI/DWI/DCEI | No | PI-RADS v1 | PI-RADS ≥2; PI-RADS ≥3; PI-RADS ≥4; PI-RADS = 5; |
24-core TPBx + TBx |
Itatani (2014) [27] | Retrospective | 2004–2007 | NR | 193 | 68.9 (8.4); 70* (47–89) | 11.8 (15.9); 7.9* (1.22–159) | NR | 1.5 T | T2WI/DWI/DCEI | No | 1–5 scale (Likert) | ≥3 | 12–14-core TRUS SBx |
Porpiglia (2014) [44] | Prospective | 2011–2013 | PNB | 170 | 65* (60–70) | 6.9* (5.2–9.8) | 42* (36–48) | 1.5 T | T2WI/DWI/DCEI | Yes | Dichotomous | Positive: at least 2/3 MR seq. with suspicious findings | 18–24-core TRUS SBx (volume dependent) |
Thompson (2014) [56] | Prospective | 2012–2013 | FB (88%) & PNB (12%) | 150 | 62.4* (IQR 55.0–66.4) | 5.6* (IQR 4.5–7.5) | 40* (IQR 30–57) | 1.5 T (47%) & 3 T (53%) | T2WI/DWI/DCEI | No | PI-RADS v1 | ≥3 | Median of 30 TPBx (volume dependent) |
Pokorny (2014) [43] | Prospective | 2012–2013 | FB | 223 | 63* (IQR 57–68) | 5.3* (IQR 4.1–6.6) | 41* (IQR 30–59) | 3 T | T2WI/DWI/DCEI | No | PI-RADS v1 | ≥3 (primary); ≥4 |
12-core TRUS SBx + TBx |
Petrillo (2014) [42] | Prospective | 2009–2010 | NR | 136 | NR | NR | NR | 1.5 T | T2WI/DWI/MRSI | Yes | 1–5 scale (Likert) | ≥3 | 12–16-core TRUS SBx (volume + PSA dependent) |
Javali (2014) [29] | Retrospective | 2002–2011 | NR | 140 | Control: 62.4 (10.5); Study: 62.9 (12.1) | Control: 6.8 (2.3); Study: 6.87 (2.6) | Control: 44 (14.2); Study: 43 (18.4) | 1.5 T | T2WI/MRSI | Yes | Dichotomous | Cit/[Cho + Cr] < 1.2 | 6-core TRUS SBx ( n = 69), 12-core TRUS SBx ( n = 119) |
Abd-Alazeez (2014) [13] | Prospective | 2007–2011 | FB | 129 | 62* (41–82) | 5.8* (1.2–20) | 40* (16–137) | 1.5 & 3 T | T2WI/DWI/DCEI | No | PI-RADS v1 | ≥3 (primary); ≥4 |
20-core TPBx |
Abd-Alazeez (2014) [12] | Retrospective | NR | PNB | 54 | 64* (39–75) | 10* (2–23) | 53* (19–136) | 1.5 & 3 T | T2WI/DWI/DCEI | No | PI-RADS v1 | ≥3 (primary); ≥4 |
≥20-core TPBx + TBx ( n = 15) |
Matsuoka (2014) [37] | Prospective | 2007–2012 | NR | 135 | 67* (50–80) | 7.0* (2.9–19.8) | 25.4* (12.7–90.2) | 1.5 T | T2WI/DWI | No | 1–5 scale (Likert) | ≥3 | 14-core TRUS SBX |
Junker (2013) [30] | Retrospective | 2011–2013 | PNB | 73 | 62 (7.4) | 7.0* (5.1–12.9) | 45* (34–61) | 3 T | T2WI/DWI/DCEI | No | PI-RADS | PI-RADS ≥10 and ≥11 for all PCa PI-RADS ≥13 for significant PCa |
10-core TRUS SBx + TBx |
Busetto (2013) [16] | Prospective | 2010–2012 | PNB | 163 | 66.4 (5.3) | 6.8 (1.6) | NR | 3 T | T2WI/DWI/DCEI/MRSI | Yes | NR | NR | 10-core TRUS SBx + TBx |
Rais-Bahrami (2013) [47] | Prospective | 2007–2012 | NR | 583 | 61.3 (8.4) | 9.9 (13.1) | NR | 3 T | T2WI/DWI/DCEI/MRSI | Yes | 1–4 scale (Likert) | ≥2 ≥3 |
12-core TRUS SBx + TBx |
Kuru (2013) [34] | Prospective | 2010–2011 | FB (51%) & PNB (49%) | 347 | 65.3 (42–82) | 9.85 (0.5–104) | 48.7 (9–180) | 3 T | T2WI/DWI/DCEI | No | 1–3 scale (Likert) | ≥2 | 12–36-core TRUS SBx (volume dependent) + TBx |
Ferda (2013) [20] | Prospective | NR | NR | 164 | (49–74) | (4.2–123) | NR | 3 T | T2WI/DWI/DCEI/MRSI | No | NR | In house | TRUS SBx |
Ganie (2013) [21] | NR | 2007–2009 | PNB | 87 | NR | NR | NR | 1.5 T | T2WI/MRSI | Yes | MRSI Cho/Cit ratio | In house | 6 core TRUS SBx + MRI TBx |
Vinet (2013) [57] | Prospective | 2009–2011 | FB | 69 | NR | 5.2* (3.2–28) | NR | 1.5 T (35 pts) & 3 T (34 pts) | T2WI/DWI/DCEI | No | 1–5 scale (Likert) | ≥3 | 12-core TRUS SBx + TBx |
Numao (2013) [38] | Prospective | 2006–2010 | FB | 351 | 65* (59–70) | 6.3* (4.9–9.1) | 32* (24–42) | 1.5 T | T2WI/DWI/DCEI (no DCEI in 42 pts) | No | 1–5 scale (Likert) | ≥3 | 3D 26-core (12 TRUS SBx + 14 TPBx – 203 pts); 3D 14-core (6 TRUS SBx + 8 TPBx – 102 pts); TPBx 14 core (46 pts) |
Belas (2012) [14] | Prospective | 2010–2011 | FB | 71 | 66* (47–76) | 7* (4–10) | 45* (15–150) | 1.5 T | T2WI/DWI/DCEI | No | TZ: 0–4 scale PZ: 0–10 scale |
TZ: >2 PZ: >6 |
12-core TRUS SBx + TBx |
Ibrahiem (2012) [26] | Prospective | 2008–2009 | FB | 100 | 65.03 (7.13) | 26.3 (24.2) | 60.09 (28.7) | 1.5 T | T2WI/DWI | No | NR | In house | 12-core TRUS SBX |
Sciarra (2012) [51] | Prospective | 2008–2011 | PNB | 84 | 64.09 (46–76) | 7.07 (4.2–15.5) | NR | 3 T | T2WI/DWI/DCEI/MRSI | Yes | NR | NR | 10-core TRUS Bx + TBx |
Portalez (2012) [45] | Prospective | 2011 | PNB | 129 | 64.7 (47–79) | 9.6 (2.7–40) | 51.1 (12–192) | 1.5 T | T2WI/DWI/DCEI | Mixed | 1–5 scale (Likert) PI-RADS |
Likert ≥3 PI-RADS ≥9 |
10–12-core TRUS SBx + TBx |
Watanabe (2012) [59] | Prospective | 2004–2008 | NR | 1448 | 72 (7.5) | NR | NR | 1.5 T | T2WI/DWI | No | NR | ADC value ≤1.35 × 10 −3 mm 2 /s | 8-core TRUS SBx + TBx |
Tamada (2011) [54] | Retrospective | 2006–2009 | NR | 50 | 70 (40–84) | 6.84* (4.06–9.94) | NR | 1.5 T | T2WI/DWI/DCEI | No | NR | In house | 12-core TRUS SBx |
Choi (2011) [18] | NR | 2009–2010 | NR | 51 | 67.16 (56–90) | 14.16 (1.02–38.9) | 42.98 (13.8–77.3) | 3 T | T2WI/DWI | NR | NR | NR | 10–12-core TRUS SBx + TBx |
Iwazawa (2011) [28] | Retrospective | 2008–2009 | NR | 178 | 68.8 (41–86) | 20.51 (4.04–568.5) | NR | 1.5 T | T2WI/DWI/DCEI | NR | 1–4 scale (Likert) | NR | 10–12-core TRUS SBx (TBx included in SBx chart) |
Rouse (2011) [48] | Prospective | 2005–2007 | PNB | 114 | 63.6 (41–83) | 13.4 (0–228) | NR | 1.5 T | T2WI/DWI/DCEI | NR | 1–5 scale (Likert) | ≥3 | TRUS SBx |
Haffner (2011) [23] | Prospective | 2005–2009 | FB | 555 | 64* (47–83) | 6.75* (0.18–100) | 46* (15–200) | 1.5 T | T2WI/DCEI | No | 1–5 scale (Likert) | ≥3 | 10-core TRUS SBx + TBx |
Panebianco (2010) [40] | Prospective | 2007–2009 | PNB | 150 | 61.2 (46–78) | 9.42 (3.91) | 41.17 (7.47) | 1.5 T | T2WI/DCEI/MRSI | Yes | NR | In house | 10-core TRUS SBx (TBx included in SBx chart) |
Roy (2010) [49] | Not specified | 2011–2009 | FB (53%) & PNB (47%) | 103 | 63 (52–78) | 7* | NR | 3 T | T2WI/DWI/DCEI | Yes | NR | NR | 8-core TRUS SBx + TBx |
Testa (2010) [55] | Not specified | 2007 | PNB | 54 | 63.9 (52–76) | 11.4 (3–42) | 59.3 (30–150) | 1.5 T | T2WI/MRSI | Yes | 1–3 scale (Likert) | ≥2 | 12-core TRUS SBx + TBx |
Sciarra (2010) [52] | Prospective | 2007–2009 | PNB | 110 | 63.5 (49–74) | NR | NR | 1.5 T | T2WI/DCEI/MRSI | Yes | NR | In house | 10-core TRUS SBx + TBx |
Kitajima (2010) [31] | Prospective | 2008–2009 | NR | 53 | 69* (56–84) | 11.1* (4.2–112.1) | NR | 3 T | T2WI/DWI/DCEI | No | 1–5 scale (Likert) | ≥3 | 20-core TPBx |
Labanaris (2010) [35] | Prospective | 2004–2008 | PNB | 260 | NR | NR | NR | 1 T | T2WI/DWI/DCEI | Yes | Dichotomous | In house | 18-core TRUS SBx |
Kumar (2009) [32] | NR | NR | NR | 61 | 65.3 (9.3) | 16.5 (0.21–155) | NR | 1.5 T | T2WI/MRSI | Yes | NR | (Cit/(Cho + Cr) ≤ 1.2 | TRUS Bx |
Schmuecking (2009) [50] | NR | NR | FB & PNB | 67 | 68 | 11.5 | NR | 1.5 T | T2WI/DCEI | No | NR | NR | 20-core Bx |
Cheikh (2009) [17] | Retrospective | 2005–2008 | PNB | 93 | 63.2 (52–74) | 9.63 (1.6–40) | NR | 1.5 T | T2WI/DCEI | No | Dichotomous | In house | 12-core TRUS SBx + TBx |
Cirillo (2008) [19] | Prospective | 2004–2006 | PNB | 54 | 65.5 (5.2) | 10.8 (7.5) | NR | 1.5 T | T2WI/MRSI | Yes | Dichotomous | In house | 10-core TRUS SBx + TBx |
Kumar (2007) [33] | Prospective | 2003–2005 | NR | 83 | NR | NR | NR | 1.5 T | T2WI/MRSI | Yes | NR | NR | 12-core TRUS SBx + TBx |
Squillaci (2005) [53] | Prospective | 2004–2005 | NR | 65 | NR | NR | NR | 1.5 T | T2WI/DCEI/MRSI | No | 1–3 scale (Likert) | ≥2 | 10-core TRUS SBx + TBx |
Hara (2005) [24] | Prospective | 2003–2004 | FB | 90 | 67.2 (NR) | NR | NR | 1.5 T | T2WI/DCEI | No | 1–3 scale (Likert) | ≥2 = 3 |
14-core TRUS SBx |
The magnetic field strength was 1, 1.5, and 3 T in one, 28, and 15 studies, respectively. Four studies used both 1.5 and 3 T MR systems. DWI and DCEI were used in 36 and 35 studies, respectively. Nineteen studies also added MRSI. An endorectal coil was used in 18 studies. The definition of positive mpMRI varied across studies. The PI-RADS v1 score was used in 12 studies, a five-level subjective (Likert) score was used in eight studies, and one study reported data based on the two scoring systems. In-house criteria were used in 13 studies for defining positive mpMRI, and five studies used a dichotomous definition. Nine studies did not report on the criteria for positive mpMRI. No study used the PI-RADS v2 score.
Regarding the reference standard, TRUS-guided biopsies were used in 39 studies, TTP biopsies in six studies, and mixed TRUS-guided and TTP biopsies in two studies. In one study, the biopsy approach was unclear. The number of cores per biopsy procedure was ≤16 in 30 studies, >16 in nine studies, and variable among patients in three studies. For six studies, the number of biopsy cores taken was unclear.
At patient level, the median biopsy positivity rate (ie, cancer prevalence) was 50.4% (IQR, 36.4–57.7%) for overall cancer and 32.9% (IQR, 28.1–37.2%) for csPCa ( Table 2 ). The median mpMRI NPV was 82.4% (IQR, 69.0–92.4%) for overall cancer and 88.1% (IQR, 85.7–92.3) for csPCa. NPV significantly decreased when cancer prevalence increased, both for overall cancer ( r = –0.64, p < 0.0001) and csPCa ( r = –0.75, p = 0.032; Fig. 3 ). In addition, NPV was highly dependent on the definition used for csPCa, with differences of up to 21% when several definitions were used in the same dataset [12 13 38 47 48] .
Study | Overall PCa prevalence (%) | Reporting level | Multiparametric MRI performance for PCa detection | Definition of csPCa | csPCa prevalence | Multiparametric MRI performance for csPCa detection | ||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
TN | FN | TP | FP | NPV | PPV | TN | FN | TP | FP | NPV | PPV | |||||
Hauth (2015) [25] | 45.7 | Patient | 6 | 1 | 42 | 45 | 85.7% | 48.3% | Low grade: GS ≤ 6 High grade: GS ≥ 7 |
NR | NR | NR | NR | NR | NR | NR |
Lesion | 59 | 13 | 55 | 73 | 81.9% | 43% | ||||||||||
Lamb (2015) [36] | 65.9 | Patient | 23 | 22 | 92 | 36 | 51.1% | 71.9% | GS ≥ 7 | 50.9% | 31 | 14 | 71 | 57 | 68.9% | 55.5% |
Brock (2015) [15] | 42.3 | Patient | 17 | 7 | 56 | 88 | 70.8% | SBx: 38.8% TBx: 22.2% Duo: 44.4% |
Epstein: GS > 6 and/or max CCL ≥50% | 24.4% | SBx: 21 | SBx: 3 | SBx: 38 TBx: 27 duo: 47 |
SBx: 106 TBx: 117 duo: 97 |
87.5% | SBx: 26.4% TBx: 18.8% duo: 32.6% |
Grenabo Bergdahl (2016) [22] | 33.7 | Patient | 36 | 7 | 19 | 21 | 83.7% | 47.5% | Clinically insignificant PCa: T1c, PSAd < 0.15, GS < 7, ≤2 positive cores, and unilateral cancer | NR | NR | NR | NR | NR | NR | NR |
Wang (2015) [58] | 58 | Patient | 165 | 8 | 332 | 81 | 95.4% | 80.4% | NR | NR | NR | NR | NR | NR | NR | NR |
Pepe (2015) [41] | 37 | Patient | 23 | 8 | 29 | 40 | 74.2% | 42% | GS ≥ 7 or GS 6 with CCL ≥ 50% | NR | NR | NR | NR | NR | 100% | 55.8% |
Panebianco (2015) [39] | 74.7 | Patient | Group A (satBx): 104 | Group A (satBx): 43 | Group A: 186 | Group A: 22 | Group A (satBx): 70.7% | Group A: 89.4% | NR | 60% | Group A: 147 | Group A: 0 | Group A: 183 | Group A: 25 | Group A: 100% | Group A: 88% |
Group B (TRUSGB NR TRUS G satBx): 93 | Group B (TRUSGB NR TRUS G satBx): 37 | Group B: 417 before and 425 after satBx | Group B: 23/440 and 15/440 after satBx. | Group B (TRUSGB–TRUS G satBx): 71.5% | Group B: 94.8% before and 96.6% after satBx | 71.9% | Group B: 130 | Group B: 0 | Group B: 410 |
Group B: 30 | Group B: 100% | Group B: 93.2% | ||||
Radtke (2015) [46] | 51 | Patient | ≥2/5: 80 ≥3: 103 ≥4: 138 = 5: 142 |
≥2/5: 18 ≥3/5: 38 ≥4/5: 78 = 5/5: 126 |
≥2/5: 132 ≥3/5: 112 ≥4/5: 72 = 5/5: 24 |
≥2/5: 64 ≥3/5: 41 ≥4/5: 6 = 5/5: 2 |
≥2/5: 81.6% ≥ 3/5: 73.1% ≥ 4/5: 63.9% = 5/5: 53% |
≥2/5: 67.4% ≥ 3/5: 73.2% ≥ 4/5: 92.3% = 5/5: 92.3% |
GS ≥ 7 | 29.3% | ≥2/5: 91 ≥3/5: 124 ≥4/5: 183 = 5/5: 203 |
≥2/5: 7 ≥3/5: 17 ≥4/5: 33 = 5/5: 65 |
≥2/5: 79 ≥3/5: 69 ≥4/5: 53 = 5/5: 21 |
≥2/5: 117 ≥3/5: 84 ≥4/5: 25 = 5/5: 5 |
≥2/5: 92.2% ≥3/5: 87.9% ≥4/5: 84.7% = 5/5: 75.8% |
≥2/5: 40.3% ≥3/5: 45.1% ≥4/5: 68% = 5/5: 80.7% |
Itatani (2014) [27] | 13 | Patient | 168 | 25 | NR | NR | 87% | NR | (1) PSAd ≥ 0.1 or GP 4/5 or ≥ 3/6 pos cores; max CCL < 50% (2) PSAd ≥ 0.15 or GP 4/5 or max core length invasion < 3 mm (min 6 cores) |
NR | NR | NR | NR | NR | NR | NR |
Porpiglia (2014) [44] | 30.6 | Patient | 107 | 5 | 47 | 11 | 95.5% | 81% | NR | NR | NR | NR | NR | NR | NR | NR |
Thompson (2014) [56] | 61.3 | Patient | 35 | 16 | 76 | 23 | 68.6% | 76.7% | Moderate or high risk Moderate risk: GS 7 (GP4 >5%) and <50% of positive cores or GS 6–7 (GP4 ≤ 5%) and either ≥30% of positive cores or max core length invasion ≥8 mm High risk: GS ≥ 7 (GP4 > 5%); ≥50% + cores or GS ≥ 8 |
34% | 49 | 2 | 49 | 50 | 96% | 49.5% |
Pokorny (2014) [43] | 63.7 | Patient | ≥3/5: 56 ≥4/5: 74 |
≥3/5: 25 ≥4/5: 40 |
≥3/5: 101 ≥4/5: 86 |
≥3/5: 41 ≥4/5: 23 |
≥3/5: 69.1% ≥4/5: 64.9% |
≥3/5: 71.1% ≥4/5: 78.9% |
NR | NR | NR | NR | NR | NR | NR | NR |
Petrillo (2014) [42] | 18.4 | Patient | 56 | 4 | 21 | 55 | 93% | 28% | NR | NR | NR | NR | NR | NR | NR | NR |
Javali (2014) [29] | 16.4 | Patient | 49 | 1 | 22 | 68 | 98% | 24.4% | NR | NR | NR | NR | NR | NR | NR | NR |
Abd-Alazeez (2014) [13] | 54.7 | Lobe | ≥3/5: 33 | ≥3/5: 14 | ≥3/5: 127 | ≥3/5: 84 | ≥3/5: 70% | ≥3/5: 60% | Def 1: GS ≥ 4 + 3 and/or max CCL ≥ 6 mm Def 2: GS ≥ 3 + 4 and/or max CCL ≥ 4 mm Def 3: GS ≥ 4 + 3 Def 4: GS ≥ 3 + 4 Def 5: max CCL ≥ 6 mm Def 6: max CCL ≥ 4 mm |
Def 1: NR Def 2: 44.2% Def 3: 23.2% Def 4: 36% Def 5: 32.9% Def 6: 39.5% |
Def 1: 46 Def 2: 42 Def 3: 47 Def 4: 43 Def 5: 46 Def 6: 43 |
Def 1: 1 Def 2: 5 Def 3: 0 Def 4: 4 Def 5: 1 Def 6: 4 |
Def 1: 45 Def 2: 72 Def 3: 13 Def 4: 50 Def 5: 39 Def 6: 59 |
Def 1: 166 Def2: 139 Def 3: 198 Def 4: 161 Def 5: 172 Def 6: 152 |
Def 1: 98 Def 2: 89 Def 3: 100 Def 4: 92 Def 5: 98 Def 6: 91 |
Def 1: 21 Def 2: 34 Deg 3: 6 Def 4: 24 Def 5: 19 Def 6: 28 |
≥4/5: 87 | ≥3/5: 62 | ≥3/5: 79 | ≥3/5: 30 | ≥3/5: 58% | ≥3/5: 73% | Def 1: 140 Def 2: 124 Def 3: 148 Def 4: 133 Def 5: 141 Def 6: 131 |
Def 1: 9 Def 2: 25 Def 3: 1 Def 4: 16 Def 5: 8 Def 6: 18 |
Def 1: 37 Def 2: 52 Def 3: 12 Def 4: 38 Def 5: 32 Def 6: 45 |
Def 1: 72 Def 2: 57 Def 3: 97 Def 4: 71 Def 5: 77 Def 6: 64 |
Def 1: 94 Def 2: 83 Def 3: 99 Def 4: 89 Def 5: 95 Def 6: 88 |
Def 1: 34 Def 2: 48 Def 3: 11 Def 4: 35 Def 5: 30 Def 6: 42 |
|||||
Abd-Alazeez (2014) [12] | 47.2 | Lobe | ≥3/5: 26 | ≥3/5: 13 | ≥3/5: 38 | ≥3/5: 31 | ≥3/5: 66% | ≥3/5: 55% | Def 1: GS ≥ 4 + 3 and/or max CCL ≥ 6 mm Def 2: GS ≥ 3 + 4 and/or max CCL ≥ 4 mm Def 3: GS ≥ 4 + 3 Def 4: GS ≥ 3 + 4 Def 5: max CCL ≥ 6 mm Def 6: max CCL ≥ 4 mm |
Def 1: 18.5% Def 2: 31.5% Def 3: 4.6% Def 4: 21.3% Def 5: 16.7% Def 6: 25% |
Def 1: 37 Def 2: 31 Def 3: 39 Def 4: 36 Def 5: 37 Def 6: 32 |
Def 1: 2 Def 2: 8 Def 3: 0 Def 4: 3 Def 5: 2 Def 6: 7 |
Def 1: 18 Def 2: 26 Def 3: 5 Def 4: 20 Def 5: 16 Def 6: 20 |
Def 1: 51 Def 2: 43 Def 3: 64 Def 4: 49 Def 5: 53 Def 6: 49 |
Def 1: 95 Def 2: 79 Def 3: 100 Def 4: 92 Def 5: 95 Def 6: 82 |
Def 1: 26 Def 2: 38 Def 3: 7 Def 4: 29 Def 5: 23 Def 6: 29 |
≥4/5: 49 | ≥4/5: 25 | ≥4/5: 26 | ≥4/5: 8 | ≥4/5: 66% | ≥4/5: 76% | Def 1: 70 Def 2: 63 Def 3: 73 Def 4: 68 Def 5: 70 Def 6: 64 |
Def 1: 4 Def 2: 11 Def 3: 1 Def 4: 6 Def 5: 4 Def 6: 10 |
Def 1: 16 Def 2: 23 Def 3: 4 Def 4: 17 Def 5: 14 Def 6: 17 |
Def 1: 18; Def 2: 11 Def 3: 30 Def 4: 17 Def 5: 20 Def 6: 17 |
Def 1: 94 Def 2: 85 Def 3: 99 Def 4: 92 Def 5: 94 Def 6: 86 |
Def 1: 47 Def 2: 67 Def 3: 12 Def 4: 50 Def 5: 41 Def 6: 49 |
|||||
Matsuoka (2014) [37] | 64.8 | Lobe | 46 | 49 | 149 | 26 | 48.4% | 85.1% | NR | NR | NR | NR | NR | NR | NR | NR |
Junker (2013) [30] | 53.4 | Patient | ≥10/15: 21 ≥11/15: 28 |
≥10/15: 4 ≥11/15: 12 |
≥10/15: 35 ≥11/15: 27 |
≥10/15: 13 ≥11/15: 6 |
≥10/15: 84% ≥11/15: 70% |
≥10/15: 72.9% ≥11/15: 81.8% |
GS ≥ 4 + 3 | 13.7% | ≥13: 54 | ≥13: 2 | ≥13: 8 | ≥13: 9 | ≥13: 96.4% | ≥13: 47% |
Busetto (2013) [16] | 41.7 | Patient | 59 | 7 | 61 | 36 | 89% | 63% | NR | NR | NR | NR | NR | NR | NR | NR |
Rais-Bahrami (2013) [47] | 54.2 | Patient | ≥2/4 : 80 | ≥2/4: 275 | ≥2/4: 187 | ≥2/4: 275 | ≥2/4: 66% | ≥2/4: 59% | GS ≥ 7: GS ≥ 8 |
31.7% | NR | NR | NR | NR | GS ≥ 7: 91% GS ≥ 8: 91% |
GS ≥ 7: 38% GS ≥ 8: 18% |
≥3/4: 251 | ≥3/4: 76 | ≥3/4: 16 | ≥3/4: 76 | ≥3/4: 51% | ≥3/4: 82% | NR | NR | NR | NR | GS ≥ 7: 75% GS ≥ 8: 91% |
GS ≥ 7: 67% GS ≥ 8: 41% |
|||||
Kuru (2013) [34] | 57.6 | Patient | 80 | 14 | 67 | 186 | 85.1% | 73.5% | NR | NR | NR | NR | NR | NR | NR | NR |
Ferda (2013) [20] | 51.2 | Patient | 52 | 2 | 82 | 28 | 96.3% | 74.5% | NR | NR | NR | NR | NR | NR | NR | NR |
Ganie (2013) [21] | 74.7 | Patient | 13 | 3 | 62 | 9 | 59.1% | 95.4% | NR | NR | NR | NR | NR | NR | NR | NR |
Vinet (2013) [57] | 49.3 | Patient | ≥3/5: 11 | ≥3/5: 6 | ≥3/5: 28 | ≥3/5: 24 | ≥3/5: 64.7% | ≥3/5: 53.8% | NR | NR | NR | NR | NR | NR | NR | NR |
≥4/5: 22 | ≥4/5: 11 | ≥4/5: 23 | ≥4/5: 13 | ≥4/5: 66.7% | ≥4/5: 63.8% | NR | NR | NR | NR | NR | NR | NR | NR | |||
Numao (2013) [38] | 45 | Patient | 137 | 57 | 101 | 56 | 70.6% | 64.3% | Def 1: GS ≥4 + 3 and/or ≥20% positive cores and/or max CCL ≥5 mm Def 2: GS ≥ 3 + 4 and/or ≥20% + cores and/or max CCL ≥5 mm Def 3: GS ≥ 3 + 4 and/or ≥20% + cores |
Def 1: 33.3% Def 2:37.8% Def 3: 35.8% |
Def 1: 74 Def 2: 65 Def 3: 69 |
Def 1: 83 Def 2: 92 Def 3: 88 |
Def 1: 160 Def 2: 153 Def 3: 156 |
Def 1: 34 Def 2: 41 Def 3: 38 |
Def 1: 82.4% Def 2: 78.8% Def 3: 80.4% |
Def 1: 58.8% Def 2: 58.5% Def 3: 56% |
Belas (2012) [14] | 53.5 | Patient | 22 | 12 | 23 | 13 | 64.7% | 63.8% | NR | NR | NR | NR | NR | NR | NR | NR |
Ibrahiem (2012) [26] | 73.9 | Patient | 14 | 11 | 57 | 10 | 56% | 85.1% | NR | NR | NR | NR | NR | NR | NR | NR |
Sciarra (2012) [51] | 34.5 | Patient | 41 | 4 | 25 | 14 | 91.1% | 64.1% | NR | NR | NR | NR | NR | NR | NR | NR |
Portalez (2012) [45] | 48.1 | Lesion | Likert: 357 | Likert: 50 | Likert: 81 | Likert: 50 | Likert: 95% | Likert: 38% | Max CCL >3 mm and/or GG 4/5 | NR | NR | NR | NR | NR | NR | NR |
PI-RADS: 404 | PI-RADS: 47 | PI-RADS: 34 | PI-RADS: 47 | PI-RADS: 95% | PI-RADS: 58% | |||||||||||
Watanabe (2012) [59] | 48.1 | Patient | 485 | 73 | 624 | 266 | 86.9% | 70.1% | NR | NR | NR | NR | NR | NR | NR | NR |
Tamada (2011) [54] | 70 | Patient | 12 | 6 | 29 | 3 | 67% | 91% | NR | NR | NR | NR | NR | NR | NR | NR |
Region | 277 | 48 | 55 | 20 | 85% | 73% | ||||||||||
Choi (2011) [18] | 70.6 | Patient | 9 | 5 | 31 | 6 | 64.2% | 75.7% | NR | NR | NR | NR | NR | NR | NR | NR |
Iwazawa (2011) [28] | 40.5 | Region | 887 | 86 | 232 | 219 | 91.1% | 51.4% | NR | NR | NR | NR | NR | NR | NR | NR |
Rouse (2011) [48] | 33.7 | Sextant | 145 | 11 | 74 | 22 | 92.9% | 77.1% | GS ≥ 7: Def 1: ≥3 mm Def 2: ≥5 mm |
Def 1: 26.6% Def 2: 26.2% |
Def 1: 153 Def 2: 153 |
Def 1: 3 Def 2: 3 |
Def 1: 64 Def 1: 63 |
Def 1: 32 Def 2: 33 |
Def 1: 98.1% Def 2: 98.1% |
Def 1: 68.1% Def 2: 67% |
59.6 | Patient | 24 | 14 | 54 | 22 | 63.2% | 71.1% | Def 1: 41.2% Def 2: 36.8% |
Def 1: 30 Def 2: 31 |
Def 1: 4 Def 2: 3 |
Def 1: 43 Def 2: 39 |
Def 1: 4 Def 2: 3 |
Def 1: 88.2% Def 2: 91.2% |
Def 1: 53.8% Def 2: 48.8% |
||
Haffner (2011) [23] | 54.4 | Patient | 154 | 50 | 240 | 111 | 75.4% | 68.3% | NR | NR | NR | NR | NR | NR | NR | NR |
Panebianco (2010) [40] | 42.7 | Patient | NR | NR | NR | NR | 95.1% | 88.2% | NR | NR | NR | NR | NR | NR | NR | NR |
Roy (2010) [49] | 55.9 | Patient | NR | NR | NR | NR | 71% | 75% | NR | NR | NR | NR | NR | NR | NR | NR |
Testa (2010) [55] | 40.7 | Patient | NR | NR | NR | NR | 79.3% | 64% | NR | NR | NR | NR | NR | NR | NR | NR |
Sciarra (2010) [52] | 50 | Patient | 61 | 4 | 66 | 9 | 93.8% | 88% | NR | NR | NR | NR | NR | NR | NR | NR |
Kitajima (2010) [31] | 56.6 | Patient | 311 | 19 | 80 | 14 | 92.2% | 85.1% | NR | NR | NR | NR | NR | NR | NR | NR |
Labanaris (2010) [35] | 73.9 | Patient | 17 | 73 | 96 | 74 | 81.11% | 56.47% | NR | NR | NR | NR | NR | NR | NR | NR |
Kumar (2009) [32] | 21.7 | Patient | 39 | 3 | 10 | 8 | 92.8% | 55% | NR | NR | NR | NR | NR | NR | NR | NR |
Schmuecking (2009) [50] | NR | Lobe | NR | NR | NR | NR | 96% | 61% | NR | NR | NR | NR | NR | NR | NR | NR |
Cheikh (2009) [17] | 24.7 | Patient | 36 | 12 | 11 | 34 | 80% | 22.9% | NR | NR | NR | NR | NR | NR | NR | NR |
Cirillo (2008) [19] | 31.5 | Patient | 19 | 0 | 17 | 18 | 100% | 48.6% | NR | NR | NR | NR | NR | NR | NR | NR |
Kumar (2007) [33] | 13.3 | Patient | 39 | 0 | 11 | 33 | 100% | 25% | NR | NR | NR | NR | NR | NR | NR | NR |
Squillaci (2005) [53] | 50.8 | Patient | 29% | 8% | 25% | 3% | 89% | 80% | NR | NR | NR | NR | NR | NR | NR | NR |
Hara (2005) [24] | 41.5 | Patient | ≥2/3: 40 = 3/3: 47 |
≥2/3: 4 = 3/3: 8 |
≥2/3 30 = 3/3: 26 |
≥2/3: 8 = 3/3: 1 |
≥2/3: 90% = 3/3: 85% |
≥2/3: 78.9% = 3/3: 96.3% |
NR | NR | NR | NR | NR | NR | NR | NR |
Cancer prevalence tended to be higher and mpMRI NPV lower in the biopsy-naïve group as compared with the repeat biopsy group, in men with positive DRE as compared with men with negative DRE and when an endorectal coil was not used ( Table 3 ). There were no clear differences in the prevalence and NPV of the other analysed subgroups (TRUS-guided vs TTP biopsy, biopsy procedures with ≤16 cores vs >16 cores; Table 3 ). However, comparisons must be interpreted with care, due to the small number of studies in some subgroups. In patients with a PSA level of ≤10 ng/ml, the median NPV for overall PCa was 86.3% (IQR, 73.3–93.6%) for a median cancer prevalence of 35.4% (IQR, 27.6–42.5%).
Nb of studies | Median PCa prevalence | Median mpMRI NPV | Nb of studies | Median csPCa prevalence | Median mpMRI NPV | |
---|---|---|---|---|---|---|
Biopsy-naïve patients | 8 | 51.4% (45.5–56.7) | 69.9% (64.2–78) | 1 | 35.8% (NA) | 80.4% (NA) |
Repeat biopsy | 14 | 42% (35.1–52.6) | 82.6% (75.5–93.1) | 3 | 24.4% (19.1–32.8) | 88.2% (87.9–92.3) |
TRUS-guided biopsy | 36 | 49.7% (34.3–57.7) | 84.6% (68.6–92.8) | 4 | 28.1% (21.7–36.5) | 89.3% (82.9–92.4) |
TTP biopsy | 4 | 53.8% (47.5–57.8) | 73.6% (72–78.7) | 2 | 31.6% (30.5–32.8) | 92% (89.9–94) |
Biopsy with ≤16 cores | 28 | 48.7% (39.2–54.8) | 81.9% (66.8–89.3) | 5 | 28.1% (21.8–36.5) | 89.3% (82.9–92.4) |
Biopsy with >16 cores | 5 | 56.6% (51–61.3) | 81.1% (73.1–92.2) | 2 | 31.7% (30.5–32.8) | 92% (89.9–93.9) |
Positive DRE | 1 | 73.9% (NA) | 56% (NA) | 0 | – | – |
Negative DRE | 6 | 36% (34.6–46.8) | 82.7% (74.2–93.1) | 0 | – | – |
Endorectal coil | 17 | 41.7% (30.6–55.9) | 92.8% (79.3–95.4) | 1 | 31.7% (NA) | 91% (NA) |
No endorectal coil | 22 | 50.9% (41.7–56.1) | 77.7% (69.5–86.6) | 7 | 34% (26.9–46.1%) | 87.9% (78.2–92.1) |
Eight studies reported NPV at patient level for overall PCa and fulfilled the inclusion criteria for meta-analysis ( Table 4 ) [22 25 38 41 43 46 56 57] .
Study | Prevalence a (%) | Neg MRI (%) | NPV (%) | PPV (%) | Spe (%) | Se (%) | ||
---|---|---|---|---|---|---|---|---|
All PCa | Score ≥ 3/5 | Grenabo Bergdahl (2016) [22] | 31.3 | 66.9 | 83.7 | 47.5 | 63.2 | 73.1 |
Numao (2013) [38] | 45 | 29.4 | 70.6 | 64.3 | 71.0 | 63.9 | ||
Hauth (2015) [25] | 45.7 | 14.3 | 85.7 | 48.3 | 11.8 | 97.7 | ||
Vinet (2013) [57] | 49.3 | 24.6 | 64.7 | 53.8 | 31.4 | 82.4 | ||
Radtke (2015) [46] | 51 | 27 | 73 | 73.2 | 71.5 | 74.7 | ||
Thompson (2014) [56] | 61.3 | 31.4 | 68.6 | 76.8 | 60.3 | 82.6 | ||
Pokorny (2014) [43] | 63.7 | 30.9 | 69.1 | 82.4 | 69.1 | 82.4 | ||
Score ≥ 4/5 | Pepe (2015) [41] | 37 | 31 | 74.2 | 42 | 36.5 | 78.4% | |
Vinet (2013) [57] | 49.3 | 47.8 | 66.7 | 63.9 | 62.9 | 67.6% | ||
Radtke (2015) [46] | 51 | 73.5 | 63.9 | 92.3 | 95.8 | 48% | ||
Gleason ≥7 PCa | Score ≥ 3/5 | Radtke (2015) [46] | 29.3 | 27 | 87.9 | 45.1 | 59.6 | 80.2% |
a Prevalence of overall prostate cancers (10 first lines) or Gleason ≥7 cancers (last line).
