Expanding Active Surveillance Criteria for Low- and Intermediate-risk Prostate Cancer: Can We Accurately Predict the Risk of Misclassification for Patients Diagnosed by Multiparametric Magnetic Resonance Imaging–targeted Biopsy?

Abstract

Models predicting the risk of adverse pathology (ie, International Society of Urological Pathology [ISUP] grade group ≥3, pT3, and/or pN1) among patients operated by radical prostatectomy (RP) have been proposed to expand active surveillance (AS) inclusion criteria. We aimed to test these models in a set of 1062 low-risk and favorable intermediate-risk prostate cancer (PCa) patients diagnosed by multiparametric magnetic resonance imaging (MRI) and MRI-targeted biopsy. We hypothesized that the inclusion of radiological features into a novel model would improve patient selection. Performance was assessed using discrimination, calibration, and decision curve analysis (DCA). Available models were characterized by poor discrimination (areas under the receiver operating characteristic curve [AUCs] of 59% and 60%), underestimation of predicted risk on calibration plots, and a small amount of net benefit against a probability threshold of 40–50% at the DCA. The development of a novel model slightly improved discrimination (AUC of 63% vs 59%, p = 0.001, and 63% vs 60%, p = 0.07) and net benefit against threshold probabilities of ≥30%. This first multicenter study demonstrated the poor performance of models predicting adverse pathology and that implementation of MRI and MRI-targeted biopsy in this setting was not associated with a clear improvement in patient selection. Patients harboring low-risk or favorable intermediate-risk PCa and candidates for RP cannot be referred accurately to an AS program without a non-negligible risk of misclassification. Patient summaryWe tested prediction models that could expand the selection of prostate cancer patients for active surveillance. Models were inaccurate and associated with a high risk of misclassification despite the implementation of multiparametric magnetic resonance imaging and targeted biopsies.