Objectives: To 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 methods: We 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 5-20%.

Results: 940 men were included, 507 (54%) had csPCa. Median and interquartile ranges of age, PSA, and PSAD were 68 (63-72) years, 9 (7-15) ng/ml, and 0.20 (0.13-0.32) ng/ml² , respectively. 18 multivariable risk calculators (MRI-RCs) and dichotomous biopsy decision strategies based on MRI findings and prostate-specific antigen density thresholds (PSAD) were assessed. The Van Leeuwen model and the Rotterdam Prostate Cancer Risk Calculator (RPCRC) had the best discriminative ability (AUC 0.86) of 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, while the RPCRC would avoid 20% of biopsies, missing 2.6% of csPCa. These multivariable models outperformed all dichotomous decision strategies based only on MRI-findings and PSAD.

Conclusions: Even in this high-risk cohort, biopsy decision support tools would avoid many prostate biopsies, while 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.