Performance of magnetic resonance imaging‐based prostate cancer risk calculators and decision strategies in two large European medical centres

Author:

Davik Petter12ORCID,Remmers Sebastiaan3ORCID,Elschot Mattijs45,Roobol Monique J.3ORCID,Bathen Tone Frost24,Bertilsson Helena12

Affiliation:

1. Department of Urology St Olavs Hospital Trondheim Norway

2. Department of Clinical and Molecular Medicine (IKOM) Norwegian University of Science and Technology (NTNU) Trondheim Norway

3. Department of Urology Erasmus MC Cancer Institute, University Medical Center Rotterdam Rotterdam The Netherlands

4. Department of Radiology and Nuclear Medicine St Olavs Hospital Trondheim Norway

5. Department of Circulation and Medical Imaging (ISB) Norwegian University of Science and Technology (NTNU) Trondheim Norway

Abstract

ObjectivesTo compare the performance of currently available biopsy decision support tools incorporating magnetic resonance imaging (MRI) findings in predicting clinically significant prostate cancer (csPCa).Patients and MethodsWe retrospectively included men who underwent prostate MRI and subsequent targeted and/or systematic prostate biopsies in two large European centres. Available decision support tools were identified by a PubMed search. Performance was assessed by calibration, discrimination, decision curve analysis (DCA) and numbers of biopsies avoided vs csPCa cases missed, before and after recalibration, at risk thresholds of 5%–20%.ResultsA total of 940 men were included, 507 (54%) had csPCa. The median (interquartile range) age, prostate‐specific antigen (PSA) level, and PSA density (PSAD) were 68 (63–72) years, 9 (7–15) ng/mL, and 0.20 (0.13–0.32) ng/mL2, respectively. In all, 18 multivariable risk calculators (MRI‐RCs) and dichotomous biopsy decision strategies based on MRI findings and PSAD thresholds were assessed. The Van Leeuwen model and the Rotterdam Prostate Cancer Risk Calculator (RPCRC) had the best discriminative ability (area under the receiver operating characteristic curve 0.86) of the MRI‐RCs that could be assessed in the whole cohort. DCA showed the highest clinical utility for the Van Leeuwen model, followed by the RPCRC. At the 10% threshold the Van Leeuwen model would avoid 22% of biopsies, missing 1.8% of csPCa, whilst the RPCRC would avoid 20% of biopsies, missing 2.6% of csPCas. These multivariable models outperformed all dichotomous decision strategies based only on MRI‐findings and PSAD.ConclusionsEven in this high‐risk cohort, biopsy decision support tools would avoid many prostate biopsies, whilst missing very few csPCa cases. The Van Leeuwen model had the highest clinical utility, followed by the RPCRC. These multivariable MRI‐RCs outperformed and should be favoured over decision strategies based only on MRI and PSAD.

Funder

Norges Forskningsråd

Publisher

Wiley

Subject

Urology

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