Tag Archive for: aotw 11-03-2020


Article of the week: External validation of novel magnetic resonance imaging‐based models for prostate cancer prediction

Every week, the Editor-in-Chief selects an Article of the Week from the current issue of BJUI. The abstract is reproduced below and you can click on the button to read the full article, which is freely available to all readers for at least 30 days from the time of this post.

In addition to this post, there is an editorial written by a prominent member of the urological community and a visual abstract created by trainee urologists. Please use the comment buttons below to join the conversation.

If you only have time to read one article this week, we recommend this one. 

External validation of novel magnetic resonance imaging‐based models for prostate cancer prediction

Lukas Püllen*, Jan P. Radtke*, Manuel Wiesenfarth, Monique J. Roobol§, Jan F.M. Verbeek§, Axel Wetter, Nika Guberina, Abhishek Pandey**, Clemens Hüttenbrink**, Stephan Tschirdewahn*, Sascha Pahernik**, Boris A. Hadaschik* and Florian A. Distler**

*Department of Urology, University Hospital Essen, Nordrhein-Westfalen, Department of Radiology, German Cancer Research Centre (DKFZ), Division of Biostatistics, German Cancer Research Centre (DKFZ), Heidelberg, Germany, §Department of Urology, Erasmus University Medical Centre, Rotterdam, The Netherlands, Department of Radiology, University Hospital Essen, Nordrhein-Westfalen, and **Department of Urology, Paracelsus Medical University, Nuremberg, Nürnberg, Germany



To validate, in an external cohort, three novel risk models, including the recently updated European Randomized Study of Screening for Prostate Cancer (ERSPC) risk calculator, that combine multiparametric magnetic resonance imaging (mpMRI) and clinical variables to predict clinically significant prostate cancer (PCa).

Patients and Methods

We retrospectively analysed 307 men who underwent mpMRI prior to transperineal ultrasound fusion biopsy between October 2015 and July 2018 at two German centres. mpMRI was rated by Prostate Imaging Reporting and Data System (PI‐RADS) v2.0 and clinically significant PCa was defined as International Society of Urological Pathology Gleason grade group ≥2. The prediction performance of the three models (MRI‐ERSPC‐3/4, and two risk models published by Radtke et al. and Distler et al., ModRad and ModDis) were compared using receiver‐operating characteristic (ROC) curve analyses, with area under the ROC curve (AUC), calibration curve analyses and decision curves used to assess net benefit.

Fig. 4. Biopsies saved vs prostate cancer detected/missed using different risk thresholds for clinically significant prostate cancers (PCas) for the different models for a standardized number of 1000 men for the whole cohort (A) and the two analysed subgroups (biopsy‐naïve (B) and previous negative biopsy (C)); including a graphical presentation of biopsy saving vs. missing clinically significant PCas for two different thresholds (10% and 15%) for the validated nomograms. Green shading shows the number of saved biopsies. Red shading shows the number of clinically significant PCas missed. ModDis, risk model published by Distler et al.; ModRad, risk model published by Radtke et al.; MRI‐ERSPC‐3/4, updated ERSPC risk calculator 3/4.


The AUCs of the three novel models (MRI‐ERSPC‐3/4, ModRad and ModDis) were 0.82, 0.85 and 0.83, respectively. Calibration curve analyses showed the best intercept for MRI‐ERSPC‐3 and ‐4 of 0.35 and 0.76. Net benefit analyses indicated clear benefit of the MRI‐ERSPC‐3/4 risk models compared with the other two validated models. The MRI‐ERSPC‐3/4 risk models demonstrated a discrimination benefit for a risk threshold of up to 15% for clinically significant PCa as compared to the other risk models.


In our external validation of three novel prostate cancer risk models, which incorporate mpMRI findings, a head‐to‐head comparison indicated that the MRI‐ERSPC‐3/4 risk model in particular could help to reduce unnecessary biopsies.

Editorial: Magnetic resonance imaging as a personalised tool to safely avoid prostate biopsy

Identifying men at risk of developing clinically significant prostate cancer (csPCa) who are either biopsy naïve or have undergone a prior negative systematic biopsy remains a dilemma for urologists seeking to utilise clinical resources in a cost‐conscious and safe manner. Clinical and demographic factors including DRE findings, serum PSA concentrations, race/ethnicity, and family history, guide shared decision‐making to pursue an initial or repeat prostate biopsy. Despite thoughtful risk assessments, the screening tools implemented often lead to biopsies where a majority demonstrates benign pathology findings or indolent forms of PCa that would not mandate immediate, definitive intervention. Hence, various risk models (RMs) have been proposed to stratify men who have a greater likelihood of harbouring csPCa, and several now incorporate findings from multiparametric MRI (mpMRI) by assessing suspicious lesion characteristics into their algorithms. While promising, most of these models were generated using single‐institution retrospective data and lack the external validation that could make them more generalisable and widely adopted in clinical practice.

