External validation of the ProCaRS nomograms and comparison of existing risk-stratification tools for localized prostate cancer.

Abstract

The purpose of this study was to perform a direct comparison of several existing risk-stratification tools for localized prostate cancer in terms of their ability to predict for biochemical failure-free survival (BFFS). Two large databases were used and an external validation of two recently developed nomograms on an independent cohort was also performed in this analysis. Patients who were treated with external beam radiotherapy (EBRT) and/or brachytherapy for localized prostate cancer were selected from the multi-institutional Genitourinary Radiation Oncologists of Canada (GUROC) Prostate Cancer Risk Stratification (ProCaRS) database (n=7974) and the Centre Hospitalier de l'Université de Montréal (CHUM) validation database (n=2266). The primary outcome was BFFS using the Phoenix definition. Concordance index (C-index) reported from Cox proportional hazards regression using 10-fold cross validation and decision curve analysis (DCA) were used to predict BFFS. C-index identified Cancer of the Prostate Risk Assessment (CAPRA) score and ProCaRS as superior to the historical GUROC and National Comprehensive Cancer Network (NCCN) risk-stratification systems. CAPRA modeled as five and three categories were superior to GUROC and NCCN only for the CHUM database. C-indices for CAPRA score, ProCaRS, GUROC, and NCCN were 0.72, 0.72, 0.71, and 0.72, respectively, for the ProCaRS database, and 0.66, 0.63, 0.57, and 0.60, respectively, for the CHUM database. However, many of these comparisons did not demonstrate a clinically meaningful difference. DCA identified minimal differences across the different risk-stratification systems, with no system emerging with optimal net benefit. External validation of the ProCaRS nomograms yielded favourable calibrations of R2=0.778 (low-dose rate [LDR]-brachytherapy) and R2=0.868 (EBRT). This study externally validated two ProCaRS nomograms for BFFS that may help clinicians in treatment selection and outcome prediction. A direct comparison between existing risk-stratification tools demonstrated minimal clinically significant differences in discriminative ability between the systems, favouring the CAPRA and ProCaRS systems. The incorporation of novel prognostic variables, such as genomic markers, is needed.