PCa = prostate cancer; MRI = magnetic resonance imaging; Neg MRI = proportion of negative magnetic resonance imaging; NPV = negative predictive value; PPV = positive predictive value; Se = sensitivity; Spe = specificity.
Seven studies used a score of ≥3/5 for defining positive mpMRI ( Fig. 4 A and B) [22 25 38 43 46 56 57] . Fig. 4 C shows the conditional probability plot of 1 – NPV and PPV as a function of overall PCa prevalence. Table 5 shows NPV and PPV estimates for the given values of PCa prevalence.
PCaPrev | PPV | NPV |
---|---|---|
0.30 | 0.43 (0.34–0.53) | 0.88 (0.77–0.99) |
0.40 | 0.54 (0.45–0.64) | 0.82 (0.70–0.94) |
0.50 | 0.64 (0.55–0.73) | 0.76 (0.64–0.88) |
0.60 | 0.73 (0.65–0.80) | 0.67 (0.56–0.79) |
0.70 | 0.81 (0.75–0.87) | 0.57 (0.47–0.67) |
0.75 | 0.84 (0.79–0.89) | 0.51 (0.42–0.59) |
Only three studies used a score of ≥4/5 for defining positive mpMRI ( Table 4 ) [41 46 57] , and a formal meta-analysis could not be performed.
Only one study reporting NPV at patient level for Gleason ≥7 cancers met the selection criteria for inclusion in the meta-analysis. It reported NPV and PPV of 87.9% and 45.1%, respectively, for a prevalence of 29.3% ( Table 4 ) [46] .
We observed a large variability in reported NPV. Many factors, such as differences in mpMRI protocols, definition of negative mpMRI, or biopsy protocols, can explain this variability. However, two major causes of variability must be pointed out. First, the cancer prevalence was highly variable, ranging at patient level from 13% to 74.7% for overall PCa, and from 13.7% to 50.9% for csPCa. This variability was observed in both the biopsy-naïve and the repeat biopsy setting. As NPV depends on prevalence, this had a major impact on reported NPV ( Fig. 3 ). Second, the definition of csPCa was highly variable from one series to another, and differences of up to 21% could be observed in NPV when different definitions of csPCa were used in the same dataset [12 13 38 47 48] .
To account for clinical heterogeneity and to further explore the clinical relevance of the results, we carefully selected studies for inclusion in the meta-analysis based on stringent criteria. Particularly, we included only studies that: (1) had biopsy protocols with at least 10 cores, since it is no longer recommended to obtain less than 10 cores per biopsy; (2) used DWI, which is the most informative technique, at least for cancers in the peripheral zone [60] ; and (3) reported mpMRI findings using a five-level score, so that negative findings could be better defined. We accepted studies using a subjective (Likert) scale because experienced readers obtained equivalent [45 61 62] or better [63] results with the Likert score than with the PI-RADS v1 score. Owing to the large variations of NPV induced by differences in definitions of csPCa, we did not include different definitions in the meta-analysis since this would have introduced unacceptable clinical heterogeneity in the results, possibly resulting in erroneous and biased estimates. We, therefore, a priori restricted the definition of csPCa to cancers with a Gleason score of ≥7, given the low lethal potential of Gleason 6 cancers [64] and the lack of consensus among pathologists on the best method to measure biopsy core invasion length [65 66] .
In this more homogeneous group of studies, the prevalence range was still large (31.3–63.7%). As a result, we modelled the evolution of NPV (and PPV) as a function of overall PCa prevalence. Unfortunately, we could not duplicate this for csPCa since only one study reporting NPV for Gleason ≥7 cancers met the inclusion criteria for meta-analysis.
We included only studies that reported the results of systematic/standard biopsy in patients with negative mpMRI and used the systematic/standard biopsy as a reference standard. It is well known that TRUS-guided biopsy harbours both random and systematic errors, as evidenced by the high rates of positivity of immediate repeat biopsy after a first series of negative biopsies [67 68] , and as confirmed recently by the PROMIS trial [69] . Therefore, using TRUS-guided biopsy as a reference standard may have overestimated the NPV of mpMRI. However, studies using radical prostatectomy specimens as a reference standard have already reported mpMRI detection rates in relation to PCa Gleason score and volume [1] . In this review, we intended to address the more pragmatic question as to whether a negative mpMRI could predict a negative subsequent biopsy. This is an important question because if the NPV of mpMRI was sufficiently high in comparison with the reference standard of systematic/standard biopsies, then in practice a negative mpMRI result could indeed avoid the need for prostate biopsy. Therefore, studies reporting only biopsy results when the mpMRI was positive (eg, obtained through MRI-targeted, guided, or fusion biopsies with added systematic biopsies) were not included in this review.
It is now well established that mpMRI is a sensitive tool for detecting aggressive PCa 1 2 3 69] . However several reasons preclude its broad use as a triage test before biopsy.
Firstly, the population referred to prostate biopsy is not standardised. The large range of reported prevalence for overall PCa and csPCa suggests substantial heterogeneity in the way patients are selected for biopsy. Owing to this heterogeneity, we did not provide a pooled estimate for mpMRI NPV. The role of mpMRI as a triage test before prostate biopsy should be evaluated in the broader context of the selection of patients with a suspicion of (aggressive) PCa. In a recent retrospective study of 514 patients, mpMRI NPV for Gleason ≥7 cancers was 91% when the PSA density was ≤0.2 ng/ml/ml, and only 71% when the PSA density was >0.2 ng/ml/ml ( p = 0.003) [70] . In another series of 288 biopsy-naïve patients, no csPCa (Gleason score ≥7 or maximum cancer core length ≥4 mm) was found in 44 patients with a PSA density of <0.15 ng/ml/ml and a PI-RADS v2 score of <3/5 [71] . We believe that such prestratification of the risk of csPCa is an interesting way for rationalising the use of mpMRI before biopsy. Patients found at very low risk would be spared both mpMRI and biopsy. Patients at a low risk—for whom mpMRI would have an NPV high enough to be used as a triage test—could avoid biopsy in case of negative mpMRI. Patients at a higher risk would need biopsy even in case of negative mpMRI. Many tools can be used to risk stratify the population of patients referred to biopsy, ranging from simple parameters such as PSA density to more complicated risk calculators [72 73] . The impact of these tools on the NPV of prebiopsy mpMRI needs to be carefully evaluated, both in the biopsy-naïve and in the repeat biopsy setting. For the moment, it is impossible to make any recommendations on the best way to risk stratify patients before referring them for mpMRI.
Secondly, the large variability in the definition of csPCa precludes any definitive conclusion on the ability of mpMRI to rule out aggressive cancer. The issue of the most appropriate definition of csPCa on biopsy is complex, since biopsy results may accurately reflect neither tumour burden nor aggressiveness. Nonetheless, there is an urgent need to standardise the histological definition(s) of csPCa, to allow meaningful comparisons between studies.
Thirdly, the specificity of mpMRI remains moderate, and there is a substantial proportion of false positives in the lesions scored 3/5 or 4/5 [1 74 75] , even with the new PI-RADS v2 score [76] . In a series of 62 patients with 116 lesions biopsied under magnetic resonance/ultrasound fusion, the overall cancer detection rates for PI-RADS v2 scores of 3/5 and 4/5 were only 15.8% and 29.8%, respectively [77] . In theory, a triage test used to rule out a disease needs to be highly sensitive for this disease. However, if its specificity is too low, it will be clinically useless since most patients will be positive, whether they have the disease or not. Therefore, if mpMRI is to be used as a triage test in the future, there is a need to improve its specificity. This could be achieved by a continuous refinement of scores [78] . Promising results in characterising csPCa have also been reported with a quantitative analysis [79] .
Finally, all published studies were conducted in specialised centres. The broad use of mpMRI as a triage test assumes good interobserver reproducibility. Unfortunately, interobserver reproducibility of existing scoring systems remains moderate [62 63 80] even with the use of the PI-RADS v2 score [80 81] . Studies evaluating on a large scale the reproducibility of mpMRI findings between expert and nonexpert centres are currently lacking.
Three systematic reviews (including two meta-analyses) regarding the role of mpMRI in localised PCa have been published recently 4 5 6 . Crucially, all three reviews focused exclusively on the sensitivity of mpMRI-targeted, guided, or fusion biopsies in diagnosing overall PCa and csPCa, using TRUS-guided prostate biopsies as reference standards. The impact of systematic biopsies on the outcome was not addressed in any of the reviews, within either the index test or the reference standard. Our review had a totally different research question and objective, focusing on NPV of mpMRI to see if a negative mpMRI can avoid the need for a prostate biopsy. As MRI-targeted/guided/fusion biopsies are not relevant if the mpMRI was negative for cancer, it can be argued that the three reviews assessed a different index test altogether. As such, we believe that the findings of this review are novel and unique, and pave the way for further focused clinical studies.
The current study represents the first systematic review addressing the role of mpMRI as a triage test before biopsy. The review elements were developed in conjunction with a multidisciplinary panel of experts (EAU Prostate Cancer Guidelines Panel), which included a patient representative, and the review was performed robustly in accordance with recognised standards. However, it is limited by the major heterogeneity of the existing literature in patient population, study design, and definitions of positive mpMRI and csPCa. It highlighted further areas of research that could help in defining the best use of mpMRI in the early detection of aggressive PCa in the future.
Although mpMRI can detect aggressive PCa with excellent sensitivity, a definitive conclusion on its role as a triage test before prostate biopsy will be possible only when three main issues are addressed. Firstly, because NPV depends on prevalence, and because overall PCa and csPCa prevalence was highly variable in the published series, it becomes mandatory to define the optimal way to pre-evaluate the risk of csPCa in patients with a suspicion of PCa. Depending on the risk category, mpMRI could then be used to obviate biopsies or not. Secondly, there is a need for consensus definitions of csPCa on biopsy findings to allow interstudy comparisons. Thirdly, although efforts have been made to standardise mpMRI technical protocols and interpretation in the past few years [11 60 76] , there is still a crucial need to improve mpMRI specificity and inter-reader reproducibility.
This systematic review was performed under the auspices of:
The European Association of Urology Guidelines Office Board
The European Association of Urology Prostate Cancer Guideline Panel
Author contributions: Olivier Rouvière had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.
Study concept and design: Rouvière, Mottet, Cornford.
Acquisition of data: Rouvière, Moldovan, Van den Broeck, Yuan.
Analysis and interpretation of data: Rouvière, Moldovan, Van den Broeck, Lam.
Drafting of the manuscript: Rouvière, Moldovan, Van den Broeck, Lam.
Critical revision of the manuscript for important intellectual content: Bellmunt, van den Bergh, Bolla, Briers, Van den Broeck, Cornford, Cumberbatch, De Santis, Fossati, Gross, Henry, Joniau, Lam, Matveev, Moldovan, van der Poel, van der Kwast, Rouvière, Schoots, Wiegel, Mottet.
Statistical analysis: None.
Obtaining funding: None.
Administrative, technical, or material support: Yuan, Sylvester, Marconi.
Supervision: None.
Other: None.
Financial disclosures: Olivier Rouvière certifies that all conflicts of interest, including specific financial interests and relationships and affiliations relevant to the subject matter or materials discussed in the manuscript (eg, employment/affiliation, grants or funding, consultancies, honoraria, stock ownership or options, expert testimony, royalties, or patents filed, received, or pending), are the following: Bellmunt is a company consultant for Janssen, Astellas, Pierre Fabre, Genentech, Merck, Ipsen, Pfizer, Novartis, and Sanofi Aventis. He has received research support from Takeda, Novartis, and Sanofi, and received travel grants from Pfizer and Pierre Fabre. Bolla has received company speaker honoraria from Ipsen and Astellas, honoraria or consultation fees from Janssen, and fellowship and travel grants from Janssen, AstraZeneca, and Astellas. Briers has received grant and research support from Ipsen, European Association of Urology, and Bayer; is an ex officio board member for Europa UOMO; is an ethics committee and advisory group member for REQUITE; is a member patient advisory board member for PAGMI; and is a member of SCA and EMA PCWP. Cornford is a company consultant for Astellas, Ipsen, and Ferring. He receives company speaker honoraria from Astellas, Janssen, Ipsen, and Pfizer; participates in trials from Ferring; and receives fellowships and travel grants from Astellas and Janssen. De Santis is a company consultant for GlaxoSmithKline, Janssen, Bayer, Novartis, Pierre Fabre, Astellas, Amgen, Eisai Inc., ESSA, Merck, and Synthon; has received company speaker honoraria from Pfizer, Takeda, Sanofi Aventis, Shionogi, Celgene, and Teva OncoGenex; has participated in trials for Pierre Fabre, Astellas, Exelixis, Bayer, and Roche; has received fellowship and travel grants from Bayer, Novartis, Ferring, Astellas, Sanofi Aventis, and Janssen; has received grant and research support from Pierre Fabre; has received honoraria from AstraZeneca; and is associated with Amgen. Joniau is a company consultant for Astellas, Ipsen, Bayer, Sanofi, and Janssen; has received company speaker honoraria from Astellas, Amgen, Bayer, Sanofi, Janssen, and Ipsen; has participated in trials for Astellas, Janssen, and Bayer; has received fellowship and travel grants from Astellas, Amgen, Bayer, Sanofi, Janssen, Ipsen, and Pfizer; and has received grant and research support from Astellas, Bayer, and Janssen. Matveev has received company speaker honoraria from Sanofi and Astellas, has participated in trials for Astellas, Pfizer and Novartis. Lam is a company consultant for and has received company speaker honoraria from Pfizer, GSK, Astellas, and Ipsen. van der Poel is a company consultant for Intuitive Surgical, has participated in trials for Astellas and Steba Biotech, and has received grant and research support from Astellas. Rouvière is a company consultant for EDAP-TMS, Bracco, and Philips; has received company speaker honoraria from EDAP-TMS, Bracco, and Philips; and has participated in trials for EDAP-TMS and Bracco. Wiegel has received company speaker honoraria from Astellas, Takeda, Hexal, Ipsen, Janssen-Cilac, and Ferring. Mottet has received grant and research support from Takeda Pharmaceutical, Millenium, Astellas, Pierre Fabre, Sanofi, and Pasteur, and has received honoraria or consultation fees from Takeda Pharaceutical, Millenium, Jansen, Astellas, BMS, Bayer, Ipsen, Ferring, Novartis, Nuclétron, Pierre Fabre, Sanofi, and Zeneca. van den Bergh, Van den Broeck, Cumberbatch, Fossati, Gross, Henry, van der Kwast, Sylvester, Yuan, Schoots, Moldovan, and Marconi have nothing to disclose.
Funding/Support and role of the sponsor: None.
A correlation with radical prostatectomy specimens has demonstrated that multiparametric magnetic resonance imaging (mpMRI) has excellent sensitivity in detecting prostate cancer (PCa) with a Gleason score of ≥7 1 2 3 . As a result, prostate mpMRI is increasingly used in patients with a suspicion of PCa to localise abnormal areas before biopsy. A large body of literature has shown that targeted biopsies of suspicious lesions seen on mpMRI (TBx) improved the detection of clinically significant PCa (csPCa), at least in the repeat biopsy setting 4 5 6 . As a result, it is now recommended that an mpMRI is performed before repeat biopsy to allow TBx of suspicious lesions in addition to standard biopsies [7] .
Some authors have recently suggested that, besides improving csPCa detection, mpMRI could also be used as a triage test so that patients with negative mpMRI findings could obviate biopsy. Such a strategy remains highly controversial [8] and depends upon the negative predictive value (NPV) of mpMRI. Therefore, the European Association of Urology Prostate Cancer Guidelines Panel undertook this systematic review and meta-analysis to assess the NPV of mpMRI in patients with a suspicion of PCa and, thus, its potential role in eliminating unnecessary prostate biopsy.
Our primary aim was to systematically evaluate the performance of negative prebiopsy prostate mpMRI in predicting a negative biopsy result for overall PCa and csPCa in biopsy-naïve men and in men with previously negative biopsies. A further objective was to explore and define factors that may contribute to relevant thresholds in order to provide guidance for future studies.
The review was performed according to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) statement [9] . The review protocol was published in PROSPERO database ( http://www.crd.york.ac.uk/PROSPERO; registration number CRD42015021929). Databases searched included the Embase and OVID Medline databases, the Cochrane database of systematic reviews, and the Cochrane Central Register for Clinical Trials, covering from January 1, 2000 to February 13, 2016. Systematic or standard prostate biopsies were used as reference standards, with positive or negative cases of PCa being determined by histopathological examination. The detailed search strategy is presented in Supplement 1.
Included studies focused on men who were assessed for suspected PCa by mpMRI before undergoing prostate biopsy. Studies enrolling both biopsy-naïve men and men who had undergone previous negative biopsies were included. Prebiopsy prostate mpMRI was considered the index test and comprised T2-weighted imaging (T2WI) and at least one functional imaging technique (diffusion-weighted imaging [DWI], dynamic contrast-enhanced imaging [DCEI], or magnetic resonance spectroscopic imaging [MRSI]). For inclusion, studies had to report on false negatives and true negatives, in order to calculate NPV (ie, results of systematic/standard prostate biopsies when the mpMRI was negative). When available, false positive and true positive findings were also noted to calculate the positive predictive value (PPV) and the cancer prevalence. There was restriction neither on the biopsy technique (transrectal or transperineal) nor on the number of biopsy cores. Studies using radical prostatectomy specimens as reference standards were excluded, as were studies evaluating men with histologically proven PCa. Studies with less than 50 participants were excluded. No language restrictions were applied.
Two reviewers (P.C.M. and T.V.D.B.) independently screened all abstracts and full-text articles for eligibility. Disagreement was resolved by consensus or reference to an independent third party (L.M.). All screening was performed using a predefined eligibility form.
Using a data extraction form developed a priori, the same two reviewers independently extracted data concerning study methodology, patient characteristics, technical characteristics of the MR scanners, mpMRI protocol, mpMRI scoring system, definition of positive mpMRI, biopsy protocol, and definition of csPCa. Any discrepancies concerning data extraction were resolved by consensus or reference to an independent arbiter (O.R. or T.B.L.).
To assess the risk of bias (RoB), all included reports were reviewed using the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool for diagnostic accuracy studies [10] .
Outcome data regarding false negative and true negative values of mpMRI before prostate biopsy were recorded as reported by authors. When not available, data were indirectly derived from specificity, sensitivity, and prevalence values reported by authors using an online Bayesian statistics calculator ( http://www.medcalc.com/bayes.html ). Descriptive statistics were used to summarise baseline characteristics and outcomes, including median and interquartile range (IQR) for estimates of NPV across studies. A correlation between mpMRI NPV and a positive biopsy rate was established using the Pearson's correlation coefficient.
A meta-analysis was undertaken to calculate pooled NPV and PPV. To ensure appropriate clinical homogeneity of the studies included in the meta-analysis, we selected only the studies enrolling biopsy-naïve patients and/or patients with a history of negative biopsy, and fulfilling the following criteria that were defined a priori: (1) reference standard consisting of prostate biopsy with at least 10 samples on all patients; (2) mpMRI protocol comprising at least T2WI and DWI; (3) mpMRI results presented as a five-level score, using a subjective Likert scale or the Prostate Imaging Reporting Data System (PI-RADS) score [11] ; (4) definition of positive mpMRI as a score ≥3/5 or ≥4/5; and (5) results reported on a per patient basis. In addition, only studies defining csPCa as Gleason ≥7 cancers were selected for the meta-analysis assessing the mpMRI NPV for csPCa. A bivariate random-effects approach was employed using the Midas package in Stata 12 (StataCorp LP, College Station, TX, USA). Since the NPV decreases and the PPV increases as the prevalence increases, post-test probability estimates of NPV and PPV were reported for the given values of the prevalence based on Bayes’ theorem.
For other studies not included in the meta-analysis based on the criteria described above, a narrative synthesis of the data was performed. To explore and define clinical heterogeneity, subgroups were analysed at patient level based on the following variables: biopsy-naïve versus previous negative biopsy; patients with positive versus negative digital rectal examination (DRE); mpMRI performed with an endorectal versus without an endorectal coil; transrectal ultrasound (TRUS) versus template transperineal (TTP) biopsy approach; and ≤16 cores versus >16 cores as the reference standard. Studies reporting mpMRI NPV for patients with a prostate-specific antigen (PSA) level of ≤10 ng/ml were also reported separately.
The study selection process is depicted in the PRISMA flow diagram ( Fig. 1 ). A total of 2980 abstracts were retrieved. After abstract screening and removal of duplicates, 240 articles were eligible for full text screening, of which 48 studies were eligible for inclusion 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 .
Out of the 48 included studies, 42 were single-centre and six were multicentre studies. Thirty-four studies were prospective and six were retrospective, whilst the design of the rest was unclear. RoB assessment using QUADAS-2 was performed for each of the individual studies ( Fig. 2 A and B). Overall, the RoB was highly heterogeneous across studies for all criteria, except for the reference standard domain, in which RoB was low in most studies.
The 48 studies comprised a total of 9613 men who underwent prostate mpMRI followed by biopsy. The study and patient baseline characteristics are presented in Table 1 . The patient population consisted of biopsy-naive men in nine studies, men with at least one previous negative biopsy in 16 studies, and both biopsy-naïve men and men with a history of previous negative biopsy in nine studies. In 14 studies, the biopsy history of the patients was unclear.
Study | Study design | Period | Population | Pt Nb | Mean/median* age (yr) | Mean/median* PSA (ng/ml) | Mean/median* prostate volume (cm 3 ) | Magnetic field strength | MR pulse sequences | Endorectal coil | MR score | Definition of positive MRI | Reference standard |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Hauth (2015) [25] | Prospective | 2011–2013 | FB | 94 | 64 (43–83) | 9 (3–31) | 51 (17–140) | 1.5 T | T2WI/DWI/DCEI/MRSI | No | PI-RADS v1 | ≥3 | 11–13-core TRUS SBx + TBx |
Lamb (2015) [36] | Retrospective | 2013–2013 | FB & PNB | 173 | NR | NR | NR | 1.5 T | T2WI/DWI | NR | NR | NR | 12-core TRUS SBx |
Brock (2015) [15] | Prospective | 2013–2014 | PNB | 168 | 64* (IQR 59–70) | 9.2* (IQR 6.7–13.4) | 55.4* (IQR 42–80) | 3 T | T2WI/DWI/DCEI | No | PI-RADS v1 | NR | 12/24-core TRUS SBx + TBx |
Grenabo Bergdahl (2016) [22] | Prospective | 2013–2014 | FB & PNB | 83 | 69.3* (IQR 69–69.6) | 1.6* (IQR 0.9–2.7) | NR | 3 T | T2WI/DWI/DCEI/MRSI | No | PI-RADS v1 | ≥3 | 10-core TRUS SBx + TBx |
Wang (2015) [58] | Prospective | 2002–2009 | FB & PNB | 586 | 70 (26–91) | 11.11* (0.02–9794) | NR | 1.5 T | T2WI/DWI/DCEI/MRSI | Yes | PI-RADS v1 | ≥3 | TRUS SBx |
Pepe (2015) [41] | Prospective | 2011–2014 | PNB | 100 | 64* | 8.6* (4.2–10) | NR | 3 T | T2WI/DWI/DCEI/MRSI | No | PI-RADS v1 | ≥4 | TPBx + TBx |
Panebianco (2015) [39] | Prospective | 2011–2014 | FB (61.62%) & PNB (38.34%) | 925 (1140 total cohort) |
NR | NR | NR | 3 T | T2WI/DWI/DCEI | Yes | PI-RADS v1 | NR | 14-core TRUS SBx; 45-core sat TPBx + TBx |
Radtke (2015) [46] | Prospective | 2013–2013 | FB (63.3%) & PNB (36.7%) | 294 | 64* (60–71) | 7.3 (6.0) | 47 (37.5) | 3 T | T2WI/DWI/DCEI | No | PI-RADS v1 | PI-RADS ≥2; PI-RADS ≥3; PI-RADS ≥4; PI-RADS = 5; |
24-core TPBx + TBx |
Itatani (2014) [27] | Retrospective | 2004–2007 | NR | 193 | 68.9 (8.4); 70* (47–89) | 11.8 (15.9); 7.9* (1.22–159) | NR | 1.5 T | T2WI/DWI/DCEI | No | 1–5 scale (Likert) | ≥3 | 12–14-core TRUS SBx |
Porpiglia (2014) [44] | Prospective | 2011–2013 | PNB | 170 | 65* (60–70) | 6.9* (5.2–9.8) | 42* (36–48) | 1.5 T | T2WI/DWI/DCEI | Yes | Dichotomous | Positive: at least 2/3 MR seq. with suspicious findings | 18–24-core TRUS SBx (volume dependent) |
Thompson (2014) [56] | Prospective | 2012–2013 | FB (88%) & PNB (12%) | 150 | 62.4* (IQR 55.0–66.4) | 5.6* (IQR 4.5–7.5) | 40* (IQR 30–57) | 1.5 T (47%) & 3 T (53%) | T2WI/DWI/DCEI | No | PI-RADS v1 | ≥3 | Median of 30 TPBx (volume dependent) |
Pokorny (2014) [43] | Prospective | 2012–2013 | FB | 223 | 63* (IQR 57–68) | 5.3* (IQR 4.1–6.6) | 41* (IQR 30–59) | 3 T | T2WI/DWI/DCEI | No | PI-RADS v1 | ≥3 (primary); ≥4 |
12-core TRUS SBx + TBx |
Petrillo (2014) [42] | Prospective | 2009–2010 | NR | 136 | NR | NR | NR | 1.5 T | T2WI/DWI/MRSI | Yes | 1–5 scale (Likert) | ≥3 | 12–16-core TRUS SBx (volume + PSA dependent) |
Javali (2014) [29] | Retrospective | 2002–2011 | NR | 140 | Control: 62.4 (10.5); Study: 62.9 (12.1) | Control: 6.8 (2.3); Study: 6.87 (2.6) | Control: 44 (14.2); Study: 43 (18.4) | 1.5 T | T2WI/MRSI | Yes | Dichotomous | Cit/[Cho + Cr] < 1.2 | 6-core TRUS SBx ( n = 69), 12-core TRUS SBx ( n = 119) |
Abd-Alazeez (2014) [13] | Prospective | 2007–2011 | FB | 129 | 62* (41–82) | 5.8* (1.2–20) | 40* (16–137) | 1.5 & 3 T | T2WI/DWI/DCEI | No | PI-RADS v1 | ≥3 (primary); ≥4 |
20-core TPBx |
Abd-Alazeez (2014) [12] | Retrospective | NR | PNB | 54 | 64* (39–75) | 10* (2–23) | 53* (19–136) | 1.5 & 3 T | T2WI/DWI/DCEI | No | PI-RADS v1 | ≥3 (primary); ≥4 |
≥20-core TPBx + TBx ( n = 15) |
Matsuoka (2014) [37] | Prospective | 2007–2012 | NR | 135 | 67* (50–80) | 7.0* (2.9–19.8) | 25.4* (12.7–90.2) | 1.5 T | T2WI/DWI | No | 1–5 scale (Likert) | ≥3 | 14-core TRUS SBX |
Junker (2013) [30] | Retrospective | 2011–2013 | PNB | 73 | 62 (7.4) | 7.0* (5.1–12.9) | 45* (34–61) | 3 T | T2WI/DWI/DCEI | No | PI-RADS | PI-RADS ≥10 and ≥11 for all PCa PI-RADS ≥13 for significant PCa |
10-core TRUS SBx + TBx |
Busetto (2013) [16] | Prospective | 2010–2012 | PNB | 163 | 66.4 (5.3) | 6.8 (1.6) | NR | 3 T | T2WI/DWI/DCEI/MRSI | Yes | NR | NR | 10-core TRUS SBx + TBx |
Rais-Bahrami (2013) [47] | Prospective | 2007–2012 | NR | 583 | 61.3 (8.4) | 9.9 (13.1) | NR | 3 T | T2WI/DWI/DCEI/MRSI | Yes | 1–4 scale (Likert) | ≥2 ≥3 |
12-core TRUS SBx + TBx |
Kuru (2013) [34] | Prospective | 2010–2011 | FB (51%) & PNB (49%) | 347 | 65.3 (42–82) | 9.85 (0.5–104) | 48.7 (9–180) | 3 T | T2WI/DWI/DCEI | No | 1–3 scale (Likert) | ≥2 | 12–36-core TRUS SBx (volume dependent) + TBx |
Ferda (2013) [20] | Prospective | NR | NR | 164 | (49–74) | (4.2–123) | NR | 3 T | T2WI/DWI/DCEI/MRSI | No | NR | In house | TRUS SBx |
Ganie (2013) [21] | NR | 2007–2009 | PNB | 87 | NR | NR | NR | 1.5 T | T2WI/MRSI | Yes | MRSI Cho/Cit ratio | In house | 6 core TRUS SBx + MRI TBx |
Vinet (2013) [57] | Prospective | 2009–2011 | FB | 69 | NR | 5.2* (3.2–28) | NR | 1.5 T (35 pts) & 3 T (34 pts) | T2WI/DWI/DCEI | No | 1–5 scale (Likert) | ≥3 | 12-core TRUS SBx + TBx |
Numao (2013) [38] | Prospective | 2006–2010 | FB | 351 | 65* (59–70) | 6.3* (4.9–9.1) | 32* (24–42) | 1.5 T | T2WI/DWI/DCEI (no DCEI in 42 pts) | No | 1–5 scale (Likert) | ≥3 | 3D 26-core (12 TRUS SBx + 14 TPBx – 203 pts); 3D 14-core (6 TRUS SBx + 8 TPBx – 102 pts); TPBx 14 core (46 pts) |
Belas (2012) [14] | Prospective | 2010–2011 | FB | 71 | 66* (47–76) | 7* (4–10) | 45* (15–150) | 1.5 T | T2WI/DWI/DCEI | No | TZ: 0–4 scale PZ: 0–10 scale |
TZ: >2 PZ: >6 |
12-core TRUS SBx + TBx |
Ibrahiem (2012) [26] | Prospective | 2008–2009 | FB | 100 | 65.03 (7.13) | 26.3 (24.2) | 60.09 (28.7) | 1.5 T | T2WI/DWI | No | NR | In house | 12-core TRUS SBX |
Sciarra (2012) [51] | Prospective | 2008–2011 | PNB | 84 | 64.09 (46–76) | 7.07 (4.2–15.5) | NR | 3 T | T2WI/DWI/DCEI/MRSI | Yes | NR | NR | 10-core TRUS Bx + TBx |
Portalez (2012) [45] | Prospective | 2011 | PNB | 129 | 64.7 (47–79) | 9.6 (2.7–40) | 51.1 (12–192) | 1.5 T | T2WI/DWI/DCEI | Mixed | 1–5 scale (Likert) PI-RADS |
Likert ≥3 PI-RADS ≥9 |
10–12-core TRUS SBx + TBx |
Watanabe (2012) [59] | Prospective | 2004–2008 | NR | 1448 | 72 (7.5) | NR | NR | 1.5 T | T2WI/DWI | No | NR | ADC value ≤1.35 × 10 −3 mm 2 /s | 8-core TRUS SBx + TBx |
Tamada (2011) [54] | Retrospective | 2006–2009 | NR | 50 | 70 (40–84) | 6.84* (4.06–9.94) | NR | 1.5 T | T2WI/DWI/DCEI | No | NR | In house | 12-core TRUS SBx |
Choi (2011) [18] | NR | 2009–2010 | NR | 51 | 67.16 (56–90) | 14.16 (1.02–38.9) | 42.98 (13.8–77.3) | 3 T | T2WI/DWI | NR | NR | NR | 10–12-core TRUS SBx + TBx |
Iwazawa (2011) [28] | Retrospective | 2008–2009 | NR | 178 | 68.8 (41–86) | 20.51 (4.04–568.5) | NR | 1.5 T | T2WI/DWI/DCEI | NR | 1–4 scale (Likert) | NR | 10–12-core TRUS SBx (TBx included in SBx chart) |
Rouse (2011) [48] | Prospective | 2005–2007 | PNB | 114 | 63.6 (41–83) | 13.4 (0–228) | NR | 1.5 T | T2WI/DWI/DCEI | NR | 1–5 scale (Likert) | ≥3 | TRUS SBx |
Haffner (2011) [23] | Prospective | 2005–2009 | FB | 555 | 64* (47–83) | 6.75* (0.18–100) | 46* (15–200) | 1.5 T | T2WI/DCEI | No | 1–5 scale (Likert) | ≥3 | 10-core TRUS SBx + TBx |
Panebianco (2010) [40] | Prospective | 2007–2009 | PNB | 150 | 61.2 (46–78) | 9.42 (3.91) | 41.17 (7.47) | 1.5 T | T2WI/DCEI/MRSI | Yes | NR | In house | 10-core TRUS SBx (TBx included in SBx chart) |
Roy (2010) [49] | Not specified | 2011–2009 | FB (53%) & PNB (47%) | 103 | 63 (52–78) | 7* | NR | 3 T | T2WI/DWI/DCEI | Yes | NR | NR | 8-core TRUS SBx + TBx |
Testa (2010) [55] | Not specified | 2007 | PNB | 54 | 63.9 (52–76) | 11.4 (3–42) | 59.3 (30–150) | 1.5 T | T2WI/MRSI | Yes | 1–3 scale (Likert) | ≥2 | 12-core TRUS SBx + TBx |
Sciarra (2010) [52] | Prospective | 2007–2009 | PNB | 110 | 63.5 (49–74) | NR | NR | 1.5 T | T2WI/DCEI/MRSI | Yes | NR | In house | 10-core TRUS SBx + TBx |
Kitajima (2010) [31] | Prospective | 2008–2009 | NR | 53 | 69* (56–84) | 11.1* (4.2–112.1) | NR | 3 T | T2WI/DWI/DCEI | No | 1–5 scale (Likert) | ≥3 | 20-core TPBx |
Labanaris (2010) [35] | Prospective | 2004–2008 | PNB | 260 | NR | NR | NR | 1 T | T2WI/DWI/DCEI | Yes | Dichotomous | In house | 18-core TRUS SBx |
Kumar (2009) [32] | NR | NR | NR | 61 | 65.3 (9.3) | 16.5 (0.21–155) | NR | 1.5 T | T2WI/MRSI | Yes | NR | (Cit/(Cho + Cr) ≤ 1.2 | TRUS Bx |
Schmuecking (2009) [50] | NR | NR | FB & PNB | 67 | 68 | 11.5 | NR | 1.5 T | T2WI/DCEI | No | NR | NR | 20-core Bx |
Cheikh (2009) [17] | Retrospective | 2005–2008 | PNB | 93 | 63.2 (52–74) | 9.63 (1.6–40) | NR | 1.5 T | T2WI/DCEI | No | Dichotomous | In house | 12-core TRUS SBx + TBx |
Cirillo (2008) [19] | Prospective | 2004–2006 | PNB | 54 | 65.5 (5.2) | 10.8 (7.5) | NR | 1.5 T | T2WI/MRSI | Yes | Dichotomous | In house | 10-core TRUS SBx + TBx |
Kumar (2007) [33] | Prospective | 2003–2005 | NR | 83 | NR | NR | NR | 1.5 T | T2WI/MRSI | Yes | NR | NR | 12-core TRUS SBx + TBx |
Squillaci (2005) [53] | Prospective | 2004–2005 | NR | 65 | NR | NR | NR | 1.5 T | T2WI/DCEI/MRSI | No | 1–3 scale (Likert) | ≥2 | 10-core TRUS SBx + TBx |
Hara (2005) [24] | Prospective | 2003–2004 | FB | 90 | 67.2 (NR) | NR | NR | 1.5 T | T2WI/DCEI | No | 1–3 scale (Likert) | ≥2 = 3 |
14-core TRUS SBx |
The magnetic field strength was 1, 1.5, and 3 T in one, 28, and 15 studies, respectively. Four studies used both 1.5 and 3 T MR systems. DWI and DCEI were used in 36 and 35 studies, respectively. Nineteen studies also added MRSI. An endorectal coil was used in 18 studies. The definition of positive mpMRI varied across studies. The PI-RADS v1 score was used in 12 studies, a five-level subjective (Likert) score was used in eight studies, and one study reported data based on the two scoring systems. In-house criteria were used in 13 studies for defining positive mpMRI, and five studies used a dichotomous definition. Nine studies did not report on the criteria for positive mpMRI. No study used the PI-RADS v2 score.
Regarding the reference standard, TRUS-guided biopsies were used in 39 studies, TTP biopsies in six studies, and mixed TRUS-guided and TTP biopsies in two studies. In one study, the biopsy approach was unclear. The number of cores per biopsy procedure was ≤16 in 30 studies, >16 in nine studies, and variable among patients in three studies. For six studies, the number of biopsy cores taken was unclear.
