Assessing a Patient's Individual Risk of Biopsy-detectable Prostate Cancer: Be Aware of Case Mix Heterogeneity and A Priori Likelihood.

The relation between prostate-specific antigen (PSA) and other relevant prebiopsy information is often combined in a risk calculator (RC). If the setting for RC use differs from that in which it was developed, there is a risk of making clinical decisions based on incorrect estimates of the absolute risk. The ERSPC-MRI RC predicts clinically significant prostate cancer (csPC; Gleason ≥3 + 4) on targeted and systematic biopsy using information on PSA, digital rectal examination, prostate volume, age, previous negative biopsy, and Prostate Imaging-Recording and Data System score. This calculator was developed on a clinical cohort of 961 men (2012-2017) with a csPC prevalence of 36%. Discrimination was good (area under the receiver operating characteristic curve 0.84). With the increasing use of multiparametric magnetic resonance imaging, we foresee that this RC will also be used for men with a lower a priori likelihood of PC. We investigated the effect of such a scenario on individual risk predictions. A small update of the intercept for the calculator can restore the accuracy to support decision-making with locally valid risk estimates. PATIENT SUMMARY: Decisions on who to refer for a prostate biopsy with its risk of sepsis and overdiagnosis require more than a prostate-specific antigen test. A prediction tool may take other relevant prebiopsy information into account, but may need to be updated to contemporary center-specific settings to provide accurate estimates of the risk of having prostate cancer.

European urology oncology. 2019 Aug 17 [Epub ahead of print]

Jan F M Verbeek, Daan Nieboer, Ewout W Steyerberg, Monique J Roobol

Department of Urology, Erasmus Medical Center, Rotterdam, The Netherlands. Electronic address: ., Department of Public Health, Erasmus Medical Center, Rotterdam, The Netherlands., Department of Public Health, Erasmus Medical Center, Rotterdam, The Netherlands; Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, The Netherlands., Department of Urology, Erasmus Medical Center, Rotterdam, The Netherlands.

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