Combined Value of Validated Clinical and Genomic Risk Stratification Tools for Predicting Prostate Cancer Mortality in a High-risk Prostatectomy Cohort

Background: Risk prediction models that incorporate biomarkers and clinicopathologic variables may be used to improve decision making after radical prostatectomy (RP). We compared two previously validated post-RP classifiers—the Cancer of the Prostate Risk Assessment Postsurgical (CAPRA-S) and the Decipher genomic classifier (GC)—to predict prostate cancer–specific mortality (CSM) in a contemporary cohort of RP patients. Objective: To evaluate the combined prognostic ability of CAPRA-S and GC to predict