At patient level, the median biopsy positivity rate (ie, cancer prevalence) was 50.4% (IQR, 36.4–57.7%) for overall cancer and 32.9% (IQR, 28.1–37.2%) for csPCa ( Table 2 ). The median mpMRI NPV was 82.4% (IQR, 69.0–92.4%) for overall cancer and 88.1% (IQR, 85.7–92.3) for csPCa. NPV significantly decreased when cancer prevalence increased, both for overall cancer ( r = –0.64, p < 0.0001) and csPCa ( r = –0.75, p = 0.032; Fig. 3 ). In addition, NPV was highly dependent on the definition used for csPCa, with differences of up to 21% when several definitions were used in the same dataset [12 13 38 47 48] .
Study | Overall PCa prevalence (%) | Reporting level | Multiparametric MRI performance for PCa detection | Definition of csPCa | csPCa prevalence | Multiparametric MRI performance for csPCa detection | ||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
TN | FN | TP | FP | NPV | PPV | TN | FN | TP | FP | NPV | PPV | |||||
Hauth (2015) [25] | 45.7 | Patient | 6 | 1 | 42 | 45 | 85.7% | 48.3% | Low grade: GS ≤ 6 High grade: GS ≥ 7 |
NR | NR | NR | NR | NR | NR | NR |
Lesion | 59 | 13 | 55 | 73 | 81.9% | 43% | ||||||||||
Lamb (2015) [36] | 65.9 | Patient | 23 | 22 | 92 | 36 | 51.1% | 71.9% | GS ≥ 7 | 50.9% | 31 | 14 | 71 | 57 | 68.9% | 55.5% |
Brock (2015) [15] | 42.3 | Patient | 17 | 7 | 56 | 88 | 70.8% | SBx: 38.8% TBx: 22.2% Duo: 44.4% |
Epstein: GS > 6 and/or max CCL ≥50% | 24.4% | SBx: 21 | SBx: 3 | SBx: 38 TBx: 27 duo: 47 |
SBx: 106 TBx: 117 duo: 97 |
87.5% | SBx: 26.4% TBx: 18.8% duo: 32.6% |
Grenabo Bergdahl (2016) [22] | 33.7 | Patient | 36 | 7 | 19 | 21 | 83.7% | 47.5% | Clinically insignificant PCa: T1c, PSAd < 0.15, GS < 7, ≤2 positive cores, and unilateral cancer | NR | NR | NR | NR | NR | NR | NR |
Wang (2015) [58] | 58 | Patient | 165 | 8 | 332 | 81 | 95.4% | 80.4% | NR | NR | NR | NR | NR | NR | NR | NR |
Pepe (2015) [41] | 37 | Patient | 23 | 8 | 29 | 40 | 74.2% | 42% | GS ≥ 7 or GS 6 with CCL ≥ 50% | NR | NR | NR | NR | NR | 100% | 55.8% |
Panebianco (2015) [39] | 74.7 | Patient | Group A (satBx): 104 | Group A (satBx): 43 | Group A: 186 | Group A: 22 | Group A (satBx): 70.7% | Group A: 89.4% | NR | 60% | Group A: 147 | Group A: 0 | Group A: 183 | Group A: 25 | Group A: 100% | Group A: 88% |
Group B (TRUSGB NR TRUS G satBx): 93 | Group B (TRUSGB NR TRUS G satBx): 37 | Group B: 417 before and 425 after satBx | Group B: 23/440 and 15/440 after satBx. | Group B (TRUSGB–TRUS G satBx): 71.5% | Group B: 94.8% before and 96.6% after satBx | 71.9% | Group B: 130 | Group B: 0 | Group B: 410 |
Group B: 30 | Group B: 100% | Group B: 93.2% | ||||
Radtke (2015) [46] | 51 | Patient | ≥2/5: 80 ≥3: 103 ≥4: 138 = 5: 142 |
≥2/5: 18 ≥3/5: 38 ≥4/5: 78 = 5/5: 126 |
≥2/5: 132 ≥3/5: 112 ≥4/5: 72 = 5/5: 24 |
≥2/5: 64 ≥3/5: 41 ≥4/5: 6 = 5/5: 2 |
≥2/5: 81.6% ≥ 3/5: 73.1% ≥ 4/5: 63.9% = 5/5: 53% |
≥2/5: 67.4% ≥ 3/5: 73.2% ≥ 4/5: 92.3% = 5/5: 92.3% |
GS ≥ 7 | 29.3% | ≥2/5: 91 ≥3/5: 124 ≥4/5: 183 = 5/5: 203 |
≥2/5: 7 ≥3/5: 17 ≥4/5: 33 = 5/5: 65 |
≥2/5: 79 ≥3/5: 69 ≥4/5: 53 = 5/5: 21 |
≥2/5: 117 ≥3/5: 84 ≥4/5: 25 = 5/5: 5 |
≥2/5: 92.2% ≥3/5: 87.9% ≥4/5: 84.7% = 5/5: 75.8% |
≥2/5: 40.3% ≥3/5: 45.1% ≥4/5: 68% = 5/5: 80.7% |
Itatani (2014) [27] | 13 | Patient | 168 | 25 | NR | NR | 87% | NR | (1) PSAd ≥ 0.1 or GP 4/5 or ≥ 3/6 pos cores; max CCL < 50% (2) PSAd ≥ 0.15 or GP 4/5 or max core length invasion < 3 mm (min 6 cores) |
NR | NR | NR | NR | NR | NR | NR |
Porpiglia (2014) [44] | 30.6 | Patient | 107 | 5 | 47 | 11 | 95.5% | 81% | NR | NR | NR | NR | NR | NR | NR | NR |
Thompson (2014) [56] | 61.3 | Patient | 35 | 16 | 76 | 23 | 68.6% | 76.7% | Moderate or high risk Moderate risk: GS 7 (GP4 >5%) and <50% of positive cores or GS 6–7 (GP4 ≤ 5%) and either ≥30% of positive cores or max core length invasion ≥8 mm High risk: GS ≥ 7 (GP4 > 5%); ≥50% + cores or GS ≥ 8 |
34% | 49 | 2 | 49 | 50 | 96% | 49.5% |
Pokorny (2014) [43] | 63.7 | Patient | ≥3/5: 56 ≥4/5: 74 |
≥3/5: 25 ≥4/5: 40 |
≥3/5: 101 ≥4/5: 86 |
≥3/5: 41 ≥4/5: 23 |
≥3/5: 69.1% ≥4/5: 64.9% |
≥3/5: 71.1% ≥4/5: 78.9% |
NR | NR | NR | NR | NR | NR | NR | NR |
Petrillo (2014) [42] | 18.4 | Patient | 56 | 4 | 21 | 55 | 93% | 28% | NR | NR | NR | NR | NR | NR | NR | NR |
Javali (2014) [29] | 16.4 | Patient | 49 | 1 | 22 | 68 | 98% | 24.4% | NR | NR | NR | NR | NR | NR | NR | NR |
Abd-Alazeez (2014) [13] | 54.7 | Lobe | ≥3/5: 33 | ≥3/5: 14 | ≥3/5: 127 | ≥3/5: 84 | ≥3/5: 70% | ≥3/5: 60% | Def 1: GS ≥ 4 + 3 and/or max CCL ≥ 6 mm Def 2: GS ≥ 3 + 4 and/or max CCL ≥ 4 mm Def 3: GS ≥ 4 + 3 Def 4: GS ≥ 3 + 4 Def 5: max CCL ≥ 6 mm Def 6: max CCL ≥ 4 mm |
Def 1: NR Def 2: 44.2% Def 3: 23.2% Def 4: 36% Def 5: 32.9% Def 6: 39.5% |
Def 1: 46 Def 2: 42 Def 3: 47 Def 4: 43 Def 5: 46 Def 6: 43 |
Def 1: 1 Def 2: 5 Def 3: 0 Def 4: 4 Def 5: 1 Def 6: 4 |
Def 1: 45 Def 2: 72 Def 3: 13 Def 4: 50 Def 5: 39 Def 6: 59 |
Def 1: 166 Def2: 139 Def 3: 198 Def 4: 161 Def 5: 172 Def 6: 152 |
Def 1: 98 Def 2: 89 Def 3: 100 Def 4: 92 Def 5: 98 Def 6: 91 |
Def 1: 21 Def 2: 34 Deg 3: 6 Def 4: 24 Def 5: 19 Def 6: 28 |
≥4/5: 87 | ≥3/5: 62 | ≥3/5: 79 | ≥3/5: 30 | ≥3/5: 58% | ≥3/5: 73% | Def 1: 140 Def 2: 124 Def 3: 148 Def 4: 133 Def 5: 141 Def 6: 131 |
Def 1: 9 Def 2: 25 Def 3: 1 Def 4: 16 Def 5: 8 Def 6: 18 |
Def 1: 37 Def 2: 52 Def 3: 12 Def 4: 38 Def 5: 32 Def 6: 45 |
Def 1: 72 Def 2: 57 Def 3: 97 Def 4: 71 Def 5: 77 Def 6: 64 |
Def 1: 94 Def 2: 83 Def 3: 99 Def 4: 89 Def 5: 95 Def 6: 88 |
Def 1: 34 Def 2: 48 Def 3: 11 Def 4: 35 Def 5: 30 Def 6: 42 |
|||||
Abd-Alazeez (2014) [12] | 47.2 | Lobe | ≥3/5: 26 | ≥3/5: 13 | ≥3/5: 38 | ≥3/5: 31 | ≥3/5: 66% | ≥3/5: 55% | Def 1: GS ≥ 4 + 3 and/or max CCL ≥ 6 mm Def 2: GS ≥ 3 + 4 and/or max CCL ≥ 4 mm Def 3: GS ≥ 4 + 3 Def 4: GS ≥ 3 + 4 Def 5: max CCL ≥ 6 mm Def 6: max CCL ≥ 4 mm |
Def 1: 18.5% Def 2: 31.5% Def 3: 4.6% Def 4: 21.3% Def 5: 16.7% Def 6: 25% |
Def 1: 37 Def 2: 31 Def 3: 39 Def 4: 36 Def 5: 37 Def 6: 32 |
Def 1: 2 Def 2: 8 Def 3: 0 Def 4: 3 Def 5: 2 Def 6: 7 |
Def 1: 18 Def 2: 26 Def 3: 5 Def 4: 20 Def 5: 16 Def 6: 20 |
Def 1: 51 Def 2: 43 Def 3: 64 Def 4: 49 Def 5: 53 Def 6: 49 |
Def 1: 95 Def 2: 79 Def 3: 100 Def 4: 92 Def 5: 95 Def 6: 82 |
Def 1: 26 Def 2: 38 Def 3: 7 Def 4: 29 Def 5: 23 Def 6: 29 |
≥4/5: 49 | ≥4/5: 25 | ≥4/5: 26 | ≥4/5: 8 | ≥4/5: 66% | ≥4/5: 76% | Def 1: 70 Def 2: 63 Def 3: 73 Def 4: 68 Def 5: 70 Def 6: 64 |
Def 1: 4 Def 2: 11 Def 3: 1 Def 4: 6 Def 5: 4 Def 6: 10 |
Def 1: 16 Def 2: 23 Def 3: 4 Def 4: 17 Def 5: 14 Def 6: 17 |
Def 1: 18; Def 2: 11 Def 3: 30 Def 4: 17 Def 5: 20 Def 6: 17 |
Def 1: 94 Def 2: 85 Def 3: 99 Def 4: 92 Def 5: 94 Def 6: 86 |
Def 1: 47 Def 2: 67 Def 3: 12 Def 4: 50 Def 5: 41 Def 6: 49 |
|||||
Matsuoka (2014) [37] | 64.8 | Lobe | 46 | 49 | 149 | 26 | 48.4% | 85.1% | NR | NR | NR | NR | NR | NR | NR | NR |
Junker (2013) [30] | 53.4 | Patient | ≥10/15: 21 ≥11/15: 28 |
≥10/15: 4 ≥11/15: 12 |
≥10/15: 35 ≥11/15: 27 |
≥10/15: 13 ≥11/15: 6 |
≥10/15: 84% ≥11/15: 70% |
≥10/15: 72.9% ≥11/15: 81.8% |
GS ≥ 4 + 3 | 13.7% | ≥13: 54 | ≥13: 2 | ≥13: 8 | ≥13: 9 | ≥13: 96.4% | ≥13: 47% |
Busetto (2013) [16] | 41.7 | Patient | 59 | 7 | 61 | 36 | 89% | 63% | NR | NR | NR | NR | NR | NR | NR | NR |
Rais-Bahrami (2013) [47] | 54.2 | Patient | ≥2/4 : 80 | ≥2/4: 275 | ≥2/4: 187 | ≥2/4: 275 | ≥2/4: 66% | ≥2/4: 59% | GS ≥ 7: GS ≥ 8 |
31.7% | NR | NR | NR | NR | GS ≥ 7: 91% GS ≥ 8: 91% |
GS ≥ 7: 38% GS ≥ 8: 18% |
≥3/4: 251 | ≥3/4: 76 | ≥3/4: 16 | ≥3/4: 76 | ≥3/4: 51% | ≥3/4: 82% | NR | NR | NR | NR | GS ≥ 7: 75% GS ≥ 8: 91% |
GS ≥ 7: 67% GS ≥ 8: 41% |
|||||
Kuru (2013) [34] | 57.6 | Patient | 80 | 14 | 67 | 186 | 85.1% | 73.5% | NR | NR | NR | NR | NR | NR | NR | NR |
Ferda (2013) [20] | 51.2 | Patient | 52 | 2 | 82 | 28 | 96.3% | 74.5% | NR | NR | NR | NR | NR | NR | NR | NR |
Ganie (2013) [21] | 74.7 | Patient | 13 | 3 | 62 | 9 | 59.1% | 95.4% | NR | NR | NR | NR | NR | NR | NR | NR |
Vinet (2013) [57] | 49.3 | Patient | ≥3/5: 11 | ≥3/5: 6 | ≥3/5: 28 | ≥3/5: 24 | ≥3/5: 64.7% | ≥3/5: 53.8% | NR | NR | NR | NR | NR | NR | NR | NR |
≥4/5: 22 | ≥4/5: 11 | ≥4/5: 23 | ≥4/5: 13 | ≥4/5: 66.7% | ≥4/5: 63.8% | NR | NR | NR | NR | NR | NR | NR | NR | |||
Numao (2013) [38] | 45 | Patient | 137 | 57 | 101 | 56 | 70.6% | 64.3% | Def 1: GS ≥4 + 3 and/or ≥20% positive cores and/or max CCL ≥5 mm Def 2: GS ≥ 3 + 4 and/or ≥20% + cores and/or max CCL ≥5 mm Def 3: GS ≥ 3 + 4 and/or ≥20% + cores |
Def 1: 33.3% Def 2:37.8% Def 3: 35.8% |
Def 1: 74 Def 2: 65 Def 3: 69 |
Def 1: 83 Def 2: 92 Def 3: 88 |
Def 1: 160 Def 2: 153 Def 3: 156 |
Def 1: 34 Def 2: 41 Def 3: 38 |
Def 1: 82.4% Def 2: 78.8% Def 3: 80.4% |
Def 1: 58.8% Def 2: 58.5% Def 3: 56% |
Belas (2012) [14] | 53.5 | Patient | 22 | 12 | 23 | 13 | 64.7% | 63.8% | NR | NR | NR | NR | NR | NR | NR | NR |
Ibrahiem (2012) [26] | 73.9 | Patient | 14 | 11 | 57 | 10 | 56% | 85.1% | NR | NR | NR | NR | NR | NR | NR | NR |
Sciarra (2012) [51] | 34.5 | Patient | 41 | 4 | 25 | 14 | 91.1% | 64.1% | NR | NR | NR | NR | NR | NR | NR | NR |
Portalez (2012) [45] | 48.1 | Lesion | Likert: 357 | Likert: 50 | Likert: 81 | Likert: 50 | Likert: 95% | Likert: 38% | Max CCL >3 mm and/or GG 4/5 | NR | NR | NR | NR | NR | NR | NR |
PI-RADS: 404 | PI-RADS: 47 | PI-RADS: 34 | PI-RADS: 47 | PI-RADS: 95% | PI-RADS: 58% | |||||||||||
Watanabe (2012) [59] | 48.1 | Patient | 485 | 73 | 624 | 266 | 86.9% | 70.1% | NR | NR | NR | NR | NR | NR | NR | NR |
Tamada (2011) [54] | 70 | Patient | 12 | 6 | 29 | 3 | 67% | 91% | NR | NR | NR | NR | NR | NR | NR | NR |
Region | 277 | 48 | 55 | 20 | 85% | 73% | ||||||||||
Choi (2011) [18] | 70.6 | Patient | 9 | 5 | 31 | 6 | 64.2% | 75.7% | NR | NR | NR | NR | NR | NR | NR | NR |
Iwazawa (2011) [28] | 40.5 | Region | 887 | 86 | 232 | 219 | 91.1% | 51.4% | NR | NR | NR | NR | NR | NR | NR | NR |
Rouse (2011) [48] | 33.7 | Sextant | 145 | 11 | 74 | 22 | 92.9% | 77.1% | GS ≥ 7: Def 1: ≥3 mm Def 2: ≥5 mm |
Def 1: 26.6% Def 2: 26.2% |
Def 1: 153 Def 2: 153 |
Def 1: 3 Def 2: 3 |
Def 1: 64 Def 1: 63 |
Def 1: 32 Def 2: 33 |
Def 1: 98.1% Def 2: 98.1% |
Def 1: 68.1% Def 2: 67% |
59.6 | Patient | 24 | 14 | 54 | 22 | 63.2% | 71.1% | Def 1: 41.2% Def 2: 36.8% |
Def 1: 30 Def 2: 31 |
Def 1: 4 Def 2: 3 |
Def 1: 43 Def 2: 39 |
Def 1: 4 Def 2: 3 |
Def 1: 88.2% Def 2: 91.2% |
Def 1: 53.8% Def 2: 48.8% |
||
Haffner (2011) [23] | 54.4 | Patient | 154 | 50 | 240 | 111 | 75.4% | 68.3% | NR | NR | NR | NR | NR | NR | NR | NR |
Panebianco (2010) [40] | 42.7 | Patient | NR | NR | NR | NR | 95.1% | 88.2% | NR | NR | NR | NR | NR | NR | NR | NR |
Roy (2010) [49] | 55.9 | Patient | NR | NR | NR | NR | 71% | 75% | NR | NR | NR | NR | NR | NR | NR | NR |
Testa (2010) [55] | 40.7 | Patient | NR | NR | NR | NR | 79.3% | 64% | NR | NR | NR | NR | NR | NR | NR | NR |
Sciarra (2010) [52] | 50 | Patient | 61 | 4 | 66 | 9 | 93.8% | 88% | NR | NR | NR | NR | NR | NR | NR | NR |
Kitajima (2010) [31] | 56.6 | Patient | 311 | 19 | 80 | 14 | 92.2% | 85.1% | NR | NR | NR | NR | NR | NR | NR | NR |
Labanaris (2010) [35] | 73.9 | Patient | 17 | 73 | 96 | 74 | 81.11% | 56.47% | NR | NR | NR | NR | NR | NR | NR | NR |
Kumar (2009) [32] | 21.7 | Patient | 39 | 3 | 10 | 8 | 92.8% | 55% | NR | NR | NR | NR | NR | NR | NR | NR |
Schmuecking (2009) [50] | NR | Lobe | NR | NR | NR | NR | 96% | 61% | NR | NR | NR | NR | NR | NR | NR | NR |
Cheikh (2009) [17] | 24.7 | Patient | 36 | 12 | 11 | 34 | 80% | 22.9% | NR | NR | NR | NR | NR | NR | NR | NR |
Cirillo (2008) [19] | 31.5 | Patient | 19 | 0 | 17 | 18 | 100% | 48.6% | NR | NR | NR | NR | NR | NR | NR | NR |
Kumar (2007) [33] | 13.3 | Patient | 39 | 0 | 11 | 33 | 100% | 25% | NR | NR | NR | NR | NR | NR | NR | NR |
Squillaci (2005) [53] | 50.8 | Patient | 29% | 8% | 25% | 3% | 89% | 80% | NR | NR | NR | NR | NR | NR | NR | NR |
Hara (2005) [24] | 41.5 | Patient | ≥2/3: 40 = 3/3: 47 |
≥2/3: 4 = 3/3: 8 |
≥2/3 30 = 3/3: 26 |
≥2/3: 8 = 3/3: 1 |
≥2/3: 90% = 3/3: 85% |
≥2/3: 78.9% = 3/3: 96.3% |
NR | NR | NR | NR | NR | NR | NR | NR |
Cancer prevalence tended to be higher and mpMRI NPV lower in the biopsy-naïve group as compared with the repeat biopsy group, in men with positive DRE as compared with men with negative DRE and when an endorectal coil was not used ( Table 3 ). There were no clear differences in the prevalence and NPV of the other analysed subgroups (TRUS-guided vs TTP biopsy, biopsy procedures with ≤16 cores vs >16 cores; Table 3 ). However, comparisons must be interpreted with care, due to the small number of studies in some subgroups. In patients with a PSA level of ≤10 ng/ml, the median NPV for overall PCa was 86.3% (IQR, 73.3–93.6%) for a median cancer prevalence of 35.4% (IQR, 27.6–42.5%).
Nb of studies | Median PCa prevalence | Median mpMRI NPV | Nb of studies | Median csPCa prevalence | Median mpMRI NPV | |
---|---|---|---|---|---|---|
Biopsy-naïve patients | 8 | 51.4% (45.5–56.7) | 69.9% (64.2–78) | 1 | 35.8% (NA) | 80.4% (NA) |
Repeat biopsy | 14 | 42% (35.1–52.6) | 82.6% (75.5–93.1) | 3 | 24.4% (19.1–32.8) | 88.2% (87.9–92.3) |
TRUS-guided biopsy | 36 | 49.7% (34.3–57.7) | 84.6% (68.6–92.8) | 4 | 28.1% (21.7–36.5) | 89.3% (82.9–92.4) |
TTP biopsy | 4 | 53.8% (47.5–57.8) | 73.6% (72–78.7) | 2 | 31.6% (30.5–32.8) | 92% (89.9–94) |
Biopsy with ≤16 cores | 28 | 48.7% (39.2–54.8) | 81.9% (66.8–89.3) | 5 | 28.1% (21.8–36.5) | 89.3% (82.9–92.4) |
Biopsy with >16 cores | 5 | 56.6% (51–61.3) | 81.1% (73.1–92.2) | 2 | 31.7% (30.5–32.8) | 92% (89.9–93.9) |
Positive DRE | 1 | 73.9% (NA) | 56% (NA) | 0 | – | – |
Negative DRE | 6 | 36% (34.6–46.8) | 82.7% (74.2–93.1) | 0 | – | – |
Endorectal coil | 17 | 41.7% (30.6–55.9) | 92.8% (79.3–95.4) | 1 | 31.7% (NA) | 91% (NA) |
No endorectal coil | 22 | 50.9% (41.7–56.1) | 77.7% (69.5–86.6) | 7 | 34% (26.9–46.1%) | 87.9% (78.2–92.1) |
Eight studies reported NPV at patient level for overall PCa and fulfilled the inclusion criteria for meta-analysis ( Table 4 ) [22 25 38 41 43 46 56 57] .
Study | Prevalence a (%) | Neg MRI (%) | NPV (%) | PPV (%) | Spe (%) | Se (%) | ||
---|---|---|---|---|---|---|---|---|
All PCa | Score ≥ 3/5 | Grenabo Bergdahl (2016) [22] | 31.3 | 66.9 | 83.7 | 47.5 | 63.2 | 73.1 |
Numao (2013) [38] | 45 | 29.4 | 70.6 | 64.3 | 71.0 | 63.9 | ||
Hauth (2015) [25] | 45.7 | 14.3 | 85.7 | 48.3 | 11.8 | 97.7 | ||
Vinet (2013) [57] | 49.3 | 24.6 | 64.7 | 53.8 | 31.4 | 82.4 | ||
Radtke (2015) [46] | 51 | 27 | 73 | 73.2 | 71.5 | 74.7 | ||
Thompson (2014) [56] | 61.3 | 31.4 | 68.6 | 76.8 | 60.3 | 82.6 | ||
Pokorny (2014) [43] | 63.7 | 30.9 | 69.1 | 82.4 | 69.1 | 82.4 | ||
Score ≥ 4/5 | Pepe (2015) [41] | 37 | 31 | 74.2 | 42 | 36.5 | 78.4% | |
Vinet (2013) [57] | 49.3 | 47.8 | 66.7 | 63.9 | 62.9 | 67.6% | ||
Radtke (2015) [46] | 51 | 73.5 | 63.9 | 92.3 | 95.8 | 48% | ||
Gleason ≥7 PCa | Score ≥ 3/5 | Radtke (2015) [46] | 29.3 | 27 | 87.9 | 45.1 | 59.6 | 80.2% |
a Prevalence of overall prostate cancers (10 first lines) or Gleason ≥7 cancers (last line).
PCa = prostate cancer; MRI = magnetic resonance imaging; Neg MRI = proportion of negative magnetic resonance imaging; NPV = negative predictive value; PPV = positive predictive value; Se = sensitivity; Spe = specificity.
Seven studies used a score of ≥3/5 for defining positive mpMRI ( Fig. 4 A and B) [22 25 38 43 46 56 57] . Fig. 4 C shows the conditional probability plot of 1 – NPV and PPV as a function of overall PCa prevalence. Table 5 shows NPV and PPV estimates for the given values of PCa prevalence.
PCaPrev | PPV | NPV |
---|---|---|
0.30 | 0.43 (0.34–0.53) | 0.88 (0.77–0.99) |
0.40 | 0.54 (0.45–0.64) | 0.82 (0.70–0.94) |
0.50 | 0.64 (0.55–0.73) | 0.76 (0.64–0.88) |
0.60 | 0.73 (0.65–0.80) | 0.67 (0.56–0.79) |
0.70 | 0.81 (0.75–0.87) | 0.57 (0.47–0.67) |
0.75 | 0.84 (0.79–0.89) | 0.51 (0.42–0.59) |
Only three studies used a score of ≥4/5 for defining positive mpMRI ( Table 4 ) [41 46 57] , and a formal meta-analysis could not be performed.
Only one study reporting NPV at patient level for Gleason ≥7 cancers met the selection criteria for inclusion in the meta-analysis. It reported NPV and PPV of 87.9% and 45.1%, respectively, for a prevalence of 29.3% ( Table 4 ) [46] .
We observed a large variability in reported NPV. Many factors, such as differences in mpMRI protocols, definition of negative mpMRI, or biopsy protocols, can explain this variability. However, two major causes of variability must be pointed out. First, the cancer prevalence was highly variable, ranging at patient level from 13% to 74.7% for overall PCa, and from 13.7% to 50.9% for csPCa. This variability was observed in both the biopsy-naïve and the repeat biopsy setting. As NPV depends on prevalence, this had a major impact on reported NPV ( Fig. 3 ). Second, the definition of csPCa was highly variable from one series to another, and differences of up to 21% could be observed in NPV when different definitions of csPCa were used in the same dataset [12 13 38 47 48] .
To account for clinical heterogeneity and to further explore the clinical relevance of the results, we carefully selected studies for inclusion in the meta-analysis based on stringent criteria. Particularly, we included only studies that: (1) had biopsy protocols with at least 10 cores, since it is no longer recommended to obtain less than 10 cores per biopsy; (2) used DWI, which is the most informative technique, at least for cancers in the peripheral zone [60] ; and (3) reported mpMRI findings using a five-level score, so that negative findings could be better defined. We accepted studies using a subjective (Likert) scale because experienced readers obtained equivalent [45 61 62] or better [63] results with the Likert score than with the PI-RADS v1 score. Owing to the large variations of NPV induced by differences in definitions of csPCa, we did not include different definitions in the meta-analysis since this would have introduced unacceptable clinical heterogeneity in the results, possibly resulting in erroneous and biased estimates. We, therefore, a priori restricted the definition of csPCa to cancers with a Gleason score of ≥7, given the low lethal potential of Gleason 6 cancers [64] and the lack of consensus among pathologists on the best method to measure biopsy core invasion length [65 66] .
In this more homogeneous group of studies, the prevalence range was still large (31.3–63.7%). As a result, we modelled the evolution of NPV (and PPV) as a function of overall PCa prevalence. Unfortunately, we could not duplicate this for csPCa since only one study reporting NPV for Gleason ≥7 cancers met the inclusion criteria for meta-analysis.
We included only studies that reported the results of systematic/standard biopsy in patients with negative mpMRI and used the systematic/standard biopsy as a reference standard. It is well known that TRUS-guided biopsy harbours both random and systematic errors, as evidenced by the high rates of positivity of immediate repeat biopsy after a first series of negative biopsies [67 68] , and as confirmed recently by the PROMIS trial [69] . Therefore, using TRUS-guided biopsy as a reference standard may have overestimated the NPV of mpMRI. However, studies using radical prostatectomy specimens as a reference standard have already reported mpMRI detection rates in relation to PCa Gleason score and volume [1] . In this review, we intended to address the more pragmatic question as to whether a negative mpMRI could predict a negative subsequent biopsy. This is an important question because if the NPV of mpMRI was sufficiently high in comparison with the reference standard of systematic/standard biopsies, then in practice a negative mpMRI result could indeed avoid the need for prostate biopsy. Therefore, studies reporting only biopsy results when the mpMRI was positive (eg, obtained through MRI-targeted, guided, or fusion biopsies with added systematic biopsies) were not included in this review.
It is now well established that mpMRI is a sensitive tool for detecting aggressive PCa 1 2 3 69] . However several reasons preclude its broad use as a triage test before biopsy.
Firstly, the population referred to prostate biopsy is not standardised. The large range of reported prevalence for overall PCa and csPCa suggests substantial heterogeneity in the way patients are selected for biopsy. Owing to this heterogeneity, we did not provide a pooled estimate for mpMRI NPV. The role of mpMRI as a triage test before prostate biopsy should be evaluated in the broader context of the selection of patients with a suspicion of (aggressive) PCa. In a recent retrospective study of 514 patients, mpMRI NPV for Gleason ≥7 cancers was 91% when the PSA density was ≤0.2 ng/ml/ml, and only 71% when the PSA density was >0.2 ng/ml/ml ( p = 0.003) [70] . In another series of 288 biopsy-naïve patients, no csPCa (Gleason score ≥7 or maximum cancer core length ≥4 mm) was found in 44 patients with a PSA density of <0.15 ng/ml/ml and a PI-RADS v2 score of <3/5 [71] . We believe that such prestratification of the risk of csPCa is an interesting way for rationalising the use of mpMRI before biopsy. Patients found at very low risk would be spared both mpMRI and biopsy. Patients at a low risk—for whom mpMRI would have an NPV high enough to be used as a triage test—could avoid biopsy in case of negative mpMRI. Patients at a higher risk would need biopsy even in case of negative mpMRI. Many tools can be used to risk stratify the population of patients referred to biopsy, ranging from simple parameters such as PSA density to more complicated risk calculators [72 73] . The impact of these tools on the NPV of prebiopsy mpMRI needs to be carefully evaluated, both in the biopsy-naïve and in the repeat biopsy setting. For the moment, it is impossible to make any recommendations on the best way to risk stratify patients before referring them for mpMRI.
Secondly, the large variability in the definition of csPCa precludes any definitive conclusion on the ability of mpMRI to rule out aggressive cancer. The issue of the most appropriate definition of csPCa on biopsy is complex, since biopsy results may accurately reflect neither tumour burden nor aggressiveness. Nonetheless, there is an urgent need to standardise the histological definition(s) of csPCa, to allow meaningful comparisons between studies.
Thirdly, the specificity of mpMRI remains moderate, and there is a substantial proportion of false positives in the lesions scored 3/5 or 4/5 [1 74 75] , even with the new PI-RADS v2 score [76] . In a series of 62 patients with 116 lesions biopsied under magnetic resonance/ultrasound fusion, the overall cancer detection rates for PI-RADS v2 scores of 3/5 and 4/5 were only 15.8% and 29.8%, respectively [77] . In theory, a triage test used to rule out a disease needs to be highly sensitive for this disease. However, if its specificity is too low, it will be clinically useless since most patients will be positive, whether they have the disease or not. Therefore, if mpMRI is to be used as a triage test in the future, there is a need to improve its specificity. This could be achieved by a continuous refinement of scores [78] . Promising results in characterising csPCa have also been reported with a quantitative analysis [79] .
Finally, all published studies were conducted in specialised centres. The broad use of mpMRI as a triage test assumes good interobserver reproducibility. Unfortunately, interobserver reproducibility of existing scoring systems remains moderate [62 63 80] even with the use of the PI-RADS v2 score [80 81] . Studies evaluating on a large scale the reproducibility of mpMRI findings between expert and nonexpert centres are currently lacking.
Three systematic reviews (including two meta-analyses) regarding the role of mpMRI in localised PCa have been published recently 4 5 6 . Crucially, all three reviews focused exclusively on the sensitivity of mpMRI-targeted, guided, or fusion biopsies in diagnosing overall PCa and csPCa, using TRUS-guided prostate biopsies as reference standards. The impact of systematic biopsies on the outcome was not addressed in any of the reviews, within either the index test or the reference standard. Our review had a totally different research question and objective, focusing on NPV of mpMRI to see if a negative mpMRI can avoid the need for a prostate biopsy. As MRI-targeted/guided/fusion biopsies are not relevant if the mpMRI was negative for cancer, it can be argued that the three reviews assessed a different index test altogether. As such, we believe that the findings of this review are novel and unique, and pave the way for further focused clinical studies.
The current study represents the first systematic review addressing the role of mpMRI as a triage test before biopsy. The review elements were developed in conjunction with a multidisciplinary panel of experts (EAU Prostate Cancer Guidelines Panel), which included a patient representative, and the review was performed robustly in accordance with recognised standards. However, it is limited by the major heterogeneity of the existing literature in patient population, study design, and definitions of positive mpMRI and csPCa. It highlighted further areas of research that could help in defining the best use of mpMRI in the early detection of aggressive PCa in the future.
Although mpMRI can detect aggressive PCa with excellent sensitivity, a definitive conclusion on its role as a triage test before prostate biopsy will be possible only when three main issues are addressed. Firstly, because NPV depends on prevalence, and because overall PCa and csPCa prevalence was highly variable in the published series, it becomes mandatory to define the optimal way to pre-evaluate the risk of csPCa in patients with a suspicion of PCa. Depending on the risk category, mpMRI could then be used to obviate biopsies or not. Secondly, there is a need for consensus definitions of csPCa on biopsy findings to allow interstudy comparisons. Thirdly, although efforts have been made to standardise mpMRI technical protocols and interpretation in the past few years [11 60 76] , there is still a crucial need to improve mpMRI specificity and inter-reader reproducibility.
This systematic review was performed under the auspices of:
The European Association of Urology Guidelines Office Board
The European Association of Urology Prostate Cancer Guideline Panel
Author contributions: Olivier Rouvière had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.
Study concept and design: Rouvière, Mottet, Cornford.
Acquisition of data: Rouvière, Moldovan, Van den Broeck, Yuan.
Analysis and interpretation of data: Rouvière, Moldovan, Van den Broeck, Lam.
Drafting of the manuscript: Rouvière, Moldovan, Van den Broeck, Lam.
Critical revision of the manuscript for important intellectual content: Bellmunt, van den Bergh, Bolla, Briers, Van den Broeck, Cornford, Cumberbatch, De Santis, Fossati, Gross, Henry, Joniau, Lam, Matveev, Moldovan, van der Poel, van der Kwast, Rouvière, Schoots, Wiegel, Mottet.
Statistical analysis: None.
Obtaining funding: None.
Administrative, technical, or material support: Yuan, Sylvester, Marconi.
Supervision: None.
Other: None.
Financial disclosures: Olivier Rouvière certifies that all conflicts of interest, including specific financial interests and relationships and affiliations relevant to the subject matter or materials discussed in the manuscript (eg, employment/affiliation, grants or funding, consultancies, honoraria, stock ownership or options, expert testimony, royalties, or patents filed, received, or pending), are the following: Bellmunt is a company consultant for Janssen, Astellas, Pierre Fabre, Genentech, Merck, Ipsen, Pfizer, Novartis, and Sanofi Aventis. He has received research support from Takeda, Novartis, and Sanofi, and received travel grants from Pfizer and Pierre Fabre. Bolla has received company speaker honoraria from Ipsen and Astellas, honoraria or consultation fees from Janssen, and fellowship and travel grants from Janssen, AstraZeneca, and Astellas. Briers has received grant and research support from Ipsen, European Association of Urology, and Bayer; is an ex officio board member for Europa UOMO; is an ethics committee and advisory group member for REQUITE; is a member patient advisory board member for PAGMI; and is a member of SCA and EMA PCWP. Cornford is a company consultant for Astellas, Ipsen, and Ferring. He receives company speaker honoraria from Astellas, Janssen, Ipsen, and Pfizer; participates in trials from Ferring; and receives fellowships and travel grants from Astellas and Janssen. De Santis is a company consultant for GlaxoSmithKline, Janssen, Bayer, Novartis, Pierre Fabre, Astellas, Amgen, Eisai Inc., ESSA, Merck, and Synthon; has received company speaker honoraria from Pfizer, Takeda, Sanofi Aventis, Shionogi, Celgene, and Teva OncoGenex; has participated in trials for Pierre Fabre, Astellas, Exelixis, Bayer, and Roche; has received fellowship and travel grants from Bayer, Novartis, Ferring, Astellas, Sanofi Aventis, and Janssen; has received grant and research support from Pierre Fabre; has received honoraria from AstraZeneca; and is associated with Amgen. Joniau is a company consultant for Astellas, Ipsen, Bayer, Sanofi, and Janssen; has received company speaker honoraria from Astellas, Amgen, Bayer, Sanofi, Janssen, and Ipsen; has participated in trials for Astellas, Janssen, and Bayer; has received fellowship and travel grants from Astellas, Amgen, Bayer, Sanofi, Janssen, Ipsen, and Pfizer; and has received grant and research support from Astellas, Bayer, and Janssen. Matveev has received company speaker honoraria from Sanofi and Astellas, has participated in trials for Astellas, Pfizer and Novartis. Lam is a company consultant for and has received company speaker honoraria from Pfizer, GSK, Astellas, and Ipsen. van der Poel is a company consultant for Intuitive Surgical, has participated in trials for Astellas and Steba Biotech, and has received grant and research support from Astellas. Rouvière is a company consultant for EDAP-TMS, Bracco, and Philips; has received company speaker honoraria from EDAP-TMS, Bracco, and Philips; and has participated in trials for EDAP-TMS and Bracco. Wiegel has received company speaker honoraria from Astellas, Takeda, Hexal, Ipsen, Janssen-Cilac, and Ferring. Mottet has received grant and research support from Takeda Pharmaceutical, Millenium, Astellas, Pierre Fabre, Sanofi, and Pasteur, and has received honoraria or consultation fees from Takeda Pharaceutical, Millenium, Jansen, Astellas, BMS, Bayer, Ipsen, Ferring, Novartis, Nuclétron, Pierre Fabre, Sanofi, and Zeneca. van den Bergh, Van den Broeck, Cumberbatch, Fossati, Gross, Henry, van der Kwast, Sylvester, Yuan, Schoots, Moldovan, and Marconi have nothing to disclose.
Funding/Support and role of the sponsor: None.
A correlation with radical prostatectomy specimens has demonstrated that multiparametric magnetic resonance imaging (mpMRI) has excellent sensitivity in detecting prostate cancer (PCa) with a Gleason score of ≥7 1 2 3 . As a result, prostate mpMRI is increasingly used in patients with a suspicion of PCa to localise abnormal areas before biopsy. A large body of literature has shown that targeted biopsies of suspicious lesions seen on mpMRI (TBx) improved the detection of clinically significant PCa (csPCa), at least in the repeat biopsy setting 4 5 6 . As a result, it is now recommended that an mpMRI is performed before repeat biopsy to allow TBx of suspicious lesions in addition to standard biopsies [7] .
Some authors have recently suggested that, besides improving csPCa detection, mpMRI could also be used as a triage test so that patients with negative mpMRI findings could obviate biopsy. Such a strategy remains highly controversial [8] and depends upon the negative predictive value (NPV) of mpMRI. Therefore, the European Association of Urology Prostate Cancer Guidelines Panel undertook this systematic review and meta-analysis to assess the NPV of mpMRI in patients with a suspicion of PCa and, thus, its potential role in eliminating unnecessary prostate biopsy.
Our primary aim was to systematically evaluate the performance of negative prebiopsy prostate mpMRI in predicting a negative biopsy result for overall PCa and csPCa in biopsy-naïve men and in men with previously negative biopsies. A further objective was to explore and define factors that may contribute to relevant thresholds in order to provide guidance for future studies.
The review was performed according to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) statement [9] . The review protocol was published in PROSPERO database ( http://www.crd.york.ac.uk/PROSPERO; registration number CRD42015021929). Databases searched included the Embase and OVID Medline databases, the Cochrane database of systematic reviews, and the Cochrane Central Register for Clinical Trials, covering from January 1, 2000 to February 13, 2016. Systematic or standard prostate biopsies were used as reference standards, with positive or negative cases of PCa being determined by histopathological examination. The detailed search strategy is presented in Supplement 1.
Included studies focused on men who were assessed for suspected PCa by mpMRI before undergoing prostate biopsy. Studies enrolling both biopsy-naïve men and men who had undergone previous negative biopsies were included. Prebiopsy prostate mpMRI was considered the index test and comprised T2-weighted imaging (T2WI) and at least one functional imaging technique (diffusion-weighted imaging [DWI], dynamic contrast-enhanced imaging [DCEI], or magnetic resonance spectroscopic imaging [MRSI]). For inclusion, studies had to report on false negatives and true negatives, in order to calculate NPV (ie, results of systematic/standard prostate biopsies when the mpMRI was negative). When available, false positive and true positive findings were also noted to calculate the positive predictive value (PPV) and the cancer prevalence. There was restriction neither on the biopsy technique (transrectal or transperineal) nor on the number of biopsy cores. Studies using radical prostatectomy specimens as reference standards were excluded, as were studies evaluating men with histologically proven PCa. Studies with less than 50 participants were excluded. No language restrictions were applied.
Two reviewers (P.C.M. and T.V.D.B.) independently screened all abstracts and full-text articles for eligibility. Disagreement was resolved by consensus or reference to an independent third party (L.M.). All screening was performed using a predefined eligibility form.
Using a data extraction form developed a priori, the same two reviewers independently extracted data concerning study methodology, patient characteristics, technical characteristics of the MR scanners, mpMRI protocol, mpMRI scoring system, definition of positive mpMRI, biopsy protocol, and definition of csPCa. Any discrepancies concerning data extraction were resolved by consensus or reference to an independent arbiter (O.R. or T.B.L.).
To assess the risk of bias (RoB), all included reports were reviewed using the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool for diagnostic accuracy studies [10] .
Outcome data regarding false negative and true negative values of mpMRI before prostate biopsy were recorded as reported by authors. When not available, data were indirectly derived from specificity, sensitivity, and prevalence values reported by authors using an online Bayesian statistics calculator ( http://www.medcalc.com/bayes.html ). Descriptive statistics were used to summarise baseline characteristics and outcomes, including median and interquartile range (IQR) for estimates of NPV across studies. A correlation between mpMRI NPV and a positive biopsy rate was established using the Pearson's correlation coefficient.
A meta-analysis was undertaken to calculate pooled NPV and PPV. To ensure appropriate clinical homogeneity of the studies included in the meta-analysis, we selected only the studies enrolling biopsy-naïve patients and/or patients with a history of negative biopsy, and fulfilling the following criteria that were defined a priori: (1) reference standard consisting of prostate biopsy with at least 10 samples on all patients; (2) mpMRI protocol comprising at least T2WI and DWI; (3) mpMRI results presented as a five-level score, using a subjective Likert scale or the Prostate Imaging Reporting Data System (PI-RADS) score [11] ; (4) definition of positive mpMRI as a score ≥3/5 or ≥4/5; and (5) results reported on a per patient basis. In addition, only studies defining csPCa as Gleason ≥7 cancers were selected for the meta-analysis assessing the mpMRI NPV for csPCa. A bivariate random-effects approach was employed using the Midas package in Stata 12 (StataCorp LP, College Station, TX, USA). Since the NPV decreases and the PPV increases as the prevalence increases, post-test probability estimates of NPV and PPV were reported for the given values of the prevalence based on Bayes’ theorem.
For other studies not included in the meta-analysis based on the criteria described above, a narrative synthesis of the data was performed. To explore and define clinical heterogeneity, subgroups were analysed at patient level based on the following variables: biopsy-naïve versus previous negative biopsy; patients with positive versus negative digital rectal examination (DRE); mpMRI performed with an endorectal versus without an endorectal coil; transrectal ultrasound (TRUS) versus template transperineal (TTP) biopsy approach; and ≤16 cores versus >16 cores as the reference standard. Studies reporting mpMRI NPV for patients with a prostate-specific antigen (PSA) level of ≤10 ng/ml were also reported separately.
The study selection process is depicted in the PRISMA flow diagram ( Fig. 1 ). A total of 2980 abstracts were retrieved. After abstract screening and removal of duplicates, 240 articles were eligible for full text screening, of which 48 studies were eligible for inclusion 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 .
Out of the 48 included studies, 42 were single-centre and six were multicentre studies. Thirty-four studies were prospective and six were retrospective, whilst the design of the rest was unclear. RoB assessment using QUADAS-2 was performed for each of the individual studies ( Fig. 2 A and B). Overall, the RoB was highly heterogeneous across studies for all criteria, except for the reference standard domain, in which RoB was low in most studies.
The 48 studies comprised a total of 9613 men who underwent prostate mpMRI followed by biopsy. The study and patient baseline characteristics are presented in Table 1 . The patient population consisted of biopsy-naive men in nine studies, men with at least one previous negative biopsy in 16 studies, and both biopsy-naïve men and men with a history of previous negative biopsy in nine studies. In 14 studies, the biopsy history of the patients was unclear.
Study | Study design | Period | Population | Pt Nb | Mean/median* age (yr) | Mean/median* PSA (ng/ml) | Mean/median* prostate volume (cm 3 ) | Magnetic field strength | MR pulse sequences | Endorectal coil | MR score | Definition of positive MRI | Reference standard |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Hauth (2015) [25] | Prospective | 2011–2013 | FB | 94 | 64 (43–83) | 9 (3–31) | 51 (17–140) | 1.5 T | T2WI/DWI/DCEI/MRSI | No | PI-RADS v1 | ≥3 | 11–13-core TRUS SBx + TBx |
Lamb (2015) [36] | Retrospective | 2013–2013 | FB & PNB | 173 | NR | NR | NR | 1.5 T | T2WI/DWI | NR | NR | NR | 12-core TRUS SBx |
Brock (2015) [15] | Prospective | 2013–2014 | PNB | 168 | 64* (IQR 59–70) | 9.2* (IQR 6.7–13.4) | 55.4* (IQR 42–80) | 3 T | T2WI/DWI/DCEI | No | PI-RADS v1 | NR | 12/24-core TRUS SBx + TBx |
Grenabo Bergdahl (2016) [22] | Prospective | 2013–2014 | FB & PNB | 83 | 69.3* (IQR 69–69.6) | 1.6* (IQR 0.9–2.7) | NR | 3 T | T2WI/DWI/DCEI/MRSI | No | PI-RADS v1 | ≥3 | 10-core TRUS SBx + TBx |
Wang (2015) [58] | Prospective | 2002–2009 | FB & PNB | 586 | 70 (26–91) | 11.11* (0.02–9794) | NR | 1.5 T | T2WI/DWI/DCEI/MRSI | Yes | PI-RADS v1 | ≥3 | TRUS SBx |
Pepe (2015) [41] | Prospective | 2011–2014 | PNB | 100 | 64* | 8.6* (4.2–10) | NR | 3 T | T2WI/DWI/DCEI/MRSI | No | PI-RADS v1 | ≥4 | TPBx + TBx |
Panebianco (2015) [39] | Prospective | 2011–2014 | FB (61.62%) & PNB (38.34%) | 925 (1140 total cohort) |
NR | NR | NR | 3 T | T2WI/DWI/DCEI | Yes | PI-RADS v1 | NR | 14-core TRUS SBx; 45-core sat TPBx + TBx |
Radtke (2015) [46] | Prospective | 2013–2013 | FB (63.3%) & PNB (36.7%) | 294 | 64* (60–71) | 7.3 (6.0) | 47 (37.5) | 3 T | T2WI/DWI/DCEI | No | PI-RADS v1 | PI-RADS ≥2; PI-RADS ≥3; PI-RADS ≥4; PI-RADS = 5; |
24-core TPBx + TBx |
Itatani (2014) [27] | Retrospective | 2004–2007 | NR | 193 | 68.9 (8.4); 70* (47–89) | 11.8 (15.9); 7.9* (1.22–159) | NR | 1.5 T | T2WI/DWI/DCEI | No | 1–5 scale (Likert) | ≥3 | 12–14-core TRUS SBx |
Porpiglia (2014) [44] | Prospective | 2011–2013 | PNB | 170 | 65* (60–70) | 6.9* (5.2–9.8) | 42* (36–48) | 1.5 T | T2WI/DWI/DCEI | Yes | Dichotomous | Positive: at least 2/3 MR seq. with suspicious findings | 18–24-core TRUS SBx (volume dependent) |
Thompson (2014) [56] | Prospective | 2012–2013 | FB (88%) & PNB (12%) | 150 | 62.4* (IQR 55.0–66.4) | 5.6* (IQR 4.5–7.5) | 40* (IQR 30–57) | 1.5 T (47%) & 3 T (53%) | T2WI/DWI/DCEI | No | PI-RADS v1 | ≥3 | Median of 30 TPBx (volume dependent) |
Pokorny (2014) [43] | Prospective | 2012–2013 | FB | 223 | 63* (IQR 57–68) | 5.3* (IQR 4.1–6.6) | 41* (IQR 30–59) | 3 T | T2WI/DWI/DCEI | No | PI-RADS v1 | ≥3 (primary); ≥4 |
12-core TRUS SBx + TBx |
Petrillo (2014) [42] | Prospective | 2009–2010 | NR | 136 | NR | NR | NR | 1.5 T | T2WI/DWI/MRSI | Yes | 1–5 scale (Likert) | ≥3 | 12–16-core TRUS SBx (volume + PSA dependent) |
Javali (2014) [29] | Retrospective | 2002–2011 | NR | 140 | Control: 62.4 (10.5); Study: 62.9 (12.1) | Control: 6.8 (2.3); Study: 6.87 (2.6) | Control: 44 (14.2); Study: 43 (18.4) | 1.5 T | T2WI/MRSI | Yes | Dichotomous | Cit/[Cho + Cr] < 1.2 | 6-core TRUS SBx ( n = 69), 12-core TRUS SBx ( n = 119) |
Abd-Alazeez (2014) [13] | Prospective | 2007–2011 | FB | 129 | 62* (41–82) | 5.8* (1.2–20) | 40* (16–137) | 1.5 & 3 T | T2WI/DWI/DCEI | No | PI-RADS v1 | ≥3 (primary); ≥4 |
20-core TPBx |
Abd-Alazeez (2014) [12] | Retrospective | NR | PNB | 54 | 64* (39–75) | 10* (2–23) | 53* (19–136) | 1.5 & 3 T | T2WI/DWI/DCEI | No | PI-RADS v1 | ≥3 (primary); ≥4 |
≥20-core TPBx + TBx ( n = 15) |
Matsuoka (2014) [37] | Prospective | 2007–2012 | NR | 135 | 67* (50–80) | 7.0* (2.9–19.8) | 25.4* (12.7–90.2) | 1.5 T | T2WI/DWI | No | 1–5 scale (Likert) | ≥3 | 14-core TRUS SBX |
Junker (2013) [30] | Retrospective | 2011–2013 | PNB | 73 | 62 (7.4) | 7.0* (5.1–12.9) | 45* (34–61) | 3 T | T2WI/DWI/DCEI | No | PI-RADS | PI-RADS ≥10 and ≥11 for all PCa PI-RADS ≥13 for significant PCa |
10-core TRUS SBx + TBx |
Busetto (2013) [16] | Prospective | 2010–2012 | PNB | 163 | 66.4 (5.3) | 6.8 (1.6) | NR | 3 T | T2WI/DWI/DCEI/MRSI | Yes | NR | NR | 10-core TRUS SBx + TBx |
Rais-Bahrami (2013) [47] | Prospective | 2007–2012 | NR | 583 | 61.3 (8.4) | 9.9 (13.1) | NR | 3 T | T2WI/DWI/DCEI/MRSI | Yes | 1–4 scale (Likert) | ≥2 ≥3 |
12-core TRUS SBx + TBx |
Kuru (2013) [34] | Prospective | 2010–2011 | FB (51%) & PNB (49%) | 347 | 65.3 (42–82) | 9.85 (0.5–104) | 48.7 (9–180) | 3 T | T2WI/DWI/DCEI | No | 1–3 scale (Likert) | ≥2 | 12–36-core TRUS SBx (volume dependent) + TBx |
Ferda (2013) [20] | Prospective | NR | NR | 164 | (49–74) | (4.2–123) | NR | 3 T | T2WI/DWI/DCEI/MRSI | No | NR | In house | TRUS SBx |
Ganie (2013) [21] | NR | 2007–2009 | PNB | 87 | NR | NR | NR | 1.5 T | T2WI/MRSI | Yes | MRSI Cho/Cit ratio | In house | 6 core TRUS SBx + MRI TBx |
Vinet (2013) [57] | Prospective | 2009–2011 | FB | 69 | NR | 5.2* (3.2–28) | NR | 1.5 T (35 pts) & 3 T (34 pts) | T2WI/DWI/DCEI | No | 1–5 scale (Likert) | ≥3 | 12-core TRUS SBx + TBx |
Numao (2013) [38] | Prospective | 2006–2010 | FB | 351 | 65* (59–70) | 6.3* (4.9–9.1) | 32* (24–42) | 1.5 T | T2WI/DWI/DCEI (no DCEI in 42 pts) | No | 1–5 scale (Likert) | ≥3 | 3D 26-core (12 TRUS SBx + 14 TPBx – 203 pts); 3D 14-core (6 TRUS SBx + 8 TPBx – 102 pts); TPBx 14 core (46 pts) |
Belas (2012) [14] | Prospective | 2010–2011 | FB | 71 | 66* (47–76) | 7* (4–10) | 45* (15–150) | 1.5 T | T2WI/DWI/DCEI | No | TZ: 0–4 scale PZ: 0–10 scale |
TZ: >2 PZ: >6 |
12-core TRUS SBx + TBx |
Ibrahiem (2012) [26] | Prospective | 2008–2009 | FB | 100 | 65.03 (7.13) | 26.3 (24.2) | 60.09 (28.7) | 1.5 T | T2WI/DWI | No | NR | In house | 12-core TRUS SBX |
Sciarra (2012) [51] | Prospective | 2008–2011 | PNB | 84 | 64.09 (46–76) | 7.07 (4.2–15.5) | NR | 3 T | T2WI/DWI/DCEI/MRSI | Yes | NR | NR | 10-core TRUS Bx + TBx |
Portalez (2012) [45] | Prospective | 2011 | PNB | 129 | 64.7 (47–79) | 9.6 (2.7–40) | 51.1 (12–192) | 1.5 T | T2WI/DWI/DCEI | Mixed | 1–5 scale (Likert) PI-RADS |
Likert ≥3 PI-RADS ≥9 |
10–12-core TRUS SBx + TBx |
Watanabe (2012) [59] | Prospective | 2004–2008 | NR | 1448 | 72 (7.5) | NR | NR | 1.5 T | T2WI/DWI | No | NR | ADC value ≤1.35 × 10 −3 mm 2 /s | 8-core TRUS SBx + TBx |
Tamada (2011) [54] | Retrospective | 2006–2009 | NR | 50 | 70 (40–84) | 6.84* (4.06–9.94) | NR | 1.5 T | T2WI/DWI/DCEI | No | NR | In house | 12-core TRUS SBx |
Choi (2011) [18] | NR | 2009–2010 | NR | 51 | 67.16 (56–90) | 14.16 (1.02–38.9) | 42.98 (13.8–77.3) | 3 T | T2WI/DWI | NR | NR | NR | 10–12-core TRUS SBx + TBx |
Iwazawa (2011) [28] | Retrospective | 2008–2009 | NR | 178 | 68.8 (41–86) | 20.51 (4.04–568.5) | NR | 1.5 T | T2WI/DWI/DCEI | NR | 1–4 scale (Likert) | NR | 10–12-core TRUS SBx (TBx included in SBx chart) |
Rouse (2011) [48] | Prospective | 2005–2007 | PNB | 114 | 63.6 (41–83) | 13.4 (0–228) | NR | 1.5 T | T2WI/DWI/DCEI | NR | 1–5 scale (Likert) | ≥3 | TRUS SBx |
Haffner (2011) [23] | Prospective | 2005–2009 | FB | 555 | 64* (47–83) | 6.75* (0.18–100) | 46* (15–200) | 1.5 T | T2WI/DCEI | No | 1–5 scale (Likert) | ≥3 | 10-core TRUS SBx + TBx |
Panebianco (2010) [40] | Prospective | 2007–2009 | PNB | 150 | 61.2 (46–78) | 9.42 (3.91) | 41.17 (7.47) | 1.5 T | T2WI/DCEI/MRSI | Yes | NR | In house | 10-core TRUS SBx (TBx included in SBx chart) |
Roy (2010) [49] | Not specified | 2011–2009 | FB (53%) & PNB (47%) | 103 | 63 (52–78) | 7* | NR | 3 T | T2WI/DWI/DCEI | Yes | NR | NR | 8-core TRUS SBx + TBx |
Testa (2010) [55] | Not specified | 2007 | PNB | 54 | 63.9 (52–76) | 11.4 (3–42) | 59.3 (30–150) | 1.5 T | T2WI/MRSI | Yes | 1–3 scale (Likert) | ≥2 | 12-core TRUS SBx + TBx |
Sciarra (2010) [52] | Prospective | 2007–2009 | PNB | 110 | 63.5 (49–74) | NR | NR | 1.5 T | T2WI/DCEI/MRSI | Yes | NR | In house | 10-core TRUS SBx + TBx |
Kitajima (2010) [31] | Prospective | 2008–2009 | NR | 53 | 69* (56–84) | 11.1* (4.2–112.1) | NR | 3 T | T2WI/DWI/DCEI | No | 1–5 scale (Likert) | ≥3 | 20-core TPBx |
Labanaris (2010) [35] | Prospective | 2004–2008 | PNB | 260 | NR | NR | NR | 1 T | T2WI/DWI/DCEI | Yes | Dichotomous | In house | 18-core TRUS SBx |
Kumar (2009) [32] | NR | NR | NR | 61 | 65.3 (9.3) | 16.5 (0.21–155) | NR | 1.5 T | T2WI/MRSI | Yes | NR | (Cit/(Cho + Cr) ≤ 1.2 | TRUS Bx |
Schmuecking (2009) [50] | NR | NR | FB & PNB | 67 | 68 | 11.5 | NR | 1.5 T | T2WI/DCEI | No | NR | NR | 20-core Bx |
Cheikh (2009) [17] | Retrospective | 2005–2008 | PNB | 93 | 63.2 (52–74) | 9.63 (1.6–40) | NR | 1.5 T | T2WI/DCEI | No | Dichotomous | In house | 12-core TRUS SBx + TBx |
Cirillo (2008) [19] | Prospective | 2004–2006 | PNB | 54 | 65.5 (5.2) | 10.8 (7.5) | NR | 1.5 T | T2WI/MRSI | Yes | Dichotomous | In house | 10-core TRUS SBx + TBx |
Kumar (2007) [33] | Prospective | 2003–2005 | NR | 83 | NR | NR | NR | 1.5 T | T2WI/MRSI | Yes | NR | NR | 12-core TRUS SBx + TBx |
Squillaci (2005) [53] | Prospective | 2004–2005 | NR | 65 | NR | NR | NR | 1.5 T | T2WI/DCEI/MRSI | No | 1–3 scale (Likert) | ≥2 | 10-core TRUS SBx + TBx |
Hara (2005) [24] | Prospective | 2003–2004 | FB | 90 | 67.2 (NR) | NR | NR | 1.5 T | T2WI/DCEI | No | 1–3 scale (Likert) | ≥2 = 3 |
14-core TRUS SBx |
The magnetic field strength was 1, 1.5, and 3 T in one, 28, and 15 studies, respectively. Four studies used both 1.5 and 3 T MR systems. DWI and DCEI were used in 36 and 35 studies, respectively. Nineteen studies also added MRSI. An endorectal coil was used in 18 studies. The definition of positive mpMRI varied across studies. The PI-RADS v1 score was used in 12 studies, a five-level subjective (Likert) score was used in eight studies, and one study reported data based on the two scoring systems. In-house criteria were used in 13 studies for defining positive mpMRI, and five studies used a dichotomous definition. Nine studies did not report on the criteria for positive mpMRI. No study used the PI-RADS v2 score.
Regarding the reference standard, TRUS-guided biopsies were used in 39 studies, TTP biopsies in six studies, and mixed TRUS-guided and TTP biopsies in two studies. In one study, the biopsy approach was unclear. The number of cores per biopsy procedure was ≤16 in 30 studies, >16 in nine studies, and variable among patients in three studies. For six studies, the number of biopsy cores taken was unclear.
At patient level, the median biopsy positivity rate (ie, cancer prevalence) was 50.4% (IQR, 36.4–57.7%) for overall cancer and 32.9% (IQR, 28.1–37.2%) for csPCa ( Table 2 ). The median mpMRI NPV was 82.4% (IQR, 69.0–92.4%) for overall cancer and 88.1% (IQR, 85.7–92.3) for csPCa. NPV significantly decreased when cancer prevalence increased, both for overall cancer ( r = –0.64, p < 0.0001) and csPCa ( r = –0.75, p = 0.032; Fig. 3 ). In addition, NPV was highly dependent on the definition used for csPCa, with differences of up to 21% when several definitions were used in the same dataset [12 13 38 47 48] .
Study | Overall PCa prevalence (%) | Reporting level | Multiparametric MRI performance for PCa detection | Definition of csPCa | csPCa prevalence | Multiparametric MRI performance for csPCa detection | ||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
TN | FN | TP | FP | NPV | PPV | TN | FN | TP | FP | NPV | PPV | |||||
Hauth (2015) [25] | 45.7 | Patient | 6 | 1 | 42 | 45 | 85.7% | 48.3% | Low grade: GS ≤ 6 High grade: GS ≥ 7 |
NR | NR | NR | NR | NR | NR | NR |
Lesion | 59 | 13 | 55 | 73 | 81.9% | 43% | ||||||||||
Lamb (2015) [36] | 65.9 | Patient | 23 | 22 | 92 | 36 | 51.1% | 71.9% | GS ≥ 7 | 50.9% | 31 | 14 | 71 | 57 | 68.9% | 55.5% |
Brock (2015) [15] | 42.3 | Patient | 17 | 7 | 56 | 88 | 70.8% | SBx: 38.8% TBx: 22.2% Duo: 44.4% |
Epstein: GS > 6 and/or max CCL ≥50% | 24.4% | SBx: 21 | SBx: 3 | SBx: 38 TBx: 27 duo: 47 |
SBx: 106 TBx: 117 duo: 97 |
87.5% | SBx: 26.4% TBx: 18.8% duo: 32.6% |
Grenabo Bergdahl (2016) [22] | 33.7 | Patient | 36 | 7 | 19 | 21 | 83.7% | 47.5% | Clinically insignificant PCa: T1c, PSAd < 0.15, GS < 7, ≤2 positive cores, and unilateral cancer | NR | NR | NR | NR | NR | NR | NR |
Wang (2015) [58] | 58 | Patient | 165 | 8 | 332 | 81 | 95.4% | 80.4% | NR | NR | NR | NR | NR | NR | NR | NR |
Pepe (2015) [41] | 37 | Patient | 23 | 8 | 29 | 40 | 74.2% | 42% | GS ≥ 7 or GS 6 with CCL ≥ 50% | NR | NR | NR | NR | NR | 100% | 55.8% |
Panebianco (2015) [39] | 74.7 | Patient | Group A (satBx): 104 | Group A (satBx): 43 | Group A: 186 | Group A: 22 | Group A (satBx): 70.7% | Group A: 89.4% | NR | 60% | Group A: 147 | Group A: 0 | Group A: 183 | Group A: 25 | Group A: 100% | Group A: 88% |
Group B (TRUSGB NR TRUS G satBx): 93 | Group B (TRUSGB NR TRUS G satBx): 37 | Group B: 417 before and 425 after satBx | Group B: 23/440 and 15/440 after satBx. | Group B (TRUSGB–TRUS G satBx): 71.5% | Group B: 94.8% before and 96.6% after satBx | 71.9% | Group B: 130 | Group B: 0 | Group B: 410 |
Group B: 30 | Group B: 100% | Group B: 93.2% | ||||
Radtke (2015) [46] | 51 | Patient | ≥2/5: 80 ≥3: 103 ≥4: 138 = 5: 142 |
≥2/5: 18 ≥3/5: 38 ≥4/5: 78 = 5/5: 126 |
≥2/5: 132 ≥3/5: 112 ≥4/5: 72 = 5/5: 24 |
≥2/5: 64 ≥3/5: 41 ≥4/5: 6 = 5/5: 2 |
≥2/5: 81.6% ≥ 3/5: 73.1% ≥ 4/5: 63.9% = 5/5: 53% |
≥2/5: 67.4% ≥ 3/5: 73.2% ≥ 4/5: 92.3% = 5/5: 92.3% |
GS ≥ 7 | 29.3% | ≥2/5: 91 ≥3/5: 124 ≥4/5: 183 = 5/5: 203 |
≥2/5: 7 ≥3/5: 17 ≥4/5: 33 = 5/5: 65 |
≥2/5: 79 ≥3/5: 69 ≥4/5: 53 = 5/5: 21 |
≥2/5: 117 ≥3/5: 84 ≥4/5: 25 = 5/5: 5 |
≥2/5: 92.2% ≥3/5: 87.9% ≥4/5: 84.7% = 5/5: 75.8% |
≥2/5: 40.3% ≥3/5: 45.1% ≥4/5: 68% = 5/5: 80.7% |
Itatani (2014) [27] | 13 | Patient | 168 | 25 | NR | NR | 87% | NR | (1) PSAd ≥ 0.1 or GP 4/5 or ≥ 3/6 pos cores; max CCL < 50% (2) PSAd ≥ 0.15 or GP 4/5 or max core length invasion < 3 mm (min 6 cores) |
NR | NR | NR | NR | NR | NR | NR |
Porpiglia (2014) [44] | 30.6 | Patient | 107 | 5 | 47 | 11 | 95.5% | 81% | NR | NR | NR | NR | NR | NR | NR | NR |
Thompson (2014) [56] | 61.3 | Patient | 35 | 16 | 76 | 23 | 68.6% | 76.7% | Moderate or high risk Moderate risk: GS 7 (GP4 >5%) and <50% of positive cores or GS 6–7 (GP4 ≤ 5%) and either ≥30% of positive cores or max core length invasion ≥8 mm High risk: GS ≥ 7 (GP4 > 5%); ≥50% + cores or GS ≥ 8 |
34% | 49 | 2 | 49 | 50 | 96% | 49.5% |
Pokorny (2014) [43] | 63.7 | Patient | ≥3/5: 56 ≥4/5: 74 |
≥3/5: 25 ≥4/5: 40 |
≥3/5: 101 ≥4/5: 86 |
≥3/5: 41 ≥4/5: 23 |
≥3/5: 69.1% ≥4/5: 64.9% |
≥3/5: 71.1% ≥4/5: 78.9% |
NR | NR | NR | NR | NR | NR | NR | NR |
Petrillo (2014) [42] | 18.4 | Patient | 56 | 4 | 21 | 55 | 93% | 28% | NR | NR | NR | NR | NR | NR | NR | NR |
Javali (2014) [29] | 16.4 | Patient | 49 | 1 | 22 | 68 | 98% | 24.4% | NR | NR | NR | NR | NR | NR | NR | NR |
Abd-Alazeez (2014) [13] | 54.7 | Lobe | ≥3/5: 33 | ≥3/5: 14 | ≥3/5: 127 | ≥3/5: 84 | ≥3/5: 70% | ≥3/5: 60% | Def 1: GS ≥ 4 + 3 and/or max CCL ≥ 6 mm Def 2: GS ≥ 3 + 4 and/or max CCL ≥ 4 mm Def 3: GS ≥ 4 + 3 Def 4: GS ≥ 3 + 4 Def 5: max CCL ≥ 6 mm Def 6: max CCL ≥ 4 mm |
Def 1: NR Def 2: 44.2% Def 3: 23.2% Def 4: 36% Def 5: 32.9% Def 6: 39.5% |
Def 1: 46 Def 2: 42 Def 3: 47 Def 4: 43 Def 5: 46 Def 6: 43 |
Def 1: 1 Def 2: 5 Def 3: 0 Def 4: 4 Def 5: 1 Def 6: 4 |
Def 1: 45 Def 2: 72 Def 3: 13 Def 4: 50 Def 5: 39 Def 6: 59 |
Def 1: 166 Def2: 139 Def 3: 198 Def 4: 161 Def 5: 172 Def 6: 152 |
Def 1: 98 Def 2: 89 Def 3: 100 Def 4: 92 Def 5: 98 Def 6: 91 |
Def 1: 21 Def 2: 34 Deg 3: 6 Def 4: 24 Def 5: 19 Def 6: 28 |
≥4/5: 87 | ≥3/5: 62 | ≥3/5: 79 | ≥3/5: 30 | ≥3/5: 58% | ≥3/5: 73% | Def 1: 140 Def 2: 124 Def 3: 148 Def 4: 133 Def 5: 141 Def 6: 131 |
Def 1: 9 Def 2: 25 Def 3: 1 Def 4: 16 Def 5: 8 Def 6: 18 |
Def 1: 37 Def 2: 52 Def 3: 12 Def 4: 38 Def 5: 32 Def 6: 45 |
Def 1: 72 Def 2: 57 Def 3: 97 Def 4: 71 Def 5: 77 Def 6: 64 |
Def 1: 94 Def 2: 83 Def 3: 99 Def 4: 89 Def 5: 95 Def 6: 88 |
Def 1: 34 Def 2: 48 Def 3: 11 Def 4: 35 Def 5: 30 Def 6: 42 |
|||||
Abd-Alazeez (2014) [12] | 47.2 | Lobe | ≥3/5: 26 | ≥3/5: 13 | ≥3/5: 38 | ≥3/5: 31 | ≥3/5: 66% | ≥3/5: 55% | Def 1: GS ≥ 4 + 3 and/or max CCL ≥ 6 mm Def 2: GS ≥ 3 + 4 and/or max CCL ≥ 4 mm Def 3: GS ≥ 4 + 3 Def 4: GS ≥ 3 + 4 Def 5: max CCL ≥ 6 mm Def 6: max CCL ≥ 4 mm |
Def 1: 18.5% Def 2: 31.5% Def 3: 4.6% Def 4: 21.3% Def 5: 16.7% Def 6: 25% |
Def 1: 37 Def 2: 31 Def 3: 39 Def 4: 36 Def 5: 37 Def 6: 32 |
Def 1: 2 Def 2: 8 Def 3: 0 Def 4: 3 Def 5: 2 Def 6: 7 |
Def 1: 18 Def 2: 26 Def 3: 5 Def 4: 20 Def 5: 16 Def 6: 20 |
Def 1: 51 Def 2: 43 Def 3: 64 Def 4: 49 Def 5: 53 Def 6: 49 |
Def 1: 95 Def 2: 79 Def 3: 100 Def 4: 92 Def 5: 95 Def 6: 82 |
Def 1: 26 Def 2: 38 Def 3: 7 Def 4: 29 Def 5: 23 Def 6: 29 |
≥4/5: 49 | ≥4/5: 25 | ≥4/5: 26 | ≥4/5: 8 | ≥4/5: 66% | ≥4/5: 76% | Def 1: 70 Def 2: 63 Def 3: 73 Def 4: 68 Def 5: 70 Def 6: 64 |
Def 1: 4 Def 2: 11 Def 3: 1 Def 4: 6 Def 5: 4 Def 6: 10 |
Def 1: 16 Def 2: 23 Def 3: 4 Def 4: 17 Def 5: 14 Def 6: 17 |
Def 1: 18; Def 2: 11 Def 3: 30 Def 4: 17 Def 5: 20 Def 6: 17 |
Def 1: 94 Def 2: 85 Def 3: 99 Def 4: 92 Def 5: 94 Def 6: 86 |
Def 1: 47 Def 2: 67 Def 3: 12 Def 4: 50 Def 5: 41 Def 6: 49 |
|||||
Matsuoka (2014) [37] | 64.8 | Lobe | 46 | 49 | 149 | 26 | 48.4% | 85.1% | NR | NR | NR | NR | NR | NR | NR | NR |
Junker (2013) [30] | 53.4 | Patient | ≥10/15: 21 ≥11/15: 28 |
≥10/15: 4 ≥11/15: 12 |
≥10/15: 35 ≥11/15: 27 |
≥10/15: 13 ≥11/15: 6 |
≥10/15: 84% ≥11/15: 70% |
≥10/15: 72.9% ≥11/15: 81.8% |
GS ≥ 4 + 3 | 13.7% | ≥13: 54 | ≥13: 2 | ≥13: 8 | ≥13: 9 | ≥13: 96.4% | ≥13: 47% |
Busetto (2013) [16] | 41.7 | Patient | 59 | 7 | 61 | 36 | 89% | 63% | NR | NR | NR | NR | NR | NR | NR | NR |
Rais-Bahrami (2013) [47] | 54.2 | Patient | ≥2/4 : 80 | ≥2/4: 275 | ≥2/4: 187 | ≥2/4: 275 | ≥2/4: 66% | ≥2/4: 59% | GS ≥ 7: GS ≥ 8 |
31.7% | NR | NR | NR | NR | GS ≥ 7: 91% GS ≥ 8: 91% |
GS ≥ 7: 38% GS ≥ 8: 18% |
≥3/4: 251 | ≥3/4: 76 | ≥3/4: 16 | ≥3/4: 76 | ≥3/4: 51% | ≥3/4: 82% | NR | NR | NR | NR | GS ≥ 7: 75% GS ≥ 8: 91% |
GS ≥ 7: 67% GS ≥ 8: 41% |
|||||
Kuru (2013) [34] | 57.6 | Patient | 80 | 14 | 67 | 186 | 85.1% | 73.5% | NR | NR | NR | NR | NR | NR | NR | NR |
Ferda (2013) [20] | 51.2 | Patient | 52 | 2 | 82 | 28 | 96.3% | 74.5% | NR | NR | NR | NR | NR | NR | NR | NR |
Ganie (2013) [21] | 74.7 | Patient | 13 | 3 | 62 | 9 | 59.1% | 95.4% | NR | NR | NR | NR | NR | NR | NR | NR |
Vinet (2013) [57] | 49.3 | Patient | ≥3/5: 11 | ≥3/5: 6 | ≥3/5: 28 | ≥3/5: 24 | ≥3/5: 64.7% | ≥3/5: 53.8% | NR | NR | NR | NR | NR | NR | NR | NR |
≥4/5: 22 | ≥4/5: 11 | ≥4/5: 23 | ≥4/5: 13 | ≥4/5: 66.7% | ≥4/5: 63.8% | NR | NR | NR | NR | NR | NR | NR | NR | |||
Numao (2013) [38] | 45 | Patient | 137 | 57 | 101 | 56 | 70.6% | 64.3% | Def 1: GS ≥4 + 3 and/or ≥20% positive cores and/or max CCL ≥5 mm Def 2: GS ≥ 3 + 4 and/or ≥20% + cores and/or max CCL ≥5 mm Def 3: GS ≥ 3 + 4 and/or ≥20% + cores |
Def 1: 33.3% Def 2:37.8% Def 3: 35.8% |
Def 1: 74 Def 2: 65 Def 3: 69 |
Def 1: 83 Def 2: 92 Def 3: 88 |
Def 1: 160 Def 2: 153 Def 3: 156 |
Def 1: 34 Def 2: 41 Def 3: 38 |
Def 1: 82.4% Def 2: 78.8% Def 3: 80.4% |
Def 1: 58.8% Def 2: 58.5% Def 3: 56% |
Belas (2012) [14] | 53.5 | Patient | 22 | 12 | 23 | 13 | 64.7% | 63.8% | NR | NR | NR | NR | NR | NR | NR | NR |
Ibrahiem (2012) [26] | 73.9 | Patient | 14 | 11 | 57 | 10 | 56% | 85.1% | NR | NR | NR | NR | NR | NR | NR | NR |
Sciarra (2012) [51] | 34.5 | Patient | 41 | 4 | 25 | 14 | 91.1% | 64.1% | NR | NR | NR | NR | NR | NR | NR | NR |
Portalez (2012) [45] | 48.1 | Lesion | Likert: 357 | Likert: 50 | Likert: 81 | Likert: 50 | Likert: 95% | Likert: 38% | Max CCL >3 mm and/or GG 4/5 | NR | NR | NR | NR | NR | NR | NR |
PI-RADS: 404 | PI-RADS: 47 | PI-RADS: 34 | PI-RADS: 47 | PI-RADS: 95% | PI-RADS: 58% | |||||||||||
Watanabe (2012) [59] | 48.1 | Patient | 485 | 73 | 624 | 266 | 86.9% | 70.1% | NR | NR | NR | NR | NR | NR | NR | NR |
Tamada (2011) [54] | 70 | Patient | 12 | 6 | 29 | 3 | 67% | 91% | NR | NR | NR | NR | NR | NR | NR | NR |
Region | 277 | 48 | 55 | 20 | 85% | 73% | ||||||||||
Choi (2011) [18] | 70.6 | Patient | 9 | 5 | 31 | 6 | 64.2% | 75.7% | NR | NR | NR | NR | NR | NR | NR | NR |
Iwazawa (2011) [28] | 40.5 | Region | 887 | 86 | 232 | 219 | 91.1% | 51.4% | NR | NR | NR | NR | NR | NR | NR | NR |
Rouse (2011) [48] | 33.7 | Sextant | 145 | 11 | 74 | 22 | 92.9% | 77.1% | GS ≥ 7: Def 1: ≥3 mm Def 2: ≥5 mm |
Def 1: 26.6% Def 2: 26.2% |
Def 1: 153 Def 2: 153 |
Def 1: 3 Def 2: 3 |
Def 1: 64 Def 1: 63 |
Def 1: 32 Def 2: 33 |
Def 1: 98.1% Def 2: 98.1% |
Def 1: 68.1% Def 2: 67% |
59.6 | Patient | 24 | 14 | 54 | 22 | 63.2% | 71.1% | Def 1: 41.2% Def 2: 36.8% |
Def 1: 30 Def 2: 31 |
Def 1: 4 Def 2: 3 |
Def 1: 43 Def 2: 39 |
Def 1: 4 Def 2: 3 |
Def 1: 88.2% Def 2: 91.2% |
Def 1: 53.8% Def 2: 48.8% |
||
Haffner (2011) [23] | 54.4 | Patient | 154 | 50 | 240 | 111 | 75.4% | 68.3% | NR | NR | NR | NR | NR | NR | NR | NR |
Panebianco (2010) [40] | 42.7 | Patient | NR | NR | NR | NR | 95.1% | 88.2% | NR | NR | NR | NR | NR | NR | NR | NR |
Roy (2010) [49] | 55.9 | Patient | NR | NR | NR | NR | 71% | 75% | NR | NR | NR | NR | NR | NR | NR | NR |
Testa (2010) [55] | 40.7 | Patient | NR | NR | NR | NR | 79.3% | 64% | NR | NR | NR | NR | NR | NR | NR | NR |
Sciarra (2010) [52] | 50 | Patient | 61 | 4 | 66 | 9 | 93.8% | 88% | NR | NR | NR | NR | NR | NR | NR | NR |
Kitajima (2010) [31] | 56.6 | Patient | 311 | 19 | 80 | 14 | 92.2% | 85.1% | NR | NR | NR | NR | NR | NR | NR | NR |
Labanaris (2010) [35] | 73.9 | Patient | 17 | 73 | 96 | 74 | 81.11% | 56.47% | NR | NR | NR | NR | NR | NR | NR | NR |
Kumar (2009) [32] | 21.7 | Patient | 39 | 3 | 10 | 8 | 92.8% | 55% | NR | NR | NR | NR | NR | NR | NR | NR |
Schmuecking (2009) [50] | NR | Lobe | NR | NR | NR | NR | 96% | 61% | NR | NR | NR | NR | NR | NR | NR | NR |
Cheikh (2009) [17] | 24.7 | Patient | 36 | 12 | 11 | 34 | 80% | 22.9% | NR | NR | NR | NR | NR | NR | NR | NR |
Cirillo (2008) [19] | 31.5 | Patient | 19 | 0 | 17 | 18 | 100% | 48.6% | NR | NR | NR | NR | NR | NR | NR | NR |
Kumar (2007) [33] | 13.3 | Patient | 39 | 0 | 11 | 33 | 100% | 25% | NR | NR | NR | NR | NR | NR | NR | NR |
Squillaci (2005) [53] | 50.8 | Patient | 29% | 8% | 25% | 3% | 89% | 80% | NR | NR | NR | NR | NR | NR | NR | NR |
Hara (2005) [24] | 41.5 | Patient | ≥2/3: 40 = 3/3: 47 |
≥2/3: 4 = 3/3: 8 |
≥2/3 30 = 3/3: 26 |
≥2/3: 8 = 3/3: 1 |
≥2/3: 90% = 3/3: 85% |
≥2/3: 78.9% = 3/3: 96.3% |
NR | NR | NR | NR | NR | NR | NR | NR |
Cancer prevalence tended to be higher and mpMRI NPV lower in the biopsy-naïve group as compared with the repeat biopsy group, in men with positive DRE as compared with men with negative DRE and when an endorectal coil was not used ( Table 3 ). There were no clear differences in the prevalence and NPV of the other analysed subgroups (TRUS-guided vs TTP biopsy, biopsy procedures with ≤16 cores vs >16 cores; Table 3 ). However, comparisons must be interpreted with care, due to the small number of studies in some subgroups. In patients with a PSA level of ≤10 ng/ml, the median NPV for overall PCa was 86.3% (IQR, 73.3–93.6%) for a median cancer prevalence of 35.4% (IQR, 27.6–42.5%).
Nb of studies | Median PCa prevalence | Median mpMRI NPV | Nb of studies | Median csPCa prevalence | Median mpMRI NPV | |
---|---|---|---|---|---|---|
Biopsy-naïve patients | 8 | 51.4% (45.5–56.7) | 69.9% (64.2–78) | 1 | 35.8% (NA) | 80.4% (NA) |
Repeat biopsy | 14 | 42% (35.1–52.6) | 82.6% (75.5–93.1) | 3 | 24.4% (19.1–32.8) | 88.2% (87.9–92.3) |
TRUS-guided biopsy | 36 | 49.7% (34.3–57.7) | 84.6% (68.6–92.8) | 4 | 28.1% (21.7–36.5) | 89.3% (82.9–92.4) |
TTP biopsy | 4 | 53.8% (47.5–57.8) | 73.6% (72–78.7) | 2 | 31.6% (30.5–32.8) | 92% (89.9–94) |
Biopsy with ≤16 cores | 28 | 48.7% (39.2–54.8) | 81.9% (66.8–89.3) | 5 | 28.1% (21.8–36.5) | 89.3% (82.9–92.4) |
Biopsy with >16 cores | 5 | 56.6% (51–61.3) | 81.1% (73.1–92.2) | 2 | 31.7% (30.5–32.8) | 92% (89.9–93.9) |
Positive DRE | 1 | 73.9% (NA) | 56% (NA) | 0 | – | – |
Negative DRE | 6 | 36% (34.6–46.8) | 82.7% (74.2–93.1) | 0 | – | – |
Endorectal coil | 17 | 41.7% (30.6–55.9) | 92.8% (79.3–95.4) | 1 | 31.7% (NA) | 91% (NA) |
No endorectal coil | 22 | 50.9% (41.7–56.1) | 77.7% (69.5–86.6) | 7 | 34% (26.9–46.1%) | 87.9% (78.2–92.1) |
Eight studies reported NPV at patient level for overall PCa and fulfilled the inclusion criteria for meta-analysis ( Table 4 ) [22 25 38 41 43 46 56 57] .
Study | Prevalence a (%) | Neg MRI (%) | NPV (%) | PPV (%) | Spe (%) | Se (%) | ||
---|---|---|---|---|---|---|---|---|
All PCa | Score ≥ 3/5 | Grenabo Bergdahl (2016) [22] | 31.3 | 66.9 | 83.7 | 47.5 | 63.2 | 73.1 |
Numao (2013) [38] | 45 | 29.4 | 70.6 | 64.3 | 71.0 | 63.9 | ||
Hauth (2015) [25] | 45.7 | 14.3 | 85.7 | 48.3 | 11.8 | 97.7 | ||
Vinet (2013) [57] | 49.3 | 24.6 | 64.7 | 53.8 | 31.4 | 82.4 | ||
Radtke (2015) [46] | 51 | 27 | 73 | 73.2 | 71.5 | 74.7 | ||
Thompson (2014) [56] | 61.3 | 31.4 | 68.6 | 76.8 | 60.3 | 82.6 | ||
Pokorny (2014) [43] | 63.7 | 30.9 | 69.1 | 82.4 | 69.1 | 82.4 | ||
Score ≥ 4/5 | Pepe (2015) [41] | 37 | 31 | 74.2 | 42 | 36.5 | 78.4% | |
Vinet (2013) [57] | 49.3 | 47.8 | 66.7 | 63.9 | 62.9 | 67.6% | ||
Radtke (2015) [46] | 51 | 73.5 | 63.9 | 92.3 | 95.8 | 48% | ||
Gleason ≥7 PCa | Score ≥ 3/5 | Radtke (2015) [46] | 29.3 | 27 | 87.9 | 45.1 | 59.6 | 80.2% |
a Prevalence of overall prostate cancers (10 first lines) or Gleason ≥7 cancers (last line).
PCa = prostate cancer; MRI = magnetic resonance imaging; Neg MRI = proportion of negative magnetic resonance imaging; NPV = negative predictive value; PPV = positive predictive value; Se = sensitivity; Spe = specificity.
Seven studies used a score of ≥3/5 for defining positive mpMRI ( Fig. 4 A and B) [22 25 38 43 46 56 57] . Fig. 4 C shows the conditional probability plot of 1 – NPV and PPV as a function of overall PCa prevalence. Table 5 shows NPV and PPV estimates for the given values of PCa prevalence.
PCaPrev | PPV | NPV |
---|---|---|
0.30 | 0.43 (0.34–0.53) | 0.88 (0.77–0.99) |
0.40 | 0.54 (0.45–0.64) | 0.82 (0.70–0.94) |
0.50 | 0.64 (0.55–0.73) | 0.76 (0.64–0.88) |
0.60 | 0.73 (0.65–0.80) | 0.67 (0.56–0.79) |
0.70 | 0.81 (0.75–0.87) | 0.57 (0.47–0.67) |
0.75 | 0.84 (0.79–0.89) | 0.51 (0.42–0.59) |
Only three studies used a score of ≥4/5 for defining positive mpMRI ( Table 4 ) [41 46 57] , and a formal meta-analysis could not be performed.
Only one study reporting NPV at patient level for Gleason ≥7 cancers met the selection criteria for inclusion in the meta-analysis. It reported NPV and PPV of 87.9% and 45.1%, respectively, for a prevalence of 29.3% ( Table 4 ) [46] .
We observed a large variability in reported NPV. Many factors, such as differences in mpMRI protocols, definition of negative mpMRI, or biopsy protocols, can explain this variability. However, two major causes of variability must be pointed out. First, the cancer prevalence was highly variable, ranging at patient level from 13% to 74.7% for overall PCa, and from 13.7% to 50.9% for csPCa. This variability was observed in both the biopsy-naïve and the repeat biopsy setting. As NPV depends on prevalence, this had a major impact on reported NPV ( Fig. 3 ). Second, the definition of csPCa was highly variable from one series to another, and differences of up to 21% could be observed in NPV when different definitions of csPCa were used in the same dataset [12 13 38 47 48] .
To account for clinical heterogeneity and to further explore the clinical relevance of the results, we carefully selected studies for inclusion in the meta-analysis based on stringent criteria. Particularly, we included only studies that: (1) had biopsy protocols with at least 10 cores, since it is no longer recommended to obtain less than 10 cores per biopsy; (2) used DWI, which is the most informative technique, at least for cancers in the peripheral zone [60] ; and (3) reported mpMRI findings using a five-level score, so that negative findings could be better defined. We accepted studies using a subjective (Likert) scale because experienced readers obtained equivalent [45 61 62] or better [63] results with the Likert score than with the PI-RADS v1 score. Owing to the large variations of NPV induced by differences in definitions of csPCa, we did not include different definitions in the meta-analysis since this would have introduced unacceptable clinical heterogeneity in the results, possibly resulting in erroneous and biased estimates. We, therefore, a priori restricted the definition of csPCa to cancers with a Gleason score of ≥7, given the low lethal potential of Gleason 6 cancers [64] and the lack of consensus among pathologists on the best method to measure biopsy core invasion length [65 66] .
In this more homogeneous group of studies, the prevalence range was still large (31.3–63.7%). As a result, we modelled the evolution of NPV (and PPV) as a function of overall PCa prevalence. Unfortunately, we could not duplicate this for csPCa since only one study reporting NPV for Gleason ≥7 cancers met the inclusion criteria for meta-analysis.
We included only studies that reported the results of systematic/standard biopsy in patients with negative mpMRI and used the systematic/standard biopsy as a reference standard. It is well known that TRUS-guided biopsy harbours both random and systematic errors, as evidenced by the high rates of positivity of immediate repeat biopsy after a first series of negative biopsies [67 68] , and as confirmed recently by the PROMIS trial [69] . Therefore, using TRUS-guided biopsy as a reference standard may have overestimated the NPV of mpMRI. However, studies using radical prostatectomy specimens as a reference standard have already reported mpMRI detection rates in relation to PCa Gleason score and volume [1] . In this review, we intended to address the more pragmatic question as to whether a negative mpMRI could predict a negative subsequent biopsy. This is an important question because if the NPV of mpMRI was sufficiently high in comparison with the reference standard of systematic/standard biopsies, then in practice a negative mpMRI result could indeed avoid the need for prostate biopsy. Therefore, studies reporting only biopsy results when the mpMRI was positive (eg, obtained through MRI-targeted, guided, or fusion biopsies with added systematic biopsies) were not included in this review.
It is now well established that mpMRI is a sensitive tool for detecting aggressive PCa 1 2 3 69] . However several reasons preclude its broad use as a triage test before biopsy.
Firstly, the population referred to prostate biopsy is not standardised. The large range of reported prevalence for overall PCa and csPCa suggests substantial heterogeneity in the way patients are selected for biopsy. Owing to this heterogeneity, we did not provide a pooled estimate for mpMRI NPV. The role of mpMRI as a triage test before prostate biopsy should be evaluated in the broader context of the selection of patients with a suspicion of (aggressive) PCa. In a recent retrospective study of 514 patients, mpMRI NPV for Gleason ≥7 cancers was 91% when the PSA density was ≤0.2 ng/ml/ml, and only 71% when the PSA density was >0.2 ng/ml/ml ( p = 0.003) [70] . In another series of 288 biopsy-naïve patients, no csPCa (Gleason score ≥7 or maximum cancer core length ≥4 mm) was found in 44 patients with a PSA density of <0.15 ng/ml/ml and a PI-RADS v2 score of <3/5 [71] . We believe that such prestratification of the risk of csPCa is an interesting way for rationalising the use of mpMRI before biopsy. Patients found at very low risk would be spared both mpMRI and biopsy. Patients at a low risk—for whom mpMRI would have an NPV high enough to be used as a triage test—could avoid biopsy in case of negative mpMRI. Patients at a higher risk would need biopsy even in case of negative mpMRI. Many tools can be used to risk stratify the population of patients referred to biopsy, ranging from simple parameters such as PSA density to more complicated risk calculators [72 73] . The impact of these tools on the NPV of prebiopsy mpMRI needs to be carefully evaluated, both in the biopsy-naïve and in the repeat biopsy setting. For the moment, it is impossible to make any recommendations on the best way to risk stratify patients before referring them for mpMRI.
Secondly, the large variability in the definition of csPCa precludes any definitive conclusion on the ability of mpMRI to rule out aggressive cancer. The issue of the most appropriate definition of csPCa on biopsy is complex, since biopsy results may accurately reflect neither tumour burden nor aggressiveness. Nonetheless, there is an urgent need to standardise the histological definition(s) of csPCa, to allow meaningful comparisons between studies.
Thirdly, the specificity of mpMRI remains moderate, and there is a substantial proportion of false positives in the lesions scored 3/5 or 4/5 [1 74 75] , even with the new PI-RADS v2 score [76] . In a series of 62 patients with 116 lesions biopsied under magnetic resonance/ultrasound fusion, the overall cancer detection rates for PI-RADS v2 scores of 3/5 and 4/5 were only 15.8% and 29.8%, respectively [77] . In theory, a triage test used to rule out a disease needs to be highly sensitive for this disease. However, if its specificity is too low, it will be clinically useless since most patients will be positive, whether they have the disease or not. Therefore, if mpMRI is to be used as a triage test in the future, there is a need to improve its specificity. This could be achieved by a continuous refinement of scores [78] . Promising results in characterising csPCa have also been reported with a quantitative analysis [79] .
Finally, all published studies were conducted in specialised centres. The broad use of mpMRI as a triage test assumes good interobserver reproducibility. Unfortunately, interobserver reproducibility of existing scoring systems remains moderate [62 63 80] even with the use of the PI-RADS v2 score [80 81] . Studies evaluating on a large scale the reproducibility of mpMRI findings between expert and nonexpert centres are currently lacking.
Three systematic reviews (including two meta-analyses) regarding the role of mpMRI in localised PCa have been published recently 4 5 6 . Crucially, all three reviews focused exclusively on the sensitivity of mpMRI-targeted, guided, or fusion biopsies in diagnosing overall PCa and csPCa, using TRUS-guided prostate biopsies as reference standards. The impact of systematic biopsies on the outcome was not addressed in any of the reviews, within either the index test or the reference standard. Our review had a totally different research question and objective, focusing on NPV of mpMRI to see if a negative mpMRI can avoid the need for a prostate biopsy. As MRI-targeted/guided/fusion biopsies are not relevant if the mpMRI was negative for cancer, it can be argued that the three reviews assessed a different index test altogether. As such, we believe that the findings of this review are novel and unique, and pave the way for further focused clinical studies.
The current study represents the first systematic review addressing the role of mpMRI as a triage test before biopsy. The review elements were developed in conjunction with a multidisciplinary panel of experts (EAU Prostate Cancer Guidelines Panel), which included a patient representative, and the review was performed robustly in accordance with recognised standards. However, it is limited by the major heterogeneity of the existing literature in patient population, study design, and definitions of positive mpMRI and csPCa. It highlighted further areas of research that could help in defining the best use of mpMRI in the early detection of aggressive PCa in the future.
Although mpMRI can detect aggressive PCa with excellent sensitivity, a definitive conclusion on its role as a triage test before prostate biopsy will be possible only when three main issues are addressed. Firstly, because NPV depends on prevalence, and because overall PCa and csPCa prevalence was highly variable in the published series, it becomes mandatory to define the optimal way to pre-evaluate the risk of csPCa in patients with a suspicion of PCa. Depending on the risk category, mpMRI could then be used to obviate biopsies or not. Secondly, there is a need for consensus definitions of csPCa on biopsy findings to allow interstudy comparisons. Thirdly, although efforts have been made to standardise mpMRI technical protocols and interpretation in the past few years [11 60 76] , there is still a crucial need to improve mpMRI specificity and inter-reader reproducibility.
This systematic review was performed under the auspices of:
The European Association of Urology Guidelines Office Board
The European Association of Urology Prostate Cancer Guideline Panel
Author contributions: Olivier Rouvière had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.
Study concept and design: Rouvière, Mottet, Cornford.
Acquisition of data: Rouvière, Moldovan, Van den Broeck, Yuan.
Analysis and interpretation of data: Rouvière, Moldovan, Van den Broeck, Lam.
Drafting of the manuscript: Rouvière, Moldovan, Van den Broeck, Lam.
Critical revision of the manuscript for important intellectual content: Bellmunt, van den Bergh, Bolla, Briers, Van den Broeck, Cornford, Cumberbatch, De Santis, Fossati, Gross, Henry, Joniau, Lam, Matveev, Moldovan, van der Poel, van der Kwast, Rouvière, Schoots, Wiegel, Mottet.
Statistical analysis: None.
Obtaining funding: None.
Administrative, technical, or material support: Yuan, Sylvester, Marconi.
Supervision: None.
Other: None.
Financial disclosures: Olivier Rouvière certifies that all conflicts of interest, including specific financial interests and relationships and affiliations relevant to the subject matter or materials discussed in the manuscript (eg, employment/affiliation, grants or funding, consultancies, honoraria, stock ownership or options, expert testimony, royalties, or patents filed, received, or pending), are the following: Bellmunt is a company consultant for Janssen, Astellas, Pierre Fabre, Genentech, Merck, Ipsen, Pfizer, Novartis, and Sanofi Aventis. He has received research support from Takeda, Novartis, and Sanofi, and received travel grants from Pfizer and Pierre Fabre. Bolla has received company speaker honoraria from Ipsen and Astellas, honoraria or consultation fees from Janssen, and fellowship and travel grants from Janssen, AstraZeneca, and Astellas. Briers has received grant and research support from Ipsen, European Association of Urology, and Bayer; is an ex officio board member for Europa UOMO; is an ethics committee and advisory group member for REQUITE; is a member patient advisory board member for PAGMI; and is a member of SCA and EMA PCWP. Cornford is a company consultant for Astellas, Ipsen, and Ferring. He receives company speaker honoraria from Astellas, Janssen, Ipsen, and Pfizer; participates in trials from Ferring; and receives fellowships and travel grants from Astellas and Janssen. De Santis is a company consultant for GlaxoSmithKline, Janssen, Bayer, Novartis, Pierre Fabre, Astellas, Amgen, Eisai Inc., ESSA, Merck, and Synthon; has received company speaker honoraria from Pfizer, Takeda, Sanofi Aventis, Shionogi, Celgene, and Teva OncoGenex; has participated in trials for Pierre Fabre, Astellas, Exelixis, Bayer, and Roche; has received fellowship and travel grants from Bayer, Novartis, Ferring, Astellas, Sanofi Aventis, and Janssen; has received grant and research support from Pierre Fabre; has received honoraria from AstraZeneca; and is associated with Amgen. Joniau is a company consultant for Astellas, Ipsen, Bayer, Sanofi, and Janssen; has received company speaker honoraria from Astellas, Amgen, Bayer, Sanofi, Janssen, and Ipsen; has participated in trials for Astellas, Janssen, and Bayer; has received fellowship and travel grants from Astellas, Amgen, Bayer, Sanofi, Janssen, Ipsen, and Pfizer; and has received grant and research support from Astellas, Bayer, and Janssen. Matveev has received company speaker honoraria from Sanofi and Astellas, has participated in trials for Astellas, Pfizer and Novartis. Lam is a company consultant for and has received company speaker honoraria from Pfizer, GSK, Astellas, and Ipsen. van der Poel is a company consultant for Intuitive Surgical, has participated in trials for Astellas and Steba Biotech, and has received grant and research support from Astellas. Rouvière is a company consultant for EDAP-TMS, Bracco, and Philips; has received company speaker honoraria from EDAP-TMS, Bracco, and Philips; and has participated in trials for EDAP-TMS and Bracco. Wiegel has received company speaker honoraria from Astellas, Takeda, Hexal, Ipsen, Janssen-Cilac, and Ferring. Mottet has received grant and research support from Takeda Pharmaceutical, Millenium, Astellas, Pierre Fabre, Sanofi, and Pasteur, and has received honoraria or consultation fees from Takeda Pharaceutical, Millenium, Jansen, Astellas, BMS, Bayer, Ipsen, Ferring, Novartis, Nuclétron, Pierre Fabre, Sanofi, and Zeneca. van den Bergh, Van den Broeck, Cumberbatch, Fossati, Gross, Henry, van der Kwast, Sylvester, Yuan, Schoots, Moldovan, and Marconi have nothing to disclose.
Funding/Support and role of the sponsor: None.
A correlation with radical prostatectomy specimens has demonstrated that multiparametric magnetic resonance imaging (mpMRI) has excellent sensitivity in detecting prostate cancer (PCa) with a Gleason score of ≥7 1 2 3 . As a result, prostate mpMRI is increasingly used in patients with a suspicion of PCa to localise abnormal areas before biopsy. A large body of literature has shown that targeted biopsies of suspicious lesions seen on mpMRI (TBx) improved the detection of clinically significant PCa (csPCa), at least in the repeat biopsy setting 4 5 6 . As a result, it is now recommended that an mpMRI is performed before repeat biopsy to allow TBx of suspicious lesions in addition to standard biopsies [7] .
Some authors have recently suggested that, besides improving csPCa detection, mpMRI could also be used as a triage test so that patients with negative mpMRI findings could obviate biopsy. Such a strategy remains highly controversial [8] and depends upon the negative predictive value (NPV) of mpMRI. Therefore, the European Association of Urology Prostate Cancer Guidelines Panel undertook this systematic review and meta-analysis to assess the NPV of mpMRI in patients with a suspicion of PCa and, thus, its potential role in eliminating unnecessary prostate biopsy.
Our primary aim was to systematically evaluate the performance of negative prebiopsy prostate mpMRI in predicting a negative biopsy result for overall PCa and csPCa in biopsy-naïve men and in men with previously negative biopsies. A further objective was to explore and define factors that may contribute to relevant thresholds in order to provide guidance for future studies.
The review was performed according to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) statement [9] . The review protocol was published in PROSPERO database ( http://www.crd.york.ac.uk/PROSPERO; registration number CRD42015021929). Databases searched included the Embase and OVID Medline databases, the Cochrane database of systematic reviews, and the Cochrane Central Register for Clinical Trials, covering from January 1, 2000 to February 13, 2016. Systematic or standard prostate biopsies were used as reference standards, with positive or negative cases of PCa being determined by histopathological examination. The detailed search strategy is presented in Supplement 1.
Included studies focused on men who were assessed for suspected PCa by mpMRI before undergoing prostate biopsy. Studies enrolling both biopsy-naïve men and men who had undergone previous negative biopsies were included. Prebiopsy prostate mpMRI was considered the index test and comprised T2-weighted imaging (T2WI) and at least one functional imaging technique (diffusion-weighted imaging [DWI], dynamic contrast-enhanced imaging [DCEI], or magnetic resonance spectroscopic imaging [MRSI]). For inclusion, studies had to report on false negatives and true negatives, in order to calculate NPV (ie, results of systematic/standard prostate biopsies when the mpMRI was negative). When available, false positive and true positive findings were also noted to calculate the positive predictive value (PPV) and the cancer prevalence. There was restriction neither on the biopsy technique (transrectal or transperineal) nor on the number of biopsy cores. Studies using radical prostatectomy specimens as reference standards were excluded, as were studies evaluating men with histologically proven PCa. Studies with less than 50 participants were excluded. No language restrictions were applied.
Two reviewers (P.C.M. and T.V.D.B.) independently screened all abstracts and full-text articles for eligibility. Disagreement was resolved by consensus or reference to an independent third party (L.M.). All screening was performed using a predefined eligibility form.
Using a data extraction form developed a priori, the same two reviewers independently extracted data concerning study methodology, patient characteristics, technical characteristics of the MR scanners, mpMRI protocol, mpMRI scoring system, definition of positive mpMRI, biopsy protocol, and definition of csPCa. Any discrepancies concerning data extraction were resolved by consensus or reference to an independent arbiter (O.R. or T.B.L.).
To assess the risk of bias (RoB), all included reports were reviewed using the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool for diagnostic accuracy studies [10] .
Outcome data regarding false negative and true negative values of mpMRI before prostate biopsy were recorded as reported by authors. When not available, data were indirectly derived from specificity, sensitivity, and prevalence values reported by authors using an online Bayesian statistics calculator ( http://www.medcalc.com/bayes.html ). Descriptive statistics were used to summarise baseline characteristics and outcomes, including median and interquartile range (IQR) for estimates of NPV across studies. A correlation between mpMRI NPV and a positive biopsy rate was established using the Pearson's correlation coefficient.
A meta-analysis was undertaken to calculate pooled NPV and PPV. To ensure appropriate clinical homogeneity of the studies included in the meta-analysis, we selected only the studies enrolling biopsy-naïve patients and/or patients with a history of negative biopsy, and fulfilling the following criteria that were defined a priori: (1) reference standard consisting of prostate biopsy with at least 10 samples on all patients; (2) mpMRI protocol comprising at least T2WI and DWI; (3) mpMRI results presented as a five-level score, using a subjective Likert scale or the Prostate Imaging Reporting Data System (PI-RADS) score [11] ; (4) definition of positive mpMRI as a score ≥3/5 or ≥4/5; and (5) results reported on a per patient basis. In addition, only studies defining csPCa as Gleason ≥7 cancers were selected for the meta-analysis assessing the mpMRI NPV for csPCa. A bivariate random-effects approach was employed using the Midas package in Stata 12 (StataCorp LP, College Station, TX, USA). Since the NPV decreases and the PPV increases as the prevalence increases, post-test probability estimates of NPV and PPV were reported for the given values of the prevalence based on Bayes’ theorem.
For other studies not included in the meta-analysis based on the criteria described above, a narrative synthesis of the data was performed. To explore and define clinical heterogeneity, subgroups were analysed at patient level based on the following variables: biopsy-naïve versus previous negative biopsy; patients with positive versus negative digital rectal examination (DRE); mpMRI performed with an endorectal versus without an endorectal coil; transrectal ultrasound (TRUS) versus template transperineal (TTP) biopsy approach; and ≤16 cores versus >16 cores as the reference standard. Studies reporting mpMRI NPV for patients with a prostate-specific antigen (PSA) level of ≤10 ng/ml were also reported separately.
The study selection process is depicted in the PRISMA flow diagram ( Fig. 1 ). A total of 2980 abstracts were retrieved. After abstract screening and removal of duplicates, 240 articles were eligible for full text screening, of which 48 studies were eligible for inclusion 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 .
Out of the 48 included studies, 42 were single-centre and six were multicentre studies. Thirty-four studies were prospective and six were retrospective, whilst the design of the rest was unclear. RoB assessment using QUADAS-2 was performed for each of the individual studies ( Fig. 2 A and B). Overall, the RoB was highly heterogeneous across studies for all criteria, except for the reference standard domain, in which RoB was low in most studies.
The 48 studies comprised a total of 9613 men who underwent prostate mpMRI followed by biopsy. The study and patient baseline characteristics are presented in Table 1 . The patient population consisted of biopsy-naive men in nine studies, men with at least one previous negative biopsy in 16 studies, and both biopsy-naïve men and men with a history of previous negative biopsy in nine studies. In 14 studies, the biopsy history of the patients was unclear.
Study | Study design | Period | Population | Pt Nb | Mean/median* age (yr) | Mean/median* PSA (ng/ml) | Mean/median* prostate volume (cm 3 ) | Magnetic field strength | MR pulse sequences | Endorectal coil | MR score | Definition of positive MRI | Reference standard |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Hauth (2015) [25] | Prospective | 2011–2013 | FB | 94 | 64 (43–83) | 9 (3–31) | 51 (17–140) | 1.5 T | T2WI/DWI/DCEI/MRSI | No | PI-RADS v1 | ≥3 | 11–13-core TRUS SBx + TBx |
Lamb (2015) [36] | Retrospective | 2013–2013 | FB & PNB | 173 | NR | NR | NR | 1.5 T | T2WI/DWI | NR | NR | NR | 12-core TRUS SBx |
Brock (2015) [15] | Prospective | 2013–2014 | PNB | 168 | 64* (IQR 59–70) | 9.2* (IQR 6.7–13.4) | 55.4* (IQR 42–80) | 3 T | T2WI/DWI/DCEI | No | PI-RADS v1 | NR | 12/24-core TRUS SBx + TBx |
Grenabo Bergdahl (2016) [22] | Prospective | 2013–2014 | FB & PNB | 83 | 69.3* (IQR 69–69.6) | 1.6* (IQR 0.9–2.7) | NR | 3 T | T2WI/DWI/DCEI/MRSI | No | PI-RADS v1 | ≥3 | 10-core TRUS SBx + TBx |
Wang (2015) [58] | Prospective | 2002–2009 | FB & PNB | 586 | 70 (26–91) | 11.11* (0.02–9794) | NR | 1.5 T | T2WI/DWI/DCEI/MRSI | Yes | PI-RADS v1 | ≥3 | TRUS SBx |
Pepe (2015) [41] | Prospective | 2011–2014 | PNB | 100 | 64* | 8.6* (4.2–10) | NR | 3 T | T2WI/DWI/DCEI/MRSI | No | PI-RADS v1 | ≥4 | TPBx + TBx |
Panebianco (2015) [39] | Prospective | 2011–2014 | FB (61.62%) & PNB (38.34%) | 925 (1140 total cohort) |
NR | NR | NR | 3 T | T2WI/DWI/DCEI | Yes | PI-RADS v1 | NR | 14-core TRUS SBx; 45-core sat TPBx + TBx |
Radtke (2015) [46] | Prospective | 2013–2013 | FB (63.3%) & PNB (36.7%) | 294 | 64* (60–71) | 7.3 (6.0) | 47 (37.5) | 3 T | T2WI/DWI/DCEI | No | PI-RADS v1 | PI-RADS ≥2; PI-RADS ≥3; PI-RADS ≥4; PI-RADS = 5; |
24-core TPBx + TBx |
Itatani (2014) [27] | Retrospective | 2004–2007 | NR | 193 | 68.9 (8.4); 70* (47–89) | 11.8 (15.9); 7.9* (1.22–159) | NR | 1.5 T | T2WI/DWI/DCEI | No | 1–5 scale (Likert) | ≥3 | 12–14-core TRUS SBx |
Porpiglia (2014) [44] | Prospective | 2011–2013 | PNB | 170 | 65* (60–70) | 6.9* (5.2–9.8) | 42* (36–48) | 1.5 T | T2WI/DWI/DCEI | Yes | Dichotomous | Positive: at least 2/3 MR seq. with suspicious findings | 18–24-core TRUS SBx (volume dependent) |
Thompson (2014) [56] | Prospective | 2012–2013 | FB (88%) & PNB (12%) | 150 | 62.4* (IQR 55.0–66.4) | 5.6* (IQR 4.5–7.5) | 40* (IQR 30–57) | 1.5 T (47%) & 3 T (53%) | T2WI/DWI/DCEI | No | PI-RADS v1 | ≥3 | Median of 30 TPBx (volume dependent) |
Pokorny (2014) [43] | Prospective | 2012–2013 | FB | 223 | 63* (IQR 57–68) | 5.3* (IQR 4.1–6.6) | 41* (IQR 30–59) | 3 T | T2WI/DWI/DCEI | No | PI-RADS v1 | ≥3 (primary); ≥4 |
12-core TRUS SBx + TBx |
Petrillo (2014) [42] | Prospective | 2009–2010 | NR | 136 | NR | NR | NR | 1.5 T | T2WI/DWI/MRSI | Yes | 1–5 scale (Likert) | ≥3 | 12–16-core TRUS SBx (volume + PSA dependent) |
Javali (2014) [29] | Retrospective | 2002–2011 | NR | 140 | Control: 62.4 (10.5); Study: 62.9 (12.1) | Control: 6.8 (2.3); Study: 6.87 (2.6) | Control: 44 (14.2); Study: 43 (18.4) | 1.5 T | T2WI/MRSI | Yes | Dichotomous | Cit/[Cho + Cr] < 1.2 | 6-core TRUS SBx ( n = 69), 12-core TRUS SBx ( n = 119) |
Abd-Alazeez (2014) [13] | Prospective | 2007–2011 | FB | 129 | 62* (41–82) | 5.8* (1.2–20) | 40* (16–137) | 1.5 & 3 T | T2WI/DWI/DCEI | No | PI-RADS v1 | ≥3 (primary); ≥4 |
20-core TPBx |
Abd-Alazeez (2014) [12] | Retrospective | NR | PNB | 54 | 64* (39–75) | 10* (2–23) | 53* (19–136) | 1.5 & 3 T | T2WI/DWI/DCEI | No | PI-RADS v1 | ≥3 (primary); ≥4 |
≥20-core TPBx + TBx ( n = 15) |
Matsuoka (2014) [37] | Prospective | 2007–2012 | NR | 135 | 67* (50–80) | 7.0* (2.9–19.8) | 25.4* (12.7–90.2) | 1.5 T | T2WI/DWI | No | 1–5 scale (Likert) | ≥3 | 14-core TRUS SBX |
Junker (2013) [30] | Retrospective | 2011–2013 | PNB | 73 | 62 (7.4) | 7.0* (5.1–12.9) | 45* (34–61) | 3 T | T2WI/DWI/DCEI | No | PI-RADS | PI-RADS ≥10 and ≥11 for all PCa PI-RADS ≥13 for significant PCa |
10-core TRUS SBx + TBx |
Busetto (2013) [16] | Prospective | 2010–2012 | PNB | 163 | 66.4 (5.3) | 6.8 (1.6) | NR | 3 T | T2WI/DWI/DCEI/MRSI | Yes | NR | NR | 10-core TRUS SBx + TBx |
Rais-Bahrami (2013) [47] | Prospective | 2007–2012 | NR | 583 | 61.3 (8.4) | 9.9 (13.1) | NR | 3 T | T2WI/DWI/DCEI/MRSI | Yes | 1–4 scale (Likert) | ≥2 ≥3 |
12-core TRUS SBx + TBx |
Kuru (2013) [34] | Prospective | 2010–2011 | FB (51%) & PNB (49%) | 347 | 65.3 (42–82) | 9.85 (0.5–104) | 48.7 (9–180) | 3 T | T2WI/DWI/DCEI | No | 1–3 scale (Likert) | ≥2 | 12–36-core TRUS SBx (volume dependent) + TBx |
Ferda (2013) [20] | Prospective | NR | NR | 164 | (49–74) | (4.2–123) | NR | 3 T | T2WI/DWI/DCEI/MRSI | No | NR | In house | TRUS SBx |
Ganie (2013) [21] | NR | 2007–2009 | PNB | 87 | NR | NR | NR | 1.5 T | T2WI/MRSI | Yes | MRSI Cho/Cit ratio | In house | 6 core TRUS SBx + MRI TBx |
Vinet (2013) [57] | Prospective | 2009–2011 | FB | 69 | NR | 5.2* (3.2–28) | NR | 1.5 T (35 pts) & 3 T (34 pts) | T2WI/DWI/DCEI | No | 1–5 scale (Likert) | ≥3 | 12-core TRUS SBx + TBx |
Numao (2013) [38] | Prospective | 2006–2010 | FB | 351 | 65* (59–70) | 6.3* (4.9–9.1) | 32* (24–42) | 1.5 T | T2WI/DWI/DCEI (no DCEI in 42 pts) | No | 1–5 scale (Likert) | ≥3 | 3D 26-core (12 TRUS SBx + 14 TPBx – 203 pts); 3D 14-core (6 TRUS SBx + 8 TPBx – 102 pts); TPBx 14 core (46 pts) |
Belas (2012) [14] | Prospective | 2010–2011 | FB | 71 | 66* (47–76) | 7* (4–10) | 45* (15–150) | 1.5 T | T2WI/DWI/DCEI | No | TZ: 0–4 scale PZ: 0–10 scale |
TZ: >2 PZ: >6 |
12-core TRUS SBx + TBx |
Ibrahiem (2012) [26] | Prospective | 2008–2009 | FB | 100 | 65.03 (7.13) | 26.3 (24.2) | 60.09 (28.7) | 1.5 T | T2WI/DWI | No | NR | In house | 12-core TRUS SBX |
Sciarra (2012) [51] | Prospective | 2008–2011 | PNB | 84 | 64.09 (46–76) | 7.07 (4.2–15.5) | NR | 3 T | T2WI/DWI/DCEI/MRSI | Yes | NR | NR | 10-core TRUS Bx + TBx |
Portalez (2012) [45] | Prospective | 2011 | PNB | 129 | 64.7 (47–79) | 9.6 (2.7–40) | 51.1 (12–192) | 1.5 T | T2WI/DWI/DCEI | Mixed | 1–5 scale (Likert) PI-RADS |
Likert ≥3 PI-RADS ≥9 |
10–12-core TRUS SBx + TBx |
Watanabe (2012) [59] | Prospective | 2004–2008 | NR | 1448 | 72 (7.5) | NR | NR | 1.5 T | T2WI/DWI | No | NR | ADC value ≤1.35 × 10 −3 mm 2 /s | 8-core TRUS SBx + TBx |
Tamada (2011) [54] | Retrospective | 2006–2009 | NR | 50 | 70 (40–84) | 6.84* (4.06–9.94) | NR | 1.5 T | T2WI/DWI/DCEI | No | NR | In house | 12-core TRUS SBx |
Choi (2011) [18] | NR | 2009–2010 | NR | 51 | 67.16 (56–90) | 14.16 (1.02–38.9) | 42.98 (13.8–77.3) | 3 T | T2WI/DWI | NR | NR | NR | 10–12-core TRUS SBx + TBx |
Iwazawa (2011) [28] | Retrospective | 2008–2009 | NR | 178 | 68.8 (41–86) | 20.51 (4.04–568.5) | NR | 1.5 T | T2WI/DWI/DCEI | NR | 1–4 scale (Likert) | NR | 10–12-core TRUS SBx (TBx included in SBx chart) |
Rouse (2011) [48] | Prospective | 2005–2007 | PNB | 114 | 63.6 (41–83) | 13.4 (0–228) | NR | 1.5 T | T2WI/DWI/DCEI | NR | 1–5 scale (Likert) | ≥3 | TRUS SBx |
Haffner (2011) [23] | Prospective | 2005–2009 | FB | 555 | 64* (47–83) | 6.75* (0.18–100) | 46* (15–200) | 1.5 T | T2WI/DCEI | No | 1–5 scale (Likert) | ≥3 | 10-core TRUS SBx + TBx |
Panebianco (2010) [40] | Prospective | 2007–2009 | PNB | 150 | 61.2 (46–78) | 9.42 (3.91) | 41.17 (7.47) | 1.5 T | T2WI/DCEI/MRSI | Yes | NR | In house | 10-core TRUS SBx (TBx included in SBx chart) |
Roy (2010) [49] | Not specified | 2011–2009 | FB (53%) & PNB (47%) | 103 | 63 (52–78) | 7* | NR | 3 T | T2WI/DWI/DCEI | Yes | NR | NR | 8-core TRUS SBx + TBx |
Testa (2010) [55] | Not specified | 2007 | PNB | 54 | 63.9 (52–76) | 11.4 (3–42) | 59.3 (30–150) | 1.5 T | T2WI/MRSI | Yes | 1–3 scale (Likert) | ≥2 | 12-core TRUS SBx + TBx |
Sciarra (2010) [52] | Prospective | 2007–2009 | PNB | 110 | 63.5 (49–74) | NR | NR | 1.5 T | T2WI/DCEI/MRSI | Yes | NR | In house | 10-core TRUS SBx + TBx |
Kitajima (2010) [31] | Prospective | 2008–2009 | NR | 53 | 69* (56–84) | 11.1* (4.2–112.1) | NR | 3 T | T2WI/DWI/DCEI | No | 1–5 scale (Likert) | ≥3 | 20-core TPBx |
Labanaris (2010) [35] | Prospective | 2004–2008 | PNB | 260 | NR | NR | NR | 1 T | T2WI/DWI/DCEI | Yes | Dichotomous | In house | 18-core TRUS SBx |
Kumar (2009) [32] | NR | NR | NR | 61 | 65.3 (9.3) | 16.5 (0.21–155) | NR | 1.5 T | T2WI/MRSI | Yes | NR | (Cit/(Cho + Cr) ≤ 1.2 | TRUS Bx |
Schmuecking (2009) [50] | NR | NR | FB & PNB | 67 | 68 | 11.5 | NR | 1.5 T | T2WI/DCEI | No | NR | NR | 20-core Bx |
Cheikh (2009) [17] | Retrospective | 2005–2008 | PNB | 93 | 63.2 (52–74) | 9.63 (1.6–40) | NR | 1.5 T | T2WI/DCEI | No | Dichotomous | In house | 12-core TRUS SBx + TBx |
Cirillo (2008) [19] | Prospective | 2004–2006 | PNB | 54 | 65.5 (5.2) | 10.8 (7.5) | NR | 1.5 T | T2WI/MRSI | Yes | Dichotomous | In house | 10-core TRUS SBx + TBx |
Kumar (2007) [33] | Prospective | 2003–2005 | NR | 83 | NR | NR | NR | 1.5 T | T2WI/MRSI | Yes | NR | NR | 12-core TRUS SBx + TBx |
Squillaci (2005) [53] | Prospective | 2004–2005 | NR | 65 | NR | NR | NR | 1.5 T | T2WI/DCEI/MRSI | No | 1–3 scale (Likert) | ≥2 | 10-core TRUS SBx + TBx |
Hara (2005) [24] | Prospective | 2003–2004 | FB | 90 | 67.2 (NR) | NR | NR | 1.5 T | T2WI/DCEI | No | 1–3 scale (Likert) | ≥2 = 3 |
14-core TRUS SBx |
The magnetic field strength was 1, 1.5, and 3 T in one, 28, and 15 studies, respectively. Four studies used both 1.5 and 3 T MR systems. DWI and DCEI were used in 36 and 35 studies, respectively. Nineteen studies also added MRSI. An endorectal coil was used in 18 studies. The definition of positive mpMRI varied across studies. The PI-RADS v1 score was used in 12 studies, a five-level subjective (Likert) score was used in eight studies, and one study reported data based on the two scoring systems. In-house criteria were used in 13 studies for defining positive mpMRI, and five studies used a dichotomous definition. Nine studies did not report on the criteria for positive mpMRI. No study used the PI-RADS v2 score.
Regarding the reference standard, TRUS-guided biopsies were used in 39 studies, TTP biopsies in six studies, and mixed TRUS-guided and TTP biopsies in two studies. In one study, the biopsy approach was unclear. The number of cores per biopsy procedure was ≤16 in 30 studies, >16 in nine studies, and variable among patients in three studies. For six studies, the number of biopsy cores taken was unclear.
At patient level, the median biopsy positivity rate (ie, cancer prevalence) was 50.4% (IQR, 36.4–57.7%) for overall cancer and 32.9% (IQR, 28.1–37.2%) for csPCa ( Table 2 ). The median mpMRI NPV was 82.4% (IQR, 69.0–92.4%) for overall cancer and 88.1% (IQR, 85.7–92.3) for csPCa. NPV significantly decreased when cancer prevalence increased, both for overall cancer ( r = –0.64, p < 0.0001) and csPCa ( r = –0.75, p = 0.032; Fig. 3 ). In addition, NPV was highly dependent on the definition used for csPCa, with differences of up to 21% when several definitions were used in the same dataset [12 13 38 47 48] .
Study | Overall PCa prevalence (%) | Reporting level | Multiparametric MRI performance for PCa detection | Definition of csPCa | csPCa prevalence | Multiparametric MRI performance for csPCa detection | ||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
TN | FN | TP | FP | NPV | PPV | TN | FN | TP | FP | NPV | PPV | |||||
Hauth (2015) [25] | 45.7 | Patient | 6 | 1 | 42 | 45 | 85.7% | 48.3% | Low grade: GS ≤ 6 High grade: GS ≥ 7 |
NR | NR | NR | NR | NR | NR | NR |
Lesion | 59 | 13 | 55 | 73 | 81.9% | 43% | ||||||||||
Lamb (2015) [36] | 65.9 | Patient | 23 | 22 | 92 | 36 | 51.1% | 71.9% | GS ≥ 7 | 50.9% | 31 | 14 | 71 | 57 | 68.9% | 55.5% |
Brock (2015) [15] | 42.3 | Patient | 17 | 7 | 56 | 88 | 70.8% | SBx: 38.8% TBx: 22.2% Duo: 44.4% |
Epstein: GS > 6 and/or max CCL ≥50% | 24.4% | SBx: 21 | SBx: 3 | SBx: 38 TBx: 27 duo: 47 |
SBx: 106 TBx: 117 duo: 97 |
87.5% | SBx: 26.4% TBx: 18.8% duo: 32.6% |
Grenabo Bergdahl (2016) [22] | 33.7 | Patient | 36 | 7 | 19 | 21 | 83.7% | 47.5% | Clinically insignificant PCa: T1c, PSAd < 0.15, GS < 7, ≤2 positive cores, and unilateral cancer | NR | NR | NR | NR | NR | NR | NR |
Wang (2015) [58] | 58 | Patient | 165 | 8 | 332 | 81 | 95.4% | 80.4% | NR | NR | NR | NR | NR | NR | NR | NR |
Pepe (2015) [41] | 37 | Patient | 23 | 8 | 29 | 40 | 74.2% | 42% | GS ≥ 7 or GS 6 with CCL ≥ 50% | NR | NR | NR | NR | NR | 100% | 55.8% |
Panebianco (2015) [39] | 74.7 | Patient | Group A (satBx): 104 | Group A (satBx): 43 | Group A: 186 | Group A: 22 | Group A (satBx): 70.7% | Group A: 89.4% | NR | 60% | Group A: 147 | Group A: 0 | Group A: 183 | Group A: 25 | Group A: 100% | Group A: 88% |
Group B (TRUSGB NR TRUS G satBx): 93 | Group B (TRUSGB NR TRUS G satBx): 37 | Group B: 417 before and 425 after satBx | Group B: 23/440 and 15/440 after satBx. | Group B (TRUSGB–TRUS G satBx): 71.5% | Group B: 94.8% before and 96.6% after satBx | 71.9% | Group B: 130 | Group B: 0 | Group B: 410 |
Group B: 30 | Group B: 100% | Group B: 93.2% | ||||
Radtke (2015) [46] | 51 | Patient | ≥2/5: 80 ≥3: 103 ≥4: 138 = 5: 142 |
≥2/5: 18 ≥3/5: 38 ≥4/5: 78 = 5/5: 126 |
≥2/5: 132 ≥3/5: 112 ≥4/5: 72 = 5/5: 24 |
≥2/5: 64 ≥3/5: 41 ≥4/5: 6 = 5/5: 2 |
≥2/5: 81.6% ≥ 3/5: 73.1% ≥ 4/5: 63.9% = 5/5: 53% |
≥2/5: 67.4% ≥ 3/5: 73.2% ≥ 4/5: 92.3% = 5/5: 92.3% |
GS ≥ 7 | 29.3% | ≥2/5: 91 ≥3/5: 124 ≥4/5: 183 = 5/5: 203 |
≥2/5: 7 ≥3/5: 17 ≥4/5: 33 = 5/5: 65 |
≥2/5: 79 ≥3/5: 69 ≥4/5: 53 = 5/5: 21 |
≥2/5: 117 ≥3/5: 84 ≥4/5: 25 = 5/5: 5 |
≥2/5: 92.2% ≥3/5: 87.9% ≥4/5: 84.7% = 5/5: 75.8% |
≥2/5: 40.3% ≥3/5: 45.1% ≥4/5: 68% = 5/5: 80.7% |
Itatani (2014) [27] | 13 | Patient | 168 | 25 | NR | NR | 87% | NR | (1) PSAd ≥ 0.1 or GP 4/5 or ≥ 3/6 pos cores; max CCL < 50% (2) PSAd ≥ 0.15 or GP 4/5 or max core length invasion < 3 mm (min 6 cores) |
NR | NR | NR | NR | NR | NR | NR |
Porpiglia (2014) [44] | 30.6 | Patient | 107 | 5 | 47 | 11 | 95.5% | 81% | NR | NR | NR | NR | NR | NR | NR | NR |
Thompson (2014) [56] | 61.3 | Patient | 35 | 16 | 76 | 23 | 68.6% | 76.7% | Moderate or high risk Moderate risk: GS 7 (GP4 >5%) and <50% of positive cores or GS 6–7 (GP4 ≤ 5%) and either ≥30% of positive cores or max core length invasion ≥8 mm High risk: GS ≥ 7 (GP4 > 5%); ≥50% + cores or GS ≥ 8 |
34% | 49 | 2 | 49 | 50 | 96% | 49.5% |
Pokorny (2014) [43] | 63.7 | Patient | ≥3/5: 56 ≥4/5: 74 |
≥3/5: 25 ≥4/5: 40 |
≥3/5: 101 ≥4/5: 86 |
≥3/5: 41 ≥4/5: 23 |
≥3/5: 69.1% ≥4/5: 64.9% |
≥3/5: 71.1% ≥4/5: 78.9% |
NR | NR | NR | NR | NR | NR | NR | NR |
Petrillo (2014) [42] | 18.4 | Patient | 56 | 4 | 21 | 55 | 93% | 28% | NR | NR | NR | NR | NR | NR | NR | NR |
Javali (2014) [29] | 16.4 | Patient | 49 | 1 | 22 | 68 | 98% | 24.4% | NR | NR | NR | NR | NR | NR | NR | NR |
Abd-Alazeez (2014) [13] | 54.7 | Lobe | ≥3/5: 33 | ≥3/5: 14 | ≥3/5: 127 | ≥3/5: 84 | ≥3/5: 70% | ≥3/5: 60% | Def 1: GS ≥ 4 + 3 and/or max CCL ≥ 6 mm Def 2: GS ≥ 3 + 4 and/or max CCL ≥ 4 mm Def 3: GS ≥ 4 + 3 Def 4: GS ≥ 3 + 4 Def 5: max CCL ≥ 6 mm Def 6: max CCL ≥ 4 mm |
Def 1: NR Def 2: 44.2% Def 3: 23.2% Def 4: 36% Def 5: 32.9% Def 6: 39.5% |
Def 1: 46 Def 2: 42 Def 3: 47 Def 4: 43 Def 5: 46 Def 6: 43 |
Def 1: 1 Def 2: 5 Def 3: 0 Def 4: 4 Def 5: 1 Def 6: 4 |
Def 1: 45 Def 2: 72 Def 3: 13 Def 4: 50 Def 5: 39 Def 6: 59 |
Def 1: 166 Def2: 139 Def 3: 198 Def 4: 161 Def 5: 172 Def 6: 152 |
Def 1: 98 Def 2: 89 Def 3: 100 Def 4: 92 Def 5: 98 Def 6: 91 |
Def 1: 21 Def 2: 34 Deg 3: 6 Def 4: 24 Def 5: 19 Def 6: 28 |
≥4/5: 87 | ≥3/5: 62 | ≥3/5: 79 | ≥3/5: 30 | ≥3/5: 58% | ≥3/5: 73% | Def 1: 140 Def 2: 124 Def 3: 148 Def 4: 133 Def 5: 141 Def 6: 131 |
Def 1: 9 Def 2: 25 Def 3: 1 Def 4: 16 Def 5: 8 Def 6: 18 |
Def 1: 37 Def 2: 52 Def 3: 12 Def 4: 38 Def 5: 32 Def 6: 45 |
Def 1: 72 Def 2: 57 Def 3: 97 Def 4: 71 Def 5: 77 Def 6: 64 |
Def 1: 94 Def 2: 83 Def 3: 99 Def 4: 89 Def 5: 95 Def 6: 88 |
Def 1: 34 Def 2: 48 Def 3: 11 Def 4: 35 Def 5: 30 Def 6: 42 |
|||||
Abd-Alazeez (2014) [12] | 47.2 | Lobe | ≥3/5: 26 | ≥3/5: 13 | ≥3/5: 38 | ≥3/5: 31 | ≥3/5: 66% | ≥3/5: 55% | Def 1: GS ≥ 4 + 3 and/or max CCL ≥ 6 mm Def 2: GS ≥ 3 + 4 and/or max CCL ≥ 4 mm Def 3: GS ≥ 4 + 3 Def 4: GS ≥ 3 + 4 Def 5: max CCL ≥ 6 mm Def 6: max CCL ≥ 4 mm |
Def 1: 18.5% Def 2: 31.5% Def 3: 4.6% Def 4: 21.3% Def 5: 16.7% Def 6: 25% |
Def 1: 37 Def 2: 31 Def 3: 39 Def 4: 36 Def 5: 37 Def 6: 32 |
Def 1: 2 Def 2: 8 Def 3: 0 Def 4: 3 Def 5: 2 Def 6: 7 |
Def 1: 18 Def 2: 26 Def 3: 5 Def 4: 20 Def 5: 16 Def 6: 20 |
Def 1: 51 Def 2: 43 Def 3: 64 Def 4: 49 Def 5: 53 Def 6: 49 |
Def 1: 95 Def 2: 79 Def 3: 100 Def 4: 92 Def 5: 95 Def 6: 82 |
Def 1: 26 Def 2: 38 Def 3: 7 Def 4: 29 Def 5: 23 Def 6: 29 |
≥4/5: 49 | ≥4/5: 25 | ≥4/5: 26 | ≥4/5: 8 | ≥4/5: 66% | ≥4/5: 76% | Def 1: 70 Def 2: 63 Def 3: 73 Def 4: 68 Def 5: 70 Def 6: 64 |
Def 1: 4 Def 2: 11 Def 3: 1 Def 4: 6 Def 5: 4 Def 6: 10 |
Def 1: 16 Def 2: 23 Def 3: 4 Def 4: 17 Def 5: 14 Def 6: 17 |
Def 1: 18; Def 2: 11 Def 3: 30 Def 4: 17 Def 5: 20 Def 6: 17 |
Def 1: 94 Def 2: 85 Def 3: 99 Def 4: 92 Def 5: 94 Def 6: 86 |
Def 1: 47 Def 2: 67 Def 3: 12 Def 4: 50 Def 5: 41 Def 6: 49 |
|||||
Matsuoka (2014) [37] | 64.8 | Lobe | 46 | 49 | 149 | 26 | 48.4% | 85.1% | NR | NR | NR | NR | NR | NR | NR | NR |
Junker (2013) [30] | 53.4 | Patient | ≥10/15: 21 ≥11/15: 28 |
≥10/15: 4 ≥11/15: 12 |
≥10/15: 35 ≥11/15: 27 |
≥10/15: 13 ≥11/15: 6 |
≥10/15: 84% ≥11/15: 70% |
≥10/15: 72.9% ≥11/15: 81.8% |
GS ≥ 4 + 3 | 13.7% | ≥13: 54 | ≥13: 2 | ≥13: 8 | ≥13: 9 | ≥13: 96.4% | ≥13: 47% |
Busetto (2013) [16] | 41.7 | Patient | 59 | 7 | 61 | 36 | 89% | 63% | NR | NR | NR | NR | NR | NR | NR | NR |
Rais-Bahrami (2013) [47] | 54.2 | Patient | ≥2/4 : 80 | ≥2/4: 275 | ≥2/4: 187 | ≥2/4: 275 | ≥2/4: 66% | ≥2/4: 59% | GS ≥ 7: GS ≥ 8 |
31.7% | NR | NR | NR | NR | GS ≥ 7: 91% GS ≥ 8: 91% |
GS ≥ 7: 38% GS ≥ 8: 18% |
≥3/4: 251 | ≥3/4: 76 | ≥3/4: 16 | ≥3/4: 76 | ≥3/4: 51% | ≥3/4: 82% | NR | NR | NR | NR | GS ≥ 7: 75% GS ≥ 8: 91% |
GS ≥ 7: 67% GS ≥ 8: 41% |
|||||
Kuru (2013) [34] | 57.6 | Patient | 80 | 14 | 67 | 186 | 85.1% | 73.5% | NR | NR | NR | NR | NR | NR | NR | NR |
Ferda (2013) [20] | 51.2 | Patient | 52 | 2 | 82 | 28 | 96.3% | 74.5% | NR | NR | NR | NR | NR | NR | NR | NR |
Ganie (2013) [21] | 74.7 | Patient | 13 | 3 | 62 | 9 | 59.1% | 95.4% | NR | NR | NR | NR | NR | NR | NR | NR |
Vinet (2013) [57] | 49.3 | Patient | ≥3/5: 11 | ≥3/5: 6 | ≥3/5: 28 | ≥3/5: 24 | ≥3/5: 64.7% | ≥3/5: 53.8% | NR | NR | NR | NR | NR | NR | NR | NR |
≥4/5: 22 | ≥4/5: 11 | ≥4/5: 23 | ≥4/5: 13 | ≥4/5: 66.7% | ≥4/5: 63.8% | NR | NR | NR | NR | NR | NR | NR | NR | |||
Numao (2013) [38] | 45 | Patient | 137 | 57 | 101 | 56 | 70.6% | 64.3% | Def 1: GS ≥4 + 3 and/or ≥20% positive cores and/or max CCL ≥5 mm Def 2: GS ≥ 3 + 4 and/or ≥20% + cores and/or max CCL ≥5 mm Def 3: GS ≥ 3 + 4 and/or ≥20% + cores |
Def 1: 33.3% Def 2:37.8% Def 3: 35.8% |
Def 1: 74 Def 2: 65 Def 3: 69 |
Def 1: 83 Def 2: 92 Def 3: 88 |
Def 1: 160 Def 2: 153 Def 3: 156 |
Def 1: 34 Def 2: 41 Def 3: 38 |
Def 1: 82.4% Def 2: 78.8% Def 3: 80.4% |
Def 1: 58.8% Def 2: 58.5% Def 3: 56% |
Belas (2012) [14] | 53.5 | Patient | 22 | 12 | 23 | 13 | 64.7% | 63.8% | NR | NR | NR | NR | NR | NR | NR | NR |
Ibrahiem (2012) [26] | 73.9 | Patient | 14 | 11 | 57 | 10 | 56% | 85.1% | NR | NR | NR | NR | NR | NR | NR | NR |
Sciarra (2012) [51] | 34.5 | Patient | 41 | 4 | 25 | 14 | 91.1% | 64.1% | NR | NR | NR | NR | NR | NR | NR | NR |
Portalez (2012) [45] | 48.1 | Lesion | Likert: 357 | Likert: 50 | Likert: 81 | Likert: 50 | Likert: 95% | Likert: 38% | Max CCL >3 mm and/or GG 4/5 | NR | NR | NR | NR | NR | NR | NR |
PI-RADS: 404 | PI-RADS: 47 | PI-RADS: 34 | PI-RADS: 47 | PI-RADS: 95% | PI-RADS: 58% | |||||||||||
Watanabe (2012) [59] | 48.1 | Patient | 485 | 73 | 624 | 266 | 86.9% | 70.1% | NR | NR | NR | NR | NR | NR | NR | NR |
Tamada (2011) [54] | 70 | Patient | 12 | 6 | 29 | 3 | 67% | 91% | NR | NR | NR | NR | NR | NR | NR | NR |
Region | 277 | 48 | 55 | 20 | 85% | 73% | ||||||||||
Choi (2011) [18] | 70.6 | Patient | 9 | 5 | 31 | 6 | 64.2% | 75.7% | NR | NR | NR | NR | NR | NR | NR | NR |
Iwazawa (2011) [28] | 40.5 | Region | 887 | 86 | 232 | 219 | 91.1% | 51.4% | NR | NR | NR | NR | NR | NR | NR | NR |
Rouse (2011) [48] | 33.7 | Sextant | 145 | 11 | 74 | 22 | 92.9% | 77.1% | GS ≥ 7: Def 1: ≥3 mm Def 2: ≥5 mm |
Def 1: 26.6% Def 2: 26.2% |
Def 1: 153 Def 2: 153 |
Def 1: 3 Def 2: 3 |
Def 1: 64 Def 1: 63 |
Def 1: 32 Def 2: 33 |
Def 1: 98.1% Def 2: 98.1% |
Def 1: 68.1% Def 2: 67% |
59.6 | Patient | 24 | 14 | 54 | 22 | 63.2% | 71.1% | Def 1: 41.2% Def 2: 36.8% |
Def 1: 30 Def 2: 31 |
Def 1: 4 Def 2: 3 |
Def 1: 43 Def 2: 39 |
Def 1: 4 Def 2: 3 |
Def 1: 88.2% Def 2: 91.2% |
Def 1: 53.8% Def 2: 48.8% |
||
Haffner (2011) [23] | 54.4 | Patient | 154 | 50 | 240 | 111 | 75.4% | 68.3% | NR | NR | NR | NR | NR | NR | NR | NR |
Panebianco (2010) [40] | 42.7 | Patient | NR | NR | NR | NR | 95.1% | 88.2% | NR | NR | NR | NR | NR | NR | NR | NR |
Roy (2010) [49] | 55.9 | Patient | NR | NR | NR | NR | 71% | 75% | NR | NR | NR | NR | NR | NR | NR | NR |
Testa (2010) [55] | 40.7 | Patient | NR | NR | NR | NR | 79.3% | 64% | NR | NR | NR | NR | NR | NR | NR | NR |
Sciarra (2010) [52] | 50 | Patient | 61 | 4 | 66 | 9 | 93.8% | 88% | NR | NR | NR | NR | NR | NR | NR | NR |
Kitajima (2010) [31] | 56.6 | Patient | 311 | 19 | 80 | 14 | 92.2% | 85.1% | NR | NR | NR | NR | NR | NR | NR | NR |
Labanaris (2010) [35] | 73.9 | Patient | 17 | 73 | 96 | 74 | 81.11% | 56.47% | NR | NR | NR | NR | NR | NR | NR | NR |
Kumar (2009) [32] | 21.7 | Patient | 39 | 3 | 10 | 8 | 92.8% | 55% | NR | NR | NR | NR | NR | NR | NR | NR |
Schmuecking (2009) [50] | NR | Lobe | NR | NR | NR | NR | 96% | 61% | NR | NR | NR | NR | NR | NR | NR | NR |
Cheikh (2009) [17] | 24.7 | Patient | 36 | 12 | 11 | 34 | 80% | 22.9% | NR | NR | NR | NR | NR | NR | NR | NR |
Cirillo (2008) [19] | 31.5 | Patient | 19 | 0 | 17 | 18 | 100% | 48.6% | NR | NR | NR | NR | NR | NR | NR | NR |
Kumar (2007) [33] | 13.3 | Patient | 39 | 0 | 11 | 33 | 100% | 25% | NR | NR | NR | NR | NR | NR | NR | NR |
Squillaci (2005) [53] | 50.8 | Patient | 29% | 8% | 25% | 3% | 89% | 80% | NR | NR | NR | NR | NR | NR | NR | NR |
Hara (2005) [24] | 41.5 | Patient | ≥2/3: 40 = 3/3: 47 |
≥2/3: 4 = 3/3: 8 |
≥2/3 30 = 3/3: 26 |
≥2/3: 8 = 3/3: 1 |
≥2/3: 90% = 3/3: 85% |
≥2/3: 78.9% = 3/3: 96.3% |
NR | NR | NR | NR | NR | NR | NR | NR |
Cancer prevalence tended to be higher and mpMRI NPV lower in the biopsy-naïve group as compared with the repeat biopsy group, in men with positive DRE as compared with men with negative DRE and when an endorectal coil was not used ( Table 3 ). There were no clear differences in the prevalence and NPV of the other analysed subgroups (TRUS-guided vs TTP biopsy, biopsy procedures with ≤16 cores vs >16 cores; Table 3 ). However, comparisons must be interpreted with care, due to the small number of studies in some subgroups. In patients with a PSA level of ≤10 ng/ml, the median NPV for overall PCa was 86.3% (IQR, 73.3–93.6%) for a median cancer prevalence of 35.4% (IQR, 27.6–42.5%).
Nb of studies | Median PCa prevalence | Median mpMRI NPV | Nb of studies | Median csPCa prevalence | Median mpMRI NPV | |
---|---|---|---|---|---|---|
Biopsy-naïve patients | 8 | 51.4% (45.5–56.7) | 69.9% (64.2–78) | 1 | 35.8% (NA) | 80.4% (NA) |
Repeat biopsy | 14 | 42% (35.1–52.6) | 82.6% (75.5–93.1) | 3 | 24.4% (19.1–32.8) | 88.2% (87.9–92.3) |
TRUS-guided biopsy | 36 | 49.7% (34.3–57.7) | 84.6% (68.6–92.8) | 4 | 28.1% (21.7–36.5) | 89.3% (82.9–92.4) |
TTP biopsy | 4 | 53.8% (47.5–57.8) | 73.6% (72–78.7) | 2 | 31.6% (30.5–32.8) | 92% (89.9–94) |
Biopsy with ≤16 cores | 28 | 48.7% (39.2–54.8) | 81.9% (66.8–89.3) | 5 | 28.1% (21.8–36.5) | 89.3% (82.9–92.4) |
Biopsy with >16 cores | 5 | 56.6% (51–61.3) | 81.1% (73.1–92.2) | 2 | 31.7% (30.5–32.8) | 92% (89.9–93.9) |
Positive DRE | 1 | 73.9% (NA) | 56% (NA) | 0 | – | – |
Negative DRE | 6 | 36% (34.6–46.8) | 82.7% (74.2–93.1) | 0 | – | – |
Endorectal coil | 17 | 41.7% (30.6–55.9) | 92.8% (79.3–95.4) | 1 | 31.7% (NA) | 91% (NA) |
No endorectal coil | 22 | 50.9% (41.7–56.1) | 77.7% (69.5–86.6) | 7 | 34% (26.9–46.1%) | 87.9% (78.2–92.1) |
Eight studies reported NPV at patient level for overall PCa and fulfilled the inclusion criteria for meta-analysis ( Table 4 ) [22 25 38 41 43 46 56 57] .
Study | Prevalence a (%) | Neg MRI (%) | NPV (%) | PPV (%) | Spe (%) | Se (%) | ||
---|---|---|---|---|---|---|---|---|
All PCa | Score ≥ 3/5 | Grenabo Bergdahl (2016) [22] | 31.3 | 66.9 | 83.7 | 47.5 | 63.2 | 73.1 |
Numao (2013) [38] | 45 | 29.4 | 70.6 | 64.3 | 71.0 | 63.9 | ||
Hauth (2015) [25] | 45.7 | 14.3 | 85.7 | 48.3 | 11.8 | 97.7 | ||
Vinet (2013) [57] | 49.3 | 24.6 | 64.7 | 53.8 | 31.4 | 82.4 | ||
Radtke (2015) [46] | 51 | 27 | 73 | 73.2 | 71.5 | 74.7 | ||
Thompson (2014) [56] | 61.3 | 31.4 | 68.6 | 76.8 | 60.3 | 82.6 | ||
Pokorny (2014) [43] | 63.7 | 30.9 | 69.1 | 82.4 | 69.1 | 82.4 | ||
Score ≥ 4/5 | Pepe (2015) [41] | 37 | 31 | 74.2 | 42 | 36.5 | 78.4% | |
Vinet (2013) [57] | 49.3 | 47.8 | 66.7 | 63.9 | 62.9 | 67.6% | ||
Radtke (2015) [46] | 51 | 73.5 | 63.9 | 92.3 | 95.8 | 48% | ||
Gleason ≥7 PCa | Score ≥ 3/5 | Radtke (2015) [46] | 29.3 | 27 | 87.9 | 45.1 | 59.6 | 80.2% |
a Prevalence of overall prostate cancers (10 first lines) or Gleason ≥7 cancers (last line).
PCa = prostate cancer; MRI = magnetic resonance imaging; Neg MRI = proportion of negative magnetic resonance imaging; NPV = negative predictive value; PPV = positive predictive value; Se = sensitivity; Spe = specificity.
Seven studies used a score of ≥3/5 for defining positive mpMRI ( Fig. 4 A and B) [22 25 38 43 46 56 57] . Fig. 4 C shows the conditional probability plot of 1 – NPV and PPV as a function of overall PCa prevalence. Table 5 shows NPV and PPV estimates for the given values of PCa prevalence.
PCaPrev | PPV | NPV |
---|---|---|
0.30 | 0.43 (0.34–0.53) | 0.88 (0.77–0.99) |
0.40 | 0.54 (0.45–0.64) | 0.82 (0.70–0.94) |
0.50 | 0.64 (0.55–0.73) | 0.76 (0.64–0.88) |
0.60 | 0.73 (0.65–0.80) | 0.67 (0.56–0.79) |
0.70 | 0.81 (0.75–0.87) | 0.57 (0.47–0.67) |
0.75 | 0.84 (0.79–0.89) | 0.51 (0.42–0.59) |
Only three studies used a score of ≥4/5 for defining positive mpMRI ( Table 4 ) [41 46 57] , and a formal meta-analysis could not be performed.