In the present issue, Püllen et al. [1] evaluate three RMs that incorporate mpMRI findings using a cohort of 307 men who were biopsy naïve or had previously undergone a negative prostate biopsy. Risk of csPCa according to the MRI‐European Randomized Prostate Screening for Prostate Cancer Risk Calculators 3 and 4 (MRI‐ERSPC‐3/4) [2], Radtke’s RM (ModRAD) [3], and Distler’s RM (ModDis) [4] were compared to final pathology after TRUS‐guided perineal prostate biopsy with MRI‐fusion targeted sampling, as indicated using a Prostate Imaging‐Reporting and Data System version 2 (PI‐RADSv2) score ≥3 as the threshold.

The cohort had a median age of 67 years, median PSA concentration of 8.8 ng/mL, and there were 453 PI‐RADSv2 ≥3 lesions, which is consistent with a typical at‐risk screening population. Amongst these men, 134 (40%) harboured csPCa defined as a Gleason Grade Group ≥2. All three RMs performed similarly on receiver operating curve analyses with area under the curve for prediction nearing 0.85 for finding csPCa in both biopsy naïve and prior negative‐biopsy patients. Using a 15% risk threshold, the adapted MRI‐ERSPC‐3/4 RM would have safely avoided 30% of biopsies with 6% of csPCa diagnoses being missed, whereas the ModRad and ModDis RMs would have only avoided 17% and 6% of unnecessary biopsies, respectively, albeit with far fewer occult cases of csPCa.

The integration of mpMRI in the pre‐biopsy setting is being more widely adopted into the clinical landscape, with emerging support largely due to its value in detecting csPCa, but also the recognised high negative predictive value potentiating the safe avoidance or deferral of prostate biopsy [5]. Performing a prostate biopsy in all men with a clinical screening positive PSA and/or DRE carries a significant public health burden, and harbours recognised clinical morbidity without definitive overall survival benefit for many. Hence, integration of MRI findings, importantly the lack of highly suspicious lesions, is of interest in RM assessment to determine which patients would be benefited most from prostate biopsy while sparing some from biopsy, without compromising detection of csPCa and oncological outcomes.

For patients who forgo prostate biopsy based upon factors such as nomogram‐predicted risk of harbouring csPCa, the appropriate timing for performing repeat evaluation with biomarkers and/or MRI is not well defined. Various models have shown much higher rates of biopsy avoidance if accepting some level of missed csPCa [6]. With the awareness that some men who would theoretically avoid a biopsy based on these RMs may actually harbour csPCa, should these men undergo repeat MRI as standard or would serial PSA assessment drive biopsy detection of their csPCa with adequate lead time for definitive treatment? Prospective investigations assessing the clinical course of patients with negative MRI findings who avoid or defer biopsy are critical to determine the real‐world applicability of such RMs. The true value of these RMs and nomograms should balance their public health cost and morbidity benefit with potential oncological risk.

by Zachary A. Glaser and Soroush Rais‐Bahrami


  1. Püllen LRadtke JPWiesenfarth M et al. External validation of novel magnetic resonance imaging‐based models for prostate cancer prediction. BJU Int 2020125407– 16
  2. Alberts ARRoobol MJVerbeek JFM et al. Prediction of high‐grade prostate cancer following multiparametric magnetic resonance imaging: improving the Rotterdam European randomized study of screening for prostate cancer risk calculators. Eur Urol 201975310– 8
  3. Radtke JPWiesenfarth MKesch C et al. Combined clinical parameters and multiparametric magnetic resonance imaging for advanced risk modeling of prostate cancer‐patient‐tailored risk stratification can reduce unnecessary biopsies. Eur Urol 201772888– 96
  4. Distler FARadtke JPBonekamp D et al. The value of PSA density in combination with PI‐RADS for the accuracy of prostate cancer prediction. J Urol 2017198575– 82
  5. Siddiqui MMRais‐Bahrami STurkbey B et al. Comparison of MR/ultrasound fusion‐guided biopsy with ultrasound‐guided biopsy for the diagnosis of prostate cancer. JAMA 2015313390– 7
  6. Mehralivand SShih JHRais‐Bahrami S et al. A Magnetic resonance imaging‐based prediction model for prostate biopsy risk stratification. JAMA Oncol 20184678– 85



Visual abstract: External validation of novel MRI-based models for prostate cancer prediction

See more infographics
© 2023 BJU International. All Rights Reserved.