Only one study reporting NPV at patient level for Gleason ≥7 cancers met the selection criteria for inclusion in the meta-analysis. It reported NPV and PPV of 87.9% and 45.1%, respectively, for a prevalence of 29.3% ( Table 4 ) [46] .
We observed a large variability in reported NPV. Many factors, such as differences in mpMRI protocols, definition of negative mpMRI, or biopsy protocols, can explain this variability. However, two major causes of variability must be pointed out. First, the cancer prevalence was highly variable, ranging at patient level from 13% to 74.7% for overall PCa, and from 13.7% to 50.9% for csPCa. This variability was observed in both the biopsy-naïve and the repeat biopsy setting. As NPV depends on prevalence, this had a major impact on reported NPV ( Fig. 3 ). Second, the definition of csPCa was highly variable from one series to another, and differences of up to 21% could be observed in NPV when different definitions of csPCa were used in the same dataset [12 13 38 47 48] .
To account for clinical heterogeneity and to further explore the clinical relevance of the results, we carefully selected studies for inclusion in the meta-analysis based on stringent criteria. Particularly, we included only studies that: (1) had biopsy protocols with at least 10 cores, since it is no longer recommended to obtain less than 10 cores per biopsy; (2) used DWI, which is the most informative technique, at least for cancers in the peripheral zone [60] ; and (3) reported mpMRI findings using a five-level score, so that negative findings could be better defined. We accepted studies using a subjective (Likert) scale because experienced readers obtained equivalent [45 61 62] or better [63] results with the Likert score than with the PI-RADS v1 score. Owing to the large variations of NPV induced by differences in definitions of csPCa, we did not include different definitions in the meta-analysis since this would have introduced unacceptable clinical heterogeneity in the results, possibly resulting in erroneous and biased estimates. We, therefore, a priori restricted the definition of csPCa to cancers with a Gleason score of ≥7, given the low lethal potential of Gleason 6 cancers [64] and the lack of consensus among pathologists on the best method to measure biopsy core invasion length [65 66] .
In this more homogeneous group of studies, the prevalence range was still large (31.3–63.7%). As a result, we modelled the evolution of NPV (and PPV) as a function of overall PCa prevalence. Unfortunately, we could not duplicate this for csPCa since only one study reporting NPV for Gleason ≥7 cancers met the inclusion criteria for meta-analysis.
We included only studies that reported the results of systematic/standard biopsy in patients with negative mpMRI and used the systematic/standard biopsy as a reference standard. It is well known that TRUS-guided biopsy harbours both random and systematic errors, as evidenced by the high rates of positivity of immediate repeat biopsy after a first series of negative biopsies [67 68] , and as confirmed recently by the PROMIS trial [69] . Therefore, using TRUS-guided biopsy as a reference standard may have overestimated the NPV of mpMRI. However, studies using radical prostatectomy specimens as a reference standard have already reported mpMRI detection rates in relation to PCa Gleason score and volume [1] . In this review, we intended to address the more pragmatic question as to whether a negative mpMRI could predict a negative subsequent biopsy. This is an important question because if the NPV of mpMRI was sufficiently high in comparison with the reference standard of systematic/standard biopsies, then in practice a negative mpMRI result could indeed avoid the need for prostate biopsy. Therefore, studies reporting only biopsy results when the mpMRI was positive (eg, obtained through MRI-targeted, guided, or fusion biopsies with added systematic biopsies) were not included in this review.
It is now well established that mpMRI is a sensitive tool for detecting aggressive PCa 1 2 3 69] . However several reasons preclude its broad use as a triage test before biopsy.
Firstly, the population referred to prostate biopsy is not standardised. The large range of reported prevalence for overall PCa and csPCa suggests substantial heterogeneity in the way patients are selected for biopsy. Owing to this heterogeneity, we did not provide a pooled estimate for mpMRI NPV. The role of mpMRI as a triage test before prostate biopsy should be evaluated in the broader context of the selection of patients with a suspicion of (aggressive) PCa. In a recent retrospective study of 514 patients, mpMRI NPV for Gleason ≥7 cancers was 91% when the PSA density was ≤0.2 ng/ml/ml, and only 71% when the PSA density was >0.2 ng/ml/ml ( p = 0.003) [70] . In another series of 288 biopsy-naïve patients, no csPCa (Gleason score ≥7 or maximum cancer core length ≥4 mm) was found in 44 patients with a PSA density of <0.15 ng/ml/ml and a PI-RADS v2 score of <3/5 [71] . We believe that such prestratification of the risk of csPCa is an interesting way for rationalising the use of mpMRI before biopsy. Patients found at very low risk would be spared both mpMRI and biopsy. Patients at a low risk—for whom mpMRI would have an NPV high enough to be used as a triage test—could avoid biopsy in case of negative mpMRI. Patients at a higher risk would need biopsy even in case of negative mpMRI. Many tools can be used to risk stratify the population of patients referred to biopsy, ranging from simple parameters such as PSA density to more complicated risk calculators [72 73] . The impact of these tools on the NPV of prebiopsy mpMRI needs to be carefully evaluated, both in the biopsy-naïve and in the repeat biopsy setting. For the moment, it is impossible to make any recommendations on the best way to risk stratify patients before referring them for mpMRI.
Secondly, the large variability in the definition of csPCa precludes any definitive conclusion on the ability of mpMRI to rule out aggressive cancer. The issue of the most appropriate definition of csPCa on biopsy is complex, since biopsy results may accurately reflect neither tumour burden nor aggressiveness. Nonetheless, there is an urgent need to standardise the histological definition(s) of csPCa, to allow meaningful comparisons between studies.
Thirdly, the specificity of mpMRI remains moderate, and there is a substantial proportion of false positives in the lesions scored 3/5 or 4/5 [1 74 75] , even with the new PI-RADS v2 score [76] . In a series of 62 patients with 116 lesions biopsied under magnetic resonance/ultrasound fusion, the overall cancer detection rates for PI-RADS v2 scores of 3/5 and 4/5 were only 15.8% and 29.8%, respectively [77] . In theory, a triage test used to rule out a disease needs to be highly sensitive for this disease. However, if its specificity is too low, it will be clinically useless since most patients will be positive, whether they have the disease or not. Therefore, if mpMRI is to be used as a triage test in the future, there is a need to improve its specificity. This could be achieved by a continuous refinement of scores [78] . Promising results in characterising csPCa have also been reported with a quantitative analysis [79] .
Finally, all published studies were conducted in specialised centres. The broad use of mpMRI as a triage test assumes good interobserver reproducibility. Unfortunately, interobserver reproducibility of existing scoring systems remains moderate [62 63 80] even with the use of the PI-RADS v2 score [80 81] . Studies evaluating on a large scale the reproducibility of mpMRI findings between expert and nonexpert centres are currently lacking.
Three systematic reviews (including two meta-analyses) regarding the role of mpMRI in localised PCa have been published recently 4 5 6 . Crucially, all three reviews focused exclusively on the sensitivity of mpMRI-targeted, guided, or fusion biopsies in diagnosing overall PCa and csPCa, using TRUS-guided prostate biopsies as reference standards. The impact of systematic biopsies on the outcome was not addressed in any of the reviews, within either the index test or the reference standard. Our review had a totally different research question and objective, focusing on NPV of mpMRI to see if a negative mpMRI can avoid the need for a prostate biopsy. As MRI-targeted/guided/fusion biopsies are not relevant if the mpMRI was negative for cancer, it can be argued that the three reviews assessed a different index test altogether. As such, we believe that the findings of this review are novel and unique, and pave the way for further focused clinical studies.
The current study represents the first systematic review addressing the role of mpMRI as a triage test before biopsy. The review elements were developed in conjunction with a multidisciplinary panel of experts (EAU Prostate Cancer Guidelines Panel), which included a patient representative, and the review was performed robustly in accordance with recognised standards. However, it is limited by the major heterogeneity of the existing literature in patient population, study design, and definitions of positive mpMRI and csPCa. It highlighted further areas of research that could help in defining the best use of mpMRI in the early detection of aggressive PCa in the future.
Although mpMRI can detect aggressive PCa with excellent sensitivity, a definitive conclusion on its role as a triage test before prostate biopsy will be possible only when three main issues are addressed. Firstly, because NPV depends on prevalence, and because overall PCa and csPCa prevalence was highly variable in the published series, it becomes mandatory to define the optimal way to pre-evaluate the risk of csPCa in patients with a suspicion of PCa. Depending on the risk category, mpMRI could then be used to obviate biopsies or not. Secondly, there is a need for consensus definitions of csPCa on biopsy findings to allow interstudy comparisons. Thirdly, although efforts have been made to standardise mpMRI technical protocols and interpretation in the past few years [11 60 76] , there is still a crucial need to improve mpMRI specificity and inter-reader reproducibility.
This systematic review was performed under the auspices of:
The European Association of Urology Guidelines Office Board
The European Association of Urology Prostate Cancer Guideline Panel
Author contributions: Olivier Rouvière had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.
Study concept and design: Rouvière, Mottet, Cornford.
Acquisition of data: Rouvière, Moldovan, Van den Broeck, Yuan.
Analysis and interpretation of data: Rouvière, Moldovan, Van den Broeck, Lam.
Drafting of the manuscript: Rouvière, Moldovan, Van den Broeck, Lam.
Critical revision of the manuscript for important intellectual content: Bellmunt, van den Bergh, Bolla, Briers, Van den Broeck, Cornford, Cumberbatch, De Santis, Fossati, Gross, Henry, Joniau, Lam, Matveev, Moldovan, van der Poel, van der Kwast, Rouvière, Schoots, Wiegel, Mottet.
Statistical analysis: None.
Obtaining funding: None.
Administrative, technical, or material support: Yuan, Sylvester, Marconi.
Supervision: None.
Other: None.
Financial disclosures: Olivier Rouvière certifies that all conflicts of interest, including specific financial interests and relationships and affiliations relevant to the subject matter or materials discussed in the manuscript (eg, employment/affiliation, grants or funding, consultancies, honoraria, stock ownership or options, expert testimony, royalties, or patents filed, received, or pending), are the following: Bellmunt is a company consultant for Janssen, Astellas, Pierre Fabre, Genentech, Merck, Ipsen, Pfizer, Novartis, and Sanofi Aventis. He has received research support from Takeda, Novartis, and Sanofi, and received travel grants from Pfizer and Pierre Fabre. Bolla has received company speaker honoraria from Ipsen and Astellas, honoraria or consultation fees from Janssen, and fellowship and travel grants from Janssen, AstraZeneca, and Astellas. Briers has received grant and research support from Ipsen, European Association of Urology, and Bayer; is an ex officio board member for Europa UOMO; is an ethics committee and advisory group member for REQUITE; is a member patient advisory board member for PAGMI; and is a member of SCA and EMA PCWP. Cornford is a company consultant for Astellas, Ipsen, and Ferring. He receives company speaker honoraria from Astellas, Janssen, Ipsen, and Pfizer; participates in trials from Ferring; and receives fellowships and travel grants from Astellas and Janssen. De Santis is a company consultant for GlaxoSmithKline, Janssen, Bayer, Novartis, Pierre Fabre, Astellas, Amgen, Eisai Inc., ESSA, Merck, and Synthon; has received company speaker honoraria from Pfizer, Takeda, Sanofi Aventis, Shionogi, Celgene, and Teva OncoGenex; has participated in trials for Pierre Fabre, Astellas, Exelixis, Bayer, and Roche; has received fellowship and travel grants from Bayer, Novartis, Ferring, Astellas, Sanofi Aventis, and Janssen; has received grant and research support from Pierre Fabre; has received honoraria from AstraZeneca; and is associated with Amgen. Joniau is a company consultant for Astellas, Ipsen, Bayer, Sanofi, and Janssen; has received company speaker honoraria from Astellas, Amgen, Bayer, Sanofi, Janssen, and Ipsen; has participated in trials for Astellas, Janssen, and Bayer; has received fellowship and travel grants from Astellas, Amgen, Bayer, Sanofi, Janssen, Ipsen, and Pfizer; and has received grant and research support from Astellas, Bayer, and Janssen. Matveev has received company speaker honoraria from Sanofi and Astellas, has participated in trials for Astellas, Pfizer and Novartis. Lam is a company consultant for and has received company speaker honoraria from Pfizer, GSK, Astellas, and Ipsen. van der Poel is a company consultant for Intuitive Surgical, has participated in trials for Astellas and Steba Biotech, and has received grant and research support from Astellas. Rouvière is a company consultant for EDAP-TMS, Bracco, and Philips; has received company speaker honoraria from EDAP-TMS, Bracco, and Philips; and has participated in trials for EDAP-TMS and Bracco. Wiegel has received company speaker honoraria from Astellas, Takeda, Hexal, Ipsen, Janssen-Cilac, and Ferring. Mottet has received grant and research support from Takeda Pharmaceutical, Millenium, Astellas, Pierre Fabre, Sanofi, and Pasteur, and has received honoraria or consultation fees from Takeda Pharaceutical, Millenium, Jansen, Astellas, BMS, Bayer, Ipsen, Ferring, Novartis, Nuclétron, Pierre Fabre, Sanofi, and Zeneca. van den Bergh, Van den Broeck, Cumberbatch, Fossati, Gross, Henry, van der Kwast, Sylvester, Yuan, Schoots, Moldovan, and Marconi have nothing to disclose.
Funding/Support and role of the sponsor: None.
A correlation with radical prostatectomy specimens has demonstrated that multiparametric magnetic resonance imaging (mpMRI) has excellent sensitivity in detecting prostate cancer (PCa) with a Gleason score of ≥7 1 2 3 . As a result, prostate mpMRI is increasingly used in patients with a suspicion of PCa to localise abnormal areas before biopsy. A large body of literature has shown that targeted biopsies of suspicious lesions seen on mpMRI (TBx) improved the detection of clinically significant PCa (csPCa), at least in the repeat biopsy setting 4 5 6 . As a result, it is now recommended that an mpMRI is performed before repeat biopsy to allow TBx of suspicious lesions in addition to standard biopsies [7] .
Some authors have recently suggested that, besides improving csPCa detection, mpMRI could also be used as a triage test so that patients with negative mpMRI findings could obviate biopsy. Such a strategy remains highly controversial [8] and depends upon the negative predictive value (NPV) of mpMRI. Therefore, the European Association of Urology Prostate Cancer Guidelines Panel undertook this systematic review and meta-analysis to assess the NPV of mpMRI in patients with a suspicion of PCa and, thus, its potential role in eliminating unnecessary prostate biopsy.
Our primary aim was to systematically evaluate the performance of negative prebiopsy prostate mpMRI in predicting a negative biopsy result for overall PCa and csPCa in biopsy-naïve men and in men with previously negative biopsies. A further objective was to explore and define factors that may contribute to relevant thresholds in order to provide guidance for future studies.
The review was performed according to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) statement [9] . The review protocol was published in PROSPERO database ( http://www.crd.york.ac.uk/PROSPERO; registration number CRD42015021929). Databases searched included the Embase and OVID Medline databases, the Cochrane database of systematic reviews, and the Cochrane Central Register for Clinical Trials, covering from January 1, 2000 to February 13, 2016. Systematic or standard prostate biopsies were used as reference standards, with positive or negative cases of PCa being determined by histopathological examination. The detailed search strategy is presented in Supplement 1.
Included studies focused on men who were assessed for suspected PCa by mpMRI before undergoing prostate biopsy. Studies enrolling both biopsy-naïve men and men who had undergone previous negative biopsies were included. Prebiopsy prostate mpMRI was considered the index test and comprised T2-weighted imaging (T2WI) and at least one functional imaging technique (diffusion-weighted imaging [DWI], dynamic contrast-enhanced imaging [DCEI], or magnetic resonance spectroscopic imaging [MRSI]). For inclusion, studies had to report on false negatives and true negatives, in order to calculate NPV (ie, results of systematic/standard prostate biopsies when the mpMRI was negative). When available, false positive and true positive findings were also noted to calculate the positive predictive value (PPV) and the cancer prevalence. There was restriction neither on the biopsy technique (transrectal or transperineal) nor on the number of biopsy cores. Studies using radical prostatectomy specimens as reference standards were excluded, as were studies evaluating men with histologically proven PCa. Studies with less than 50 participants were excluded. No language restrictions were applied.
Two reviewers (P.C.M. and T.V.D.B.) independently screened all abstracts and full-text articles for eligibility. Disagreement was resolved by consensus or reference to an independent third party (L.M.). All screening was performed using a predefined eligibility form.
Using a data extraction form developed a priori, the same two reviewers independently extracted data concerning study methodology, patient characteristics, technical characteristics of the MR scanners, mpMRI protocol, mpMRI scoring system, definition of positive mpMRI, biopsy protocol, and definition of csPCa. Any discrepancies concerning data extraction were resolved by consensus or reference to an independent arbiter (O.R. or T.B.L.).
To assess the risk of bias (RoB), all included reports were reviewed using the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool for diagnostic accuracy studies [10] .
Outcome data regarding false negative and true negative values of mpMRI before prostate biopsy were recorded as reported by authors. When not available, data were indirectly derived from specificity, sensitivity, and prevalence values reported by authors using an online Bayesian statistics calculator ( http://www.medcalc.com/bayes.html ). Descriptive statistics were used to summarise baseline characteristics and outcomes, including median and interquartile range (IQR) for estimates of NPV across studies. A correlation between mpMRI NPV and a positive biopsy rate was established using the Pearson's correlation coefficient.
A meta-analysis was undertaken to calculate pooled NPV and PPV. To ensure appropriate clinical homogeneity of the studies included in the meta-analysis, we selected only the studies enrolling biopsy-naïve patients and/or patients with a history of negative biopsy, and fulfilling the following criteria that were defined a priori: (1) reference standard consisting of prostate biopsy with at least 10 samples on all patients; (2) mpMRI protocol comprising at least T2WI and DWI; (3) mpMRI results presented as a five-level score, using a subjective Likert scale or the Prostate Imaging Reporting Data System (PI-RADS) score [11] ; (4) definition of positive mpMRI as a score ≥3/5 or ≥4/5; and (5) results reported on a per patient basis. In addition, only studies defining csPCa as Gleason ≥7 cancers were selected for the meta-analysis assessing the mpMRI NPV for csPCa. A bivariate random-effects approach was employed using the Midas package in Stata 12 (StataCorp LP, College Station, TX, USA). Since the NPV decreases and the PPV increases as the prevalence increases, post-test probability estimates of NPV and PPV were reported for the given values of the prevalence based on Bayes’ theorem.
For other studies not included in the meta-analysis based on the criteria described above, a narrative synthesis of the data was performed. To explore and define clinical heterogeneity, subgroups were analysed at patient level based on the following variables: biopsy-naïve versus previous negative biopsy; patients with positive versus negative digital rectal examination (DRE); mpMRI performed with an endorectal versus without an endorectal coil; transrectal ultrasound (TRUS) versus template transperineal (TTP) biopsy approach; and ≤16 cores versus >16 cores as the reference standard. Studies reporting mpMRI NPV for patients with a prostate-specific antigen (PSA) level of ≤10 ng/ml were also reported separately.
The study selection process is depicted in the PRISMA flow diagram ( Fig. 1 ). A total of 2980 abstracts were retrieved. After abstract screening and removal of duplicates, 240 articles were eligible for full text screening, of which 48 studies were eligible for inclusion 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 .
Out of the 48 included studies, 42 were single-centre and six were multicentre studies. Thirty-four studies were prospective and six were retrospective, whilst the design of the rest was unclear. RoB assessment using QUADAS-2 was performed for each of the individual studies ( Fig. 2 A and B). Overall, the RoB was highly heterogeneous across studies for all criteria, except for the reference standard domain, in which RoB was low in most studies.
The 48 studies comprised a total of 9613 men who underwent prostate mpMRI followed by biopsy. The study and patient baseline characteristics are presented in Table 1 . The patient population consisted of biopsy-naive men in nine studies, men with at least one previous negative biopsy in 16 studies, and both biopsy-naïve men and men with a history of previous negative biopsy in nine studies. In 14 studies, the biopsy history of the patients was unclear.
Study | Study design | Period | Population | Pt Nb | Mean/median* age (yr) | Mean/median* PSA (ng/ml) | Mean/median* prostate volume (cm 3 ) | Magnetic field strength | MR pulse sequences | Endorectal coil | MR score | Definition of positive MRI | Reference standard |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Hauth (2015) [25] | Prospective | 2011–2013 | FB | 94 | 64 (43–83) | 9 (3–31) | 51 (17–140) | 1.5 T | T2WI/DWI/DCEI/MRSI | No | PI-RADS v1 | ≥3 | 11–13-core TRUS SBx + TBx |
Lamb (2015) [36] | Retrospective | 2013–2013 | FB & PNB | 173 | NR | NR | NR | 1.5 T | T2WI/DWI | NR | NR | NR | 12-core TRUS SBx |
Brock (2015) [15] | Prospective | 2013–2014 | PNB | 168 | 64* (IQR 59–70) | 9.2* (IQR 6.7–13.4) | 55.4* (IQR 42–80) | 3 T | T2WI/DWI/DCEI | No | PI-RADS v1 | NR | 12/24-core TRUS SBx + TBx |
Grenabo Bergdahl (2016) [22] | Prospective | 2013–2014 | FB & PNB | 83 | 69.3* (IQR 69–69.6) | 1.6* (IQR 0.9–2.7) | NR | 3 T | T2WI/DWI/DCEI/MRSI | No | PI-RADS v1 | ≥3 | 10-core TRUS SBx + TBx |
Wang (2015) [58] | Prospective | 2002–2009 | FB & PNB | 586 | 70 (26–91) | 11.11* (0.02–9794) | NR | 1.5 T | T2WI/DWI/DCEI/MRSI | Yes | PI-RADS v1 | ≥3 | TRUS SBx |
Pepe (2015) [41] | Prospective | 2011–2014 | PNB | 100 | 64* | 8.6* (4.2–10) | NR | 3 T | T2WI/DWI/DCEI/MRSI | No | PI-RADS v1 | ≥4 | TPBx + TBx |
Panebianco (2015) [39] | Prospective | 2011–2014 | FB (61.62%) & PNB (38.34%) | 925 (1140 total cohort) |
NR | NR | NR | 3 T | T2WI/DWI/DCEI | Yes | PI-RADS v1 | NR | 14-core TRUS SBx; 45-core sat TPBx + TBx |
Radtke (2015) [46] | Prospective | 2013–2013 | FB (63.3%) & PNB (36.7%) | 294 | 64* (60–71) | 7.3 (6.0) | 47 (37.5) | 3 T | T2WI/DWI/DCEI | No | PI-RADS v1 | PI-RADS ≥2; PI-RADS ≥3; PI-RADS ≥4; PI-RADS = 5; |
24-core TPBx + TBx |
Itatani (2014) [27] | Retrospective | 2004–2007 | NR | 193 | 68.9 (8.4); 70* (47–89) | 11.8 (15.9); 7.9* (1.22–159) | NR | 1.5 T | T2WI/DWI/DCEI | No | 1–5 scale (Likert) | ≥3 | 12–14-core TRUS SBx |
Porpiglia (2014) [44] | Prospective | 2011–2013 | PNB | 170 | 65* (60–70) | 6.9* (5.2–9.8) | 42* (36–48) | 1.5 T | T2WI/DWI/DCEI | Yes | Dichotomous | Positive: at least 2/3 MR seq. with suspicious findings | 18–24-core TRUS SBx (volume dependent) |
Thompson (2014) [56] | Prospective | 2012–2013 | FB (88%) & PNB (12%) | 150 | 62.4* (IQR 55.0–66.4) | 5.6* (IQR 4.5–7.5) | 40* (IQR 30–57) | 1.5 T (47%) & 3 T (53%) | T2WI/DWI/DCEI | No | PI-RADS v1 | ≥3 | Median of 30 TPBx (volume dependent) |
Pokorny (2014) [43] | Prospective | 2012–2013 | FB | 223 | 63* (IQR 57–68) | 5.3* (IQR 4.1–6.6) | 41* (IQR 30–59) | 3 T | T2WI/DWI/DCEI | No | PI-RADS v1 | ≥3 (primary); ≥4 |
12-core TRUS SBx + TBx |
Petrillo (2014) [42] | Prospective | 2009–2010 | NR | 136 | NR | NR | NR | 1.5 T | T2WI/DWI/MRSI | Yes | 1–5 scale (Likert) | ≥3 | 12–16-core TRUS SBx (volume + PSA dependent) |
Javali (2014) [29] | Retrospective | 2002–2011 | NR | 140 | Control: 62.4 (10.5); Study: 62.9 (12.1) | Control: 6.8 (2.3); Study: 6.87 (2.6) | Control: 44 (14.2); Study: 43 (18.4) | 1.5 T | T2WI/MRSI | Yes | Dichotomous | Cit/[Cho + Cr] < 1.2 | 6-core TRUS SBx ( n = 69), 12-core TRUS SBx ( n = 119) |
Abd-Alazeez (2014) [13] | Prospective | 2007–2011 | FB | 129 | 62* (41–82) | 5.8* (1.2–20) | 40* (16–137) | 1.5 & 3 T | T2WI/DWI/DCEI | No | PI-RADS v1 | ≥3 (primary); ≥4 |
20-core TPBx |
Abd-Alazeez (2014) [12] | Retrospective | NR | PNB | 54 | 64* (39–75) | 10* (2–23) | 53* (19–136) | 1.5 & 3 T | T2WI/DWI/DCEI | No | PI-RADS v1 | ≥3 (primary); ≥4 |
≥20-core TPBx + TBx ( n = 15) |
Matsuoka (2014) [37] | Prospective | 2007–2012 | NR | 135 | 67* (50–80) | 7.0* (2.9–19.8) | 25.4* (12.7–90.2) | 1.5 T | T2WI/DWI | No | 1–5 scale (Likert) | ≥3 | 14-core TRUS SBX |
Junker (2013) [30] | Retrospective | 2011–2013 | PNB | 73 | 62 (7.4) | 7.0* (5.1–12.9) | 45* (34–61) | 3 T | T2WI/DWI/DCEI | No | PI-RADS | PI-RADS ≥10 and ≥11 for all PCa PI-RADS ≥13 for significant PCa |
10-core TRUS SBx + TBx |
Busetto (2013) [16] | Prospective | 2010–2012 | PNB | 163 | 66.4 (5.3) | 6.8 (1.6) | NR | 3 T | T2WI/DWI/DCEI/MRSI | Yes | NR | NR | 10-core TRUS SBx + TBx |
Rais-Bahrami (2013) [47] | Prospective | 2007–2012 | NR | 583 | 61.3 (8.4) | 9.9 (13.1) | NR | 3 T | T2WI/DWI/DCEI/MRSI | Yes | 1–4 scale (Likert) | ≥2 ≥3 |
12-core TRUS SBx + TBx |
Kuru (2013) [34] | Prospective | 2010–2011 | FB (51%) & PNB (49%) | 347 | 65.3 (42–82) | 9.85 (0.5–104) | 48.7 (9–180) | 3 T | T2WI/DWI/DCEI | No | 1–3 scale (Likert) | ≥2 | 12–36-core TRUS SBx (volume dependent) + TBx |
Ferda (2013) [20] | Prospective | NR | NR | 164 | (49–74) | (4.2–123) | NR | 3 T | T2WI/DWI/DCEI/MRSI | No | NR | In house | TRUS SBx |
Ganie (2013) [21] | NR | 2007–2009 | PNB | 87 | NR | NR | NR | 1.5 T | T2WI/MRSI | Yes | MRSI Cho/Cit ratio | In house | 6 core TRUS SBx + MRI TBx |
Vinet (2013) [57] | Prospective | 2009–2011 | FB | 69 | NR | 5.2* (3.2–28) | NR | 1.5 T (35 pts) & 3 T (34 pts) | T2WI/DWI/DCEI | No | 1–5 scale (Likert) | ≥3 | 12-core TRUS SBx + TBx |
Numao (2013) [38] | Prospective | 2006–2010 | FB | 351 | 65* (59–70) | 6.3* (4.9–9.1) | 32* (24–42) | 1.5 T | T2WI/DWI/DCEI (no DCEI in 42 pts) | No | 1–5 scale (Likert) | ≥3 | 3D 26-core (12 TRUS SBx + 14 TPBx – 203 pts); 3D 14-core (6 TRUS SBx + 8 TPBx – 102 pts); TPBx 14 core (46 pts) |
Belas (2012) [14] | Prospective | 2010–2011 | FB | 71 | 66* (47–76) | 7* (4–10) | 45* (15–150) | 1.5 T | T2WI/DWI/DCEI | No | TZ: 0–4 scale PZ: 0–10 scale |
TZ: >2 PZ: >6 |
12-core TRUS SBx + TBx |
Ibrahiem (2012) [26] | Prospective | 2008–2009 | FB | 100 | 65.03 (7.13) | 26.3 (24.2) | 60.09 (28.7) | 1.5 T | T2WI/DWI | No | NR | In house | 12-core TRUS SBX |
Sciarra (2012) [51] | Prospective | 2008–2011 | PNB | 84 | 64.09 (46–76) | 7.07 (4.2–15.5) | NR | 3 T | T2WI/DWI/DCEI/MRSI | Yes | NR | NR | 10-core TRUS Bx + TBx |
Portalez (2012) [45] | Prospective | 2011 | PNB | 129 | 64.7 (47–79) | 9.6 (2.7–40) | 51.1 (12–192) | 1.5 T | T2WI/DWI/DCEI | Mixed | 1–5 scale (Likert) PI-RADS |
Likert ≥3 PI-RADS ≥9 |
10–12-core TRUS SBx + TBx |
Watanabe (2012) [59] | Prospective | 2004–2008 | NR | 1448 | 72 (7.5) | NR | NR | 1.5 T | T2WI/DWI | No | NR | ADC value ≤1.35 × 10 −3 mm 2 /s | 8-core TRUS SBx + TBx |
Tamada (2011) [54] | Retrospective | 2006–2009 | NR | 50 | 70 (40–84) | 6.84* (4.06–9.94) | NR | 1.5 T | T2WI/DWI/DCEI | No | NR | In house | 12-core TRUS SBx |
Choi (2011) [18] | NR | 2009–2010 | NR | 51 | 67.16 (56–90) | 14.16 (1.02–38.9) | 42.98 (13.8–77.3) | 3 T | T2WI/DWI | NR | NR | NR | 10–12-core TRUS SBx + TBx |
Iwazawa (2011) [28] | Retrospective | 2008–2009 | NR | 178 | 68.8 (41–86) | 20.51 (4.04–568.5) | NR | 1.5 T | T2WI/DWI/DCEI | NR | 1–4 scale (Likert) | NR | 10–12-core TRUS SBx (TBx included in SBx chart) |
Rouse (2011) [48] | Prospective | 2005–2007 | PNB | 114 | 63.6 (41–83) | 13.4 (0–228) | NR | 1.5 T | T2WI/DWI/DCEI | NR | 1–5 scale (Likert) | ≥3 | TRUS SBx |
Haffner (2011) [23] | Prospective | 2005–2009 | FB | 555 | 64* (47–83) | 6.75* (0.18–100) | 46* (15–200) | 1.5 T | T2WI/DCEI | No | 1–5 scale (Likert) | ≥3 | 10-core TRUS SBx + TBx |
Panebianco (2010) [40] | Prospective | 2007–2009 | PNB | 150 | 61.2 (46–78) | 9.42 (3.91) | 41.17 (7.47) | 1.5 T | T2WI/DCEI/MRSI | Yes | NR | In house | 10-core TRUS SBx (TBx included in SBx chart) |
Roy (2010) [49] | Not specified | 2011–2009 | FB (53%) & PNB (47%) | 103 | 63 (52–78) | 7* | NR | 3 T | T2WI/DWI/DCEI | Yes | NR | NR | 8-core TRUS SBx + TBx |
Testa (2010) [55] | Not specified | 2007 | PNB | 54 | 63.9 (52–76) | 11.4 (3–42) | 59.3 (30–150) | 1.5 T | T2WI/MRSI | Yes | 1–3 scale (Likert) | ≥2 | 12-core TRUS SBx + TBx |
Sciarra (2010) [52] | Prospective | 2007–2009 | PNB | 110 | 63.5 (49–74) | NR | NR | 1.5 T | T2WI/DCEI/MRSI | Yes | NR | In house | 10-core TRUS SBx + TBx |
Kitajima (2010) [31] | Prospective | 2008–2009 | NR | 53 | 69* (56–84) | 11.1* (4.2–112.1) | NR | 3 T | T2WI/DWI/DCEI | No | 1–5 scale (Likert) | ≥3 | 20-core TPBx |
Labanaris (2010) [35] | Prospective | 2004–2008 | PNB | 260 | NR | NR | NR | 1 T | T2WI/DWI/DCEI | Yes | Dichotomous | In house | 18-core TRUS SBx |
Kumar (2009) [32] | NR | NR | NR | 61 | 65.3 (9.3) | 16.5 (0.21–155) | NR | 1.5 T | T2WI/MRSI | Yes | NR | (Cit/(Cho + Cr) ≤ 1.2 | TRUS Bx |
Schmuecking (2009) [50] | NR | NR | FB & PNB | 67 | 68 | 11.5 | NR | 1.5 T | T2WI/DCEI | No | NR | NR | 20-core Bx |
Cheikh (2009) [17] | Retrospective | 2005–2008 | PNB | 93 | 63.2 (52–74) | 9.63 (1.6–40) | NR | 1.5 T | T2WI/DCEI | No | Dichotomous | In house | 12-core TRUS SBx + TBx |
Cirillo (2008) [19] | Prospective | 2004–2006 | PNB | 54 | 65.5 (5.2) | 10.8 (7.5) | NR | 1.5 T | T2WI/MRSI | Yes | Dichotomous | In house | 10-core TRUS SBx + TBx |
Kumar (2007) [33] | Prospective | 2003–2005 | NR | 83 | NR | NR | NR | 1.5 T | T2WI/MRSI | Yes | NR | NR | 12-core TRUS SBx + TBx |
Squillaci (2005) [53] | Prospective | 2004–2005 | NR | 65 | NR | NR | NR | 1.5 T | T2WI/DCEI/MRSI | No | 1–3 scale (Likert) | ≥2 | 10-core TRUS SBx + TBx |
Hara (2005) [24] | Prospective | 2003–2004 | FB | 90 | 67.2 (NR) | NR | NR | 1.5 T | T2WI/DCEI | No | 1–3 scale (Likert) | ≥2 = 3 |
14-core TRUS SBx |
The magnetic field strength was 1, 1.5, and 3 T in one, 28, and 15 studies, respectively. Four studies used both 1.5 and 3 T MR systems. DWI and DCEI were used in 36 and 35 studies, respectively. Nineteen studies also added MRSI. An endorectal coil was used in 18 studies. The definition of positive mpMRI varied across studies. The PI-RADS v1 score was used in 12 studies, a five-level subjective (Likert) score was used in eight studies, and one study reported data based on the two scoring systems. In-house criteria were used in 13 studies for defining positive mpMRI, and five studies used a dichotomous definition. Nine studies did not report on the criteria for positive mpMRI. No study used the PI-RADS v2 score.
Regarding the reference standard, TRUS-guided biopsies were used in 39 studies, TTP biopsies in six studies, and mixed TRUS-guided and TTP biopsies in two studies. In one study, the biopsy approach was unclear. The number of cores per biopsy procedure was ≤16 in 30 studies, >16 in nine studies, and variable among patients in three studies. For six studies, the number of biopsy cores taken was unclear.
At patient level, the median biopsy positivity rate (ie, cancer prevalence) was 50.4% (IQR, 36.4–57.7%) for overall cancer and 32.9% (IQR, 28.1–37.2%) for csPCa ( Table 2 ). The median mpMRI NPV was 82.4% (IQR, 69.0–92.4%) for overall cancer and 88.1% (IQR, 85.7–92.3) for csPCa. NPV significantly decreased when cancer prevalence increased, both for overall cancer ( r = –0.64, p < 0.0001) and csPCa ( r = –0.75, p = 0.032; Fig. 3 ). In addition, NPV was highly dependent on the definition used for csPCa, with differences of up to 21% when several definitions were used in the same dataset [12 13 38 47 48] .
Study | Overall PCa prevalence (%) | Reporting level | Multiparametric MRI performance for PCa detection | Definition of csPCa | csPCa prevalence | Multiparametric MRI performance for csPCa detection | ||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
TN | FN | TP | FP | NPV | PPV | TN | FN | TP | FP | NPV | PPV | |||||
Hauth (2015) [25] | 45.7 | Patient | 6 | 1 | 42 | 45 | 85.7% | 48.3% | Low grade: GS ≤ 6 High grade: GS ≥ 7 |
NR | NR | NR | NR | NR | NR | NR |
Lesion | 59 | 13 | 55 | 73 | 81.9% | 43% | ||||||||||
Lamb (2015) [36] | 65.9 | Patient | 23 | 22 | 92 | 36 | 51.1% | 71.9% | GS ≥ 7 | 50.9% | 31 | 14 | 71 | 57 | 68.9% | 55.5% |
Brock (2015) [15] | 42.3 | Patient | 17 | 7 | 56 | 88 | 70.8% | SBx: 38.8% TBx: 22.2% Duo: 44.4% |
Epstein: GS > 6 and/or max CCL ≥50% | 24.4% | SBx: 21 | SBx: 3 | SBx: 38 TBx: 27 duo: 47 |
SBx: 106 TBx: 117 duo: 97 |
87.5% | SBx: 26.4% TBx: 18.8% duo: 32.6% |
Grenabo Bergdahl (2016) [22] | 33.7 | Patient | 36 | 7 | 19 | 21 | 83.7% | 47.5% | Clinically insignificant PCa: T1c, PSAd < 0.15, GS < 7, ≤2 positive cores, and unilateral cancer | NR | NR | NR | NR | NR | NR | NR |
Wang (2015) [58] | 58 | Patient | 165 | 8 | 332 | 81 | 95.4% | 80.4% | NR | NR | NR | NR | NR | NR | NR | NR |
Pepe (2015) [41] | 37 | Patient | 23 | 8 | 29 | 40 | 74.2% | 42% | GS ≥ 7 or GS 6 with CCL ≥ 50% | NR | NR | NR | NR | NR | 100% | 55.8% |
Panebianco (2015) [39] | 74.7 | Patient | Group A (satBx): 104 | Group A (satBx): 43 | Group A: 186 | Group A: 22 | Group A (satBx): 70.7% | Group A: 89.4% | NR | 60% | Group A: 147 | Group A: 0 | Group A: 183 | Group A: 25 | Group A: 100% | Group A: 88% |
Group B (TRUSGB NR TRUS G satBx): 93 | Group B (TRUSGB NR TRUS G satBx): 37 | Group B: 417 before and 425 after satBx | Group B: 23/440 and 15/440 after satBx. | Group B (TRUSGB–TRUS G satBx): 71.5% | Group B: 94.8% before and 96.6% after satBx | 71.9% | Group B: 130 | Group B: 0 | Group B: 410 |
Group B: 30 | Group B: 100% | Group B: 93.2% | ||||
Radtke (2015) [46] | 51 | Patient | ≥2/5: 80 ≥3: 103 ≥4: 138 = 5: 142 |
≥2/5: 18 ≥3/5: 38 ≥4/5: 78 = 5/5: 126 |
≥2/5: 132 ≥3/5: 112 ≥4/5: 72 = 5/5: 24 |
≥2/5: 64 ≥3/5: 41 ≥4/5: 6 = 5/5: 2 |
≥2/5: 81.6% ≥ 3/5: 73.1% ≥ 4/5: 63.9% = 5/5: 53% |
≥2/5: 67.4% ≥ 3/5: 73.2% ≥ 4/5: 92.3% = 5/5: 92.3% |
GS ≥ 7 | 29.3% | ≥2/5: 91 ≥3/5: 124 ≥4/5: 183 = 5/5: 203 |
≥2/5: 7 ≥3/5: 17 ≥4/5: 33 = 5/5: 65 |
≥2/5: 79 ≥3/5: 69 ≥4/5: 53 = 5/5: 21 |
≥2/5: 117 ≥3/5: 84 ≥4/5: 25 = 5/5: 5 |
≥2/5: 92.2% ≥3/5: 87.9% ≥4/5: 84.7% = 5/5: 75.8% |
≥2/5: 40.3% ≥3/5: 45.1% ≥4/5: 68% = 5/5: 80.7% |
Itatani (2014) [27] | 13 | Patient | 168 | 25 | NR | NR | 87% | NR | (1) PSAd ≥ 0.1 or GP 4/5 or ≥ 3/6 pos cores; max CCL < 50% (2) PSAd ≥ 0.15 or GP 4/5 or max core length invasion < 3 mm (min 6 cores) |
NR | NR | NR | NR | NR | NR | NR |
Porpiglia (2014) [44] | 30.6 | Patient | 107 | 5 | 47 | 11 | 95.5% | 81% | NR | NR | NR | NR | NR | NR | NR | NR |
Thompson (2014) [56] | 61.3 | Patient | 35 | 16 | 76 | 23 | 68.6% | 76.7% | Moderate or high risk Moderate risk: GS 7 (GP4 >5%) and <50% of positive cores or GS 6–7 (GP4 ≤ 5%) and either ≥30% of positive cores or max core length invasion ≥8 mm High risk: GS ≥ 7 (GP4 > 5%); ≥50% + cores or GS ≥ 8 |
34% | 49 | 2 | 49 | 50 | 96% | 49.5% |
Pokorny (2014) [43] | 63.7 | Patient | ≥3/5: 56 ≥4/5: 74 |
≥3/5: 25 ≥4/5: 40 |
≥3/5: 101 ≥4/5: 86 |
≥3/5: 41 ≥4/5: 23 |
≥3/5: 69.1% ≥4/5: 64.9% |
≥3/5: 71.1% ≥4/5: 78.9% |
NR | NR | NR | NR | NR | NR | NR | NR |
Petrillo (2014) [42] | 18.4 | Patient | 56 | 4 | 21 | 55 | 93% | 28% | NR | NR | NR | NR | NR | NR | NR | NR |
Javali (2014) [29] | 16.4 | Patient | 49 | 1 | 22 | 68 | 98% | 24.4% | NR | NR | NR | NR | NR | NR | NR | NR |
Abd-Alazeez (2014) [13] | 54.7 | Lobe | ≥3/5: 33 | ≥3/5: 14 | ≥3/5: 127 | ≥3/5: 84 | ≥3/5: 70% | ≥3/5: 60% | Def 1: GS ≥ 4 + 3 and/or max CCL ≥ 6 mm Def 2: GS ≥ 3 + 4 and/or max CCL ≥ 4 mm Def 3: GS ≥ 4 + 3 Def 4: GS ≥ 3 + 4 Def 5: max CCL ≥ 6 mm Def 6: max CCL ≥ 4 mm |
Def 1: NR Def 2: 44.2% Def 3: 23.2% Def 4: 36% Def 5: 32.9% Def 6: 39.5% |
Def 1: 46 Def 2: 42 Def 3: 47 Def 4: 43 Def 5: 46 Def 6: 43 |
Def 1: 1 Def 2: 5 Def 3: 0 Def 4: 4 Def 5: 1 Def 6: 4 |
Def 1: 45 Def 2: 72 Def 3: 13 Def 4: 50 Def 5: 39 Def 6: 59 |
Def 1: 166 Def2: 139 Def 3: 198 Def 4: 161 Def 5: 172 Def 6: 152 |
Def 1: 98 Def 2: 89 Def 3: 100 Def 4: 92 Def 5: 98 Def 6: 91 |
Def 1: 21 Def 2: 34 Deg 3: 6 Def 4: 24 Def 5: 19 Def 6: 28 |
≥4/5: 87 | ≥3/5: 62 | ≥3/5: 79 | ≥3/5: 30 | ≥3/5: 58% | ≥3/5: 73% | Def 1: 140 Def 2: 124 Def 3: 148 Def 4: 133 Def 5: 141 Def 6: 131 |
Def 1: 9 Def 2: 25 Def 3: 1 Def 4: 16 Def 5: 8 Def 6: 18 |
Def 1: 37 Def 2: 52 Def 3: 12 Def 4: 38 Def 5: 32 Def 6: 45 |
Def 1: 72 Def 2: 57 Def 3: 97 Def 4: 71 Def 5: 77 Def 6: 64 |
Def 1: 94 Def 2: 83 Def 3: 99 Def 4: 89 Def 5: 95 Def 6: 88 |
Def 1: 34 Def 2: 48 Def 3: 11 Def 4: 35 Def 5: 30 Def 6: 42 |
|||||
Abd-Alazeez (2014) [12] | 47.2 | Lobe | ≥3/5: 26 | ≥3/5: 13 | ≥3/5: 38 | ≥3/5: 31 | ≥3/5: 66% | ≥3/5: 55% | Def 1: GS ≥ 4 + 3 and/or max CCL ≥ 6 mm Def 2: GS ≥ 3 + 4 and/or max CCL ≥ 4 mm Def 3: GS ≥ 4 + 3 Def 4: GS ≥ 3 + 4 Def 5: max CCL ≥ 6 mm Def 6: max CCL ≥ 4 mm |
Def 1: 18.5% Def 2: 31.5% Def 3: 4.6% Def 4: 21.3% Def 5: 16.7% Def 6: 25% |
Def 1: 37 Def 2: 31 Def 3: 39 Def 4: 36 Def 5: 37 Def 6: 32 |
Def 1: 2 Def 2: 8 Def 3: 0 Def 4: 3 Def 5: 2 Def 6: 7 |
Def 1: 18 Def 2: 26 Def 3: 5 Def 4: 20 Def 5: 16 Def 6: 20 |
Def 1: 51 Def 2: 43 Def 3: 64 Def 4: 49 Def 5: 53 Def 6: 49 |
Def 1: 95 Def 2: 79 Def 3: 100 Def 4: 92 Def 5: 95 Def 6: 82 |
Def 1: 26 Def 2: 38 Def 3: 7 Def 4: 29 Def 5: 23 Def 6: 29 |
≥4/5: 49 | ≥4/5: 25 | ≥4/5: 26 | ≥4/5: 8 | ≥4/5: 66% | ≥4/5: 76% | Def 1: 70 Def 2: 63 Def 3: 73 Def 4: 68 Def 5: 70 Def 6: 64 |
Def 1: 4 Def 2: 11 Def 3: 1 Def 4: 6 Def 5: 4 Def 6: 10 |
Def 1: 16 Def 2: 23 Def 3: 4 Def 4: 17 Def 5: 14 Def 6: 17 |
Def 1: 18; Def 2: 11 Def 3: 30 Def 4: 17 Def 5: 20 Def 6: 17 |
Def 1: 94 Def 2: 85 Def 3: 99 Def 4: 92 Def 5: 94 Def 6: 86 |
Def 1: 47 Def 2: 67 Def 3: 12 Def 4: 50 Def 5: 41 Def 6: 49 |
|||||
Matsuoka (2014) [37] | 64.8 | Lobe | 46 | 49 | 149 | 26 | 48.4% | 85.1% | NR | NR | NR | NR | NR | NR | NR | NR |
Junker (2013) [30] | 53.4 | Patient | ≥10/15: 21 ≥11/15: 28 |
≥10/15: 4 ≥11/15: 12 |
≥10/15: 35 ≥11/15: 27 |
≥10/15: 13 ≥11/15: 6 |
≥10/15: 84% ≥11/15: 70% |
≥10/15: 72.9% ≥11/15: 81.8% |
GS ≥ 4 + 3 | 13.7% | ≥13: 54 | ≥13: 2 | ≥13: 8 | ≥13: 9 | ≥13: 96.4% | ≥13: 47% |
Busetto (2013) [16] | 41.7 | Patient | 59 | 7 | 61 | 36 | 89% | 63% | NR | NR | NR | NR | NR | NR | NR | NR |
Rais-Bahrami (2013) [47] | 54.2 | Patient | ≥2/4 : 80 | ≥2/4: 275 | ≥2/4: 187 | ≥2/4: 275 | ≥2/4: 66% | ≥2/4: 59% | GS ≥ 7: GS ≥ 8 |
31.7% | NR | NR | NR | NR | GS ≥ 7: 91% GS ≥ 8: 91% |
GS ≥ 7: 38% GS ≥ 8: 18% |
≥3/4: 251 | ≥3/4: 76 | ≥3/4: 16 | ≥3/4: 76 | ≥3/4: 51% | ≥3/4: 82% | NR | NR | NR | NR | GS ≥ 7: 75% GS ≥ 8: 91% |
GS ≥ 7: 67% GS ≥ 8: 41% |
|||||
Kuru (2013) [34] | 57.6 | Patient | 80 | 14 | 67 | 186 | 85.1% | 73.5% | NR | NR | NR | NR | NR | NR | NR | NR |
Ferda (2013) [20] | 51.2 | Patient | 52 | 2 | 82 | 28 | 96.3% | 74.5% | NR | NR | NR | NR | NR | NR | NR | NR |
Ganie (2013) [21] | 74.7 | Patient | 13 | 3 | 62 | 9 | 59.1% | 95.4% | NR | NR | NR | NR | NR | NR | NR | NR |
Vinet (2013) [57] | 49.3 | Patient | ≥3/5: 11 | ≥3/5: 6 | ≥3/5: 28 | ≥3/5: 24 | ≥3/5: 64.7% | ≥3/5: 53.8% | NR | NR | NR | NR | NR | NR | NR | NR |
≥4/5: 22 | ≥4/5: 11 | ≥4/5: 23 | ≥4/5: 13 | ≥4/5: 66.7% | ≥4/5: 63.8% | NR | NR | NR | NR | NR | NR | NR | NR | |||
Numao (2013) [38] | 45 | Patient | 137 | 57 | 101 | 56 | 70.6% | 64.3% | Def 1: GS ≥4 + 3 and/or ≥20% positive cores and/or max CCL ≥5 mm Def 2: GS ≥ 3 + 4 and/or ≥20% + cores and/or max CCL ≥5 mm Def 3: GS ≥ 3 + 4 and/or ≥20% + cores |
Def 1: 33.3% Def 2:37.8% Def 3: 35.8% |
Def 1: 74 Def 2: 65 Def 3: 69 |
Def 1: 83 Def 2: 92 Def 3: 88 |
Def 1: 160 Def 2: 153 Def 3: 156 |
Def 1: 34 Def 2: 41 Def 3: 38 |
Def 1: 82.4% Def 2: 78.8% Def 3: 80.4% |
Def 1: 58.8% Def 2: 58.5% Def 3: 56% |
Belas (2012) [14] | 53.5 | Patient | 22 | 12 | 23 | 13 | 64.7% | 63.8% | NR | NR | NR | NR | NR | NR | NR | NR |
Ibrahiem (2012) [26] | 73.9 | Patient | 14 | 11 | 57 | 10 | 56% | 85.1% | NR | NR | NR | NR | NR | NR | NR | NR |
Sciarra (2012) [51] | 34.5 | Patient | 41 | 4 | 25 | 14 | 91.1% | 64.1% | NR | NR | NR | NR | NR | NR | NR | NR |
Portalez (2012) [45] | 48.1 | Lesion | Likert: 357 | Likert: 50 | Likert: 81 | Likert: 50 | Likert: 95% | Likert: 38% | Max CCL >3 mm and/or GG 4/5 | NR | NR | NR | NR | NR | NR | NR |
PI-RADS: 404 | PI-RADS: 47 | PI-RADS: 34 | PI-RADS: 47 | PI-RADS: 95% | PI-RADS: 58% | |||||||||||
Watanabe (2012) [59] | 48.1 | Patient | 485 | 73 | 624 | 266 | 86.9% | 70.1% | NR | NR | NR | NR | NR | NR | NR | NR |
Tamada (2011) [54] | 70 | Patient | 12 | 6 | 29 | 3 | 67% | 91% | NR | NR | NR | NR | NR | NR | NR | NR |
Region | 277 | 48 | 55 | 20 | 85% | 73% | ||||||||||
Choi (2011) [18] | 70.6 | Patient | 9 | 5 | 31 | 6 | 64.2% | 75.7% | NR | NR | NR | NR | NR | NR | NR | NR |
Iwazawa (2011) [28] | 40.5 | Region | 887 | 86 | 232 | 219 | 91.1% | 51.4% | NR | NR | NR | NR | NR | NR | NR | NR |
Rouse (2011) [48] | 33.7 | Sextant | 145 | 11 | 74 | 22 | 92.9% | 77.1% | GS ≥ 7: Def 1: ≥3 mm Def 2: ≥5 mm |
Def 1: 26.6% Def 2: 26.2% |
Def 1: 153 Def 2: 153 |
Def 1: 3 Def 2: 3 |
Def 1: 64 Def 1: 63 |
Def 1: 32 Def 2: 33 |
Def 1: 98.1% Def 2: 98.1% |
Def 1: 68.1% Def 2: 67% |
59.6 | Patient | 24 | 14 | 54 | 22 | 63.2% | 71.1% | Def 1: 41.2% Def 2: 36.8% |
Def 1: 30 Def 2: 31 |
Def 1: 4 Def 2: 3 |
Def 1: 43 Def 2: 39 |
Def 1: 4 Def 2: 3 |
Def 1: 88.2% Def 2: 91.2% |
Def 1: 53.8% Def 2: 48.8% |
||
Haffner (2011) [23] | 54.4 | Patient | 154 | 50 | 240 | 111 | 75.4% | 68.3% | NR | NR | NR | NR | NR | NR | NR | NR |
Panebianco (2010) [40] | 42.7 | Patient | NR | NR | NR | NR | 95.1% | 88.2% | NR | NR | NR | NR | NR | NR | NR | NR |
Roy (2010) [49] | 55.9 | Patient | NR | NR | NR | NR | 71% | 75% | NR | NR | NR | NR | NR | NR | NR | NR |
Testa (2010) [55] | 40.7 | Patient | NR | NR | NR | NR | 79.3% | 64% | NR | NR | NR | NR | NR | NR | NR | NR |
Sciarra (2010) [52] | 50 | Patient | 61 | 4 | 66 | 9 | 93.8% | 88% | NR | NR | NR | NR | NR | NR | NR | NR |
Kitajima (2010) [31] | 56.6 | Patient | 311 | 19 | 80 | 14 | 92.2% | 85.1% | NR | NR | NR | NR | NR | NR | NR | NR |
Labanaris (2010) [35] | 73.9 | Patient | 17 | 73 | 96 | 74 | 81.11% | 56.47% | NR | NR | NR | NR | NR | NR | NR | NR |
Kumar (2009) [32] | 21.7 | Patient | 39 | 3 | 10 | 8 | 92.8% | 55% | NR | NR | NR | NR | NR | NR | NR | NR |
Schmuecking (2009) [50] | NR | Lobe | NR | NR | NR | NR | 96% | 61% | NR | NR | NR | NR | NR | NR | NR | NR |
Cheikh (2009) [17] | 24.7 | Patient | 36 | 12 | 11 | 34 | 80% | 22.9% | NR | NR | NR | NR | NR | NR | NR | NR |
Cirillo (2008) [19] | 31.5 | Patient | 19 | 0 | 17 | 18 | 100% | 48.6% | NR | NR | NR | NR | NR | NR | NR | NR |
Kumar (2007) [33] | 13.3 | Patient | 39 | 0 | 11 | 33 | 100% | 25% | NR | NR | NR | NR | NR | NR | NR | NR |
Squillaci (2005) [53] | 50.8 | Patient | 29% | 8% | 25% | 3% | 89% | 80% | NR | NR | NR | NR | NR | NR | NR | NR |
Hara (2005) [24] | 41.5 | Patient | ≥2/3: 40 = 3/3: 47 |
≥2/3: 4 = 3/3: 8 |
≥2/3 30 = 3/3: 26 |
≥2/3: 8 = 3/3: 1 |
≥2/3: 90% = 3/3: 85% |
≥2/3: 78.9% = 3/3: 96.3% |
NR | NR | NR | NR | NR | NR | NR | NR |
Cancer prevalence tended to be higher and mpMRI NPV lower in the biopsy-naïve group as compared with the repeat biopsy group, in men with positive DRE as compared with men with negative DRE and when an endorectal coil was not used ( Table 3 ). There were no clear differences in the prevalence and NPV of the other analysed subgroups (TRUS-guided vs TTP biopsy, biopsy procedures with ≤16 cores vs >16 cores; Table 3 ). However, comparisons must be interpreted with care, due to the small number of studies in some subgroups. In patients with a PSA level of ≤10 ng/ml, the median NPV for overall PCa was 86.3% (IQR, 73.3–93.6%) for a median cancer prevalence of 35.4% (IQR, 27.6–42.5%).
Nb of studies | Median PCa prevalence | Median mpMRI NPV | Nb of studies | Median csPCa prevalence | Median mpMRI NPV | |
---|---|---|---|---|---|---|
Biopsy-naïve patients | 8 | 51.4% (45.5–56.7) | 69.9% (64.2–78) | 1 | 35.8% (NA) | 80.4% (NA) |
Repeat biopsy | 14 | 42% (35.1–52.6) | 82.6% (75.5–93.1) | 3 | 24.4% (19.1–32.8) | 88.2% (87.9–92.3) |
TRUS-guided biopsy | 36 | 49.7% (34.3–57.7) | 84.6% (68.6–92.8) | 4 | 28.1% (21.7–36.5) | 89.3% (82.9–92.4) |
TTP biopsy | 4 | 53.8% (47.5–57.8) | 73.6% (72–78.7) | 2 | 31.6% (30.5–32.8) | 92% (89.9–94) |
Biopsy with ≤16 cores | 28 | 48.7% (39.2–54.8) | 81.9% (66.8–89.3) | 5 | 28.1% (21.8–36.5) | 89.3% (82.9–92.4) |
Biopsy with >16 cores | 5 | 56.6% (51–61.3) | 81.1% (73.1–92.2) | 2 | 31.7% (30.5–32.8) | 92% (89.9–93.9) |
Positive DRE | 1 | 73.9% (NA) | 56% (NA) | 0 | – | – |
Negative DRE | 6 | 36% (34.6–46.8) | 82.7% (74.2–93.1) | 0 | – | – |
Endorectal coil | 17 | 41.7% (30.6–55.9) | 92.8% (79.3–95.4) | 1 | 31.7% (NA) | 91% (NA) |
No endorectal coil | 22 | 50.9% (41.7–56.1) | 77.7% (69.5–86.6) | 7 | 34% (26.9–46.1%) | 87.9% (78.2–92.1) |
Eight studies reported NPV at patient level for overall PCa and fulfilled the inclusion criteria for meta-analysis ( Table 4 ) [22 25 38 41 43 46 56 57] .
Study | Prevalence a (%) | Neg MRI (%) | NPV (%) | PPV (%) | Spe (%) | Se (%) | ||
---|---|---|---|---|---|---|---|---|
All PCa | Score ≥ 3/5 | Grenabo Bergdahl (2016) [22] | 31.3 | 66.9 | 83.7 | 47.5 | 63.2 | 73.1 |
Numao (2013) [38] | 45 | 29.4 | 70.6 | 64.3 | 71.0 | 63.9 | ||
Hauth (2015) [25] | 45.7 | 14.3 | 85.7 | 48.3 | 11.8 | 97.7 | ||
Vinet (2013) [57] | 49.3 | 24.6 | 64.7 | 53.8 | 31.4 | 82.4 | ||
Radtke (2015) [46] | 51 | 27 | 73 | 73.2 | 71.5 | 74.7 | ||
Thompson (2014) [56] | 61.3 | 31.4 | 68.6 | 76.8 | 60.3 | 82.6 | ||
Pokorny (2014) [43] | 63.7 | 30.9 | 69.1 | 82.4 | 69.1 | 82.4 | ||
Score ≥ 4/5 | Pepe (2015) [41] | 37 | 31 | 74.2 | 42 | 36.5 | 78.4% | |
Vinet (2013) [57] | 49.3 | 47.8 | 66.7 | 63.9 | 62.9 | 67.6% | ||
Radtke (2015) [46] | 51 | 73.5 | 63.9 | 92.3 | 95.8 | 48% | ||
Gleason ≥7 PCa | Score ≥ 3/5 | Radtke (2015) [46] | 29.3 | 27 | 87.9 | 45.1 | 59.6 | 80.2% |
a Prevalence of overall prostate cancers (10 first lines) or Gleason ≥7 cancers (last line).
PCa = prostate cancer; MRI = magnetic resonance imaging; Neg MRI = proportion of negative magnetic resonance imaging; NPV = negative predictive value; PPV = positive predictive value; Se = sensitivity; Spe = specificity.
Seven studies used a score of ≥3/5 for defining positive mpMRI ( Fig. 4 A and B) [22 25 38 43 46 56 57] . Fig. 4 C shows the conditional probability plot of 1 – NPV and PPV as a function of overall PCa prevalence. Table 5 shows NPV and PPV estimates for the given values of PCa prevalence.
PCaPrev | PPV | NPV |
---|---|---|
0.30 | 0.43 (0.34–0.53) | 0.88 (0.77–0.99) |
0.40 | 0.54 (0.45–0.64) | 0.82 (0.70–0.94) |
0.50 | 0.64 (0.55–0.73) | 0.76 (0.64–0.88) |
0.60 | 0.73 (0.65–0.80) | 0.67 (0.56–0.79) |
0.70 | 0.81 (0.75–0.87) | 0.57 (0.47–0.67) |
0.75 | 0.84 (0.79–0.89) | 0.51 (0.42–0.59) |
Only three studies used a score of ≥4/5 for defining positive mpMRI ( Table 4 ) [41 46 57] , and a formal meta-analysis could not be performed.
Only one study reporting NPV at patient level for Gleason ≥7 cancers met the selection criteria for inclusion in the meta-analysis. It reported NPV and PPV of 87.9% and 45.1%, respectively, for a prevalence of 29.3% ( Table 4 ) [46] .
We observed a large variability in reported NPV. Many factors, such as differences in mpMRI protocols, definition of negative mpMRI, or biopsy protocols, can explain this variability. However, two major causes of variability must be pointed out. First, the cancer prevalence was highly variable, ranging at patient level from 13% to 74.7% for overall PCa, and from 13.7% to 50.9% for csPCa. This variability was observed in both the biopsy-naïve and the repeat biopsy setting. As NPV depends on prevalence, this had a major impact on reported NPV ( Fig. 3 ). Second, the definition of csPCa was highly variable from one series to another, and differences of up to 21% could be observed in NPV when different definitions of csPCa were used in the same dataset [12 13 38 47 48] .
To account for clinical heterogeneity and to further explore the clinical relevance of the results, we carefully selected studies for inclusion in the meta-analysis based on stringent criteria. Particularly, we included only studies that: (1) had biopsy protocols with at least 10 cores, since it is no longer recommended to obtain less than 10 cores per biopsy; (2) used DWI, which is the most informative technique, at least for cancers in the peripheral zone [60] ; and (3) reported mpMRI findings using a five-level score, so that negative findings could be better defined. We accepted studies using a subjective (Likert) scale because experienced readers obtained equivalent [45 61 62] or better [63] results with the Likert score than with the PI-RADS v1 score. Owing to the large variations of NPV induced by differences in definitions of csPCa, we did not include different definitions in the meta-analysis since this would have introduced unacceptable clinical heterogeneity in the results, possibly resulting in erroneous and biased estimates. We, therefore, a priori restricted the definition of csPCa to cancers with a Gleason score of ≥7, given the low lethal potential of Gleason 6 cancers [64] and the lack of consensus among pathologists on the best method to measure biopsy core invasion length [65 66] .
In this more homogeneous group of studies, the prevalence range was still large (31.3–63.7%). As a result, we modelled the evolution of NPV (and PPV) as a function of overall PCa prevalence. Unfortunately, we could not duplicate this for csPCa since only one study reporting NPV for Gleason ≥7 cancers met the inclusion criteria for meta-analysis.
We included only studies that reported the results of systematic/standard biopsy in patients with negative mpMRI and used the systematic/standard biopsy as a reference standard. It is well known that TRUS-guided biopsy harbours both random and systematic errors, as evidenced by the high rates of positivity of immediate repeat biopsy after a first series of negative biopsies [67 68] , and as confirmed recently by the PROMIS trial [69] . Therefore, using TRUS-guided biopsy as a reference standard may have overestimated the NPV of mpMRI. However, studies using radical prostatectomy specimens as a reference standard have already reported mpMRI detection rates in relation to PCa Gleason score and volume [1] . In this review, we intended to address the more pragmatic question as to whether a negative mpMRI could predict a negative subsequent biopsy. This is an important question because if the NPV of mpMRI was sufficiently high in comparison with the reference standard of systematic/standard biopsies, then in practice a negative mpMRI result could indeed avoid the need for prostate biopsy. Therefore, studies reporting only biopsy results when the mpMRI was positive (eg, obtained through MRI-targeted, guided, or fusion biopsies with added systematic biopsies) were not included in this review.
It is now well established that mpMRI is a sensitive tool for detecting aggressive PCa 1 2 3 69] . However several reasons preclude its broad use as a triage test before biopsy.
Firstly, the population referred to prostate biopsy is not standardised. The large range of reported prevalence for overall PCa and csPCa suggests substantial heterogeneity in the way patients are selected for biopsy. Owing to this heterogeneity, we did not provide a pooled estimate for mpMRI NPV. The role of mpMRI as a triage test before prostate biopsy should be evaluated in the broader context of the selection of patients with a suspicion of (aggressive) PCa. In a recent retrospective study of 514 patients, mpMRI NPV for Gleason ≥7 cancers was 91% when the PSA density was ≤0.2 ng/ml/ml, and only 71% when the PSA density was >0.2 ng/ml/ml ( p = 0.003) [70] . In another series of 288 biopsy-naïve patients, no csPCa (Gleason score ≥7 or maximum cancer core length ≥4 mm) was found in 44 patients with a PSA density of <0.15 ng/ml/ml and a PI-RADS v2 score of <3/5 [71] . We believe that such prestratification of the risk of csPCa is an interesting way for rationalising the use of mpMRI before biopsy. Patients found at very low risk would be spared both mpMRI and biopsy. Patients at a low risk—for whom mpMRI would have an NPV high enough to be used as a triage test—could avoid biopsy in case of negative mpMRI. Patients at a higher risk would need biopsy even in case of negative mpMRI. Many tools can be used to risk stratify the population of patients referred to biopsy, ranging from simple parameters such as PSA density to more complicated risk calculators [72 73] . The impact of these tools on the NPV of prebiopsy mpMRI needs to be carefully evaluated, both in the biopsy-naïve and in the repeat biopsy setting. For the moment, it is impossible to make any recommendations on the best way to risk stratify patients before referring them for mpMRI.
Secondly, the large variability in the definition of csPCa precludes any definitive conclusion on the ability of mpMRI to rule out aggressive cancer. The issue of the most appropriate definition of csPCa on biopsy is complex, since biopsy results may accurately reflect neither tumour burden nor aggressiveness. Nonetheless, there is an urgent need to standardise the histological definition(s) of csPCa, to allow meaningful comparisons between studies.
Thirdly, the specificity of mpMRI remains moderate, and there is a substantial proportion of false positives in the lesions scored 3/5 or 4/5 [1 74 75] , even with the new PI-RADS v2 score [76] . In a series of 62 patients with 116 lesions biopsied under magnetic resonance/ultrasound fusion, the overall cancer detection rates for PI-RADS v2 scores of 3/5 and 4/5 were only 15.8% and 29.8%, respectively [77] . In theory, a triage test used to rule out a disease needs to be highly sensitive for this disease. However, if its specificity is too low, it will be clinically useless since most patients will be positive, whether they have the disease or not. Therefore, if mpMRI is to be used as a triage test in the future, there is a need to improve its specificity. This could be achieved by a continuous refinement of scores [78] . Promising results in characterising csPCa have also been reported with a quantitative analysis [79] .
Finally, all published studies were conducted in specialised centres. The broad use of mpMRI as a triage test assumes good interobserver reproducibility. Unfortunately, interobserver reproducibility of existing scoring systems remains moderate [62 63 80] even with the use of the PI-RADS v2 score [80 81] . Studies evaluating on a large scale the reproducibility of mpMRI findings between expert and nonexpert centres are currently lacking.
Three systematic reviews (including two meta-analyses) regarding the role of mpMRI in localised PCa have been published recently 4 5 6 . Crucially, all three reviews focused exclusively on the sensitivity of mpMRI-targeted, guided, or fusion biopsies in diagnosing overall PCa and csPCa, using TRUS-guided prostate biopsies as reference standards. The impact of systematic biopsies on the outcome was not addressed in any of the reviews, within either the index test or the reference standard. Our review had a totally different research question and objective, focusing on NPV of mpMRI to see if a negative mpMRI can avoid the need for a prostate biopsy. As MRI-targeted/guided/fusion biopsies are not relevant if the mpMRI was negative for cancer, it can be argued that the three reviews assessed a different index test altogether. As such, we believe that the findings of this review are novel and unique, and pave the way for further focused clinical studies.
The current study represents the first systematic review addressing the role of mpMRI as a triage test before biopsy. The review elements were developed in conjunction with a multidisciplinary panel of experts (EAU Prostate Cancer Guidelines Panel), which included a patient representative, and the review was performed robustly in accordance with recognised standards. However, it is limited by the major heterogeneity of the existing literature in patient population, study design, and definitions of positive mpMRI and csPCa. It highlighted further areas of research that could help in defining the best use of mpMRI in the early detection of aggressive PCa in the future.
Although mpMRI can detect aggressive PCa with excellent sensitivity, a definitive conclusion on its role as a triage test before prostate biopsy will be possible only when three main issues are addressed. Firstly, because NPV depends on prevalence, and because overall PCa and csPCa prevalence was highly variable in the published series, it becomes mandatory to define the optimal way to pre-evaluate the risk of csPCa in patients with a suspicion of PCa. Depending on the risk category, mpMRI could then be used to obviate biopsies or not. Secondly, there is a need for consensus definitions of csPCa on biopsy findings to allow interstudy comparisons. Thirdly, although efforts have been made to standardise mpMRI technical protocols and interpretation in the past few years [11 60 76] , there is still a crucial need to improve mpMRI specificity and inter-reader reproducibility.
This systematic review was performed under the auspices of:
The European Association of Urology Guidelines Office Board
The European Association of Urology Prostate Cancer Guideline Panel
Author contributions: Olivier Rouvière had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.
Study concept and design: Rouvière, Mottet, Cornford.
Acquisition of data: Rouvière, Moldovan, Van den Broeck, Yuan.
Analysis and interpretation of data: Rouvière, Moldovan, Van den Broeck, Lam.
Drafting of the manuscript: Rouvière, Moldovan, Van den Broeck, Lam.
Critical revision of the manuscript for important intellectual content: Bellmunt, van den Bergh, Bolla, Briers, Van den Broeck, Cornford, Cumberbatch, De Santis, Fossati, Gross, Henry, Joniau, Lam, Matveev, Moldovan, van der Poel, van der Kwast, Rouvière, Schoots, Wiegel, Mottet.
Statistical analysis: None.
Obtaining funding: None.
Administrative, technical, or material support: Yuan, Sylvester, Marconi.
Supervision: None.
Other: None.
Financial disclosures: Olivier Rouvière certifies that all conflicts of interest, including specific financial interests and relationships and affiliations relevant to the subject matter or materials discussed in the manuscript (eg, employment/affiliation, grants or funding, consultancies, honoraria, stock ownership or options, expert testimony, royalties, or patents filed, received, or pending), are the following: Bellmunt is a company consultant for Janssen, Astellas, Pierre Fabre, Genentech, Merck, Ipsen, Pfizer, Novartis, and Sanofi Aventis. He has received research support from Takeda, Novartis, and Sanofi, and received travel grants from Pfizer and Pierre Fabre. Bolla has received company speaker honoraria from Ipsen and Astellas, honoraria or consultation fees from Janssen, and fellowship and travel grants from Janssen, AstraZeneca, and Astellas. Briers has received grant and research support from Ipsen, European Association of Urology, and Bayer; is an ex officio board member for Europa UOMO; is an ethics committee and advisory group member for REQUITE; is a member patient advisory board member for PAGMI; and is a member of SCA and EMA PCWP. Cornford is a company consultant for Astellas, Ipsen, and Ferring. He receives company speaker honoraria from Astellas, Janssen, Ipsen, and Pfizer; participates in trials from Ferring; and receives fellowships and travel grants from Astellas and Janssen. De Santis is a company consultant for GlaxoSmithKline, Janssen, Bayer, Novartis, Pierre Fabre, Astellas, Amgen, Eisai Inc., ESSA, Merck, and Synthon; has received company speaker honoraria from Pfizer, Takeda, Sanofi Aventis, Shionogi, Celgene, and Teva OncoGenex; has participated in trials for Pierre Fabre, Astellas, Exelixis, Bayer, and Roche; has received fellowship and travel grants from Bayer, Novartis, Ferring, Astellas, Sanofi Aventis, and Janssen; has received grant and research support from Pierre Fabre; has received honoraria from AstraZeneca; and is associated with Amgen. Joniau is a company consultant for Astellas, Ipsen, Bayer, Sanofi, and Janssen; has received company speaker honoraria from Astellas, Amgen, Bayer, Sanofi, Janssen, and Ipsen; has participated in trials for Astellas, Janssen, and Bayer; has received fellowship and travel grants from Astellas, Amgen, Bayer, Sanofi, Janssen, Ipsen, and Pfizer; and has received grant and research support from Astellas, Bayer, and Janssen. Matveev has received company speaker honoraria from Sanofi and Astellas, has participated in trials for Astellas, Pfizer and Novartis. Lam is a company consultant for and has received company speaker honoraria from Pfizer, GSK, Astellas, and Ipsen. van der Poel is a company consultant for Intuitive Surgical, has participated in trials for Astellas and Steba Biotech, and has received grant and research support from Astellas. Rouvière is a company consultant for EDAP-TMS, Bracco, and Philips; has received company speaker honoraria from EDAP-TMS, Bracco, and Philips; and has participated in trials for EDAP-TMS and Bracco. Wiegel has received company speaker honoraria from Astellas, Takeda, Hexal, Ipsen, Janssen-Cilac, and Ferring. Mottet has received grant and research support from Takeda Pharmaceutical, Millenium, Astellas, Pierre Fabre, Sanofi, and Pasteur, and has received honoraria or consultation fees from Takeda Pharaceutical, Millenium, Jansen, Astellas, BMS, Bayer, Ipsen, Ferring, Novartis, Nuclétron, Pierre Fabre, Sanofi, and Zeneca. van den Bergh, Van den Broeck, Cumberbatch, Fossati, Gross, Henry, van der Kwast, Sylvester, Yuan, Schoots, Moldovan, and Marconi have nothing to disclose.
Funding/Support and role of the sponsor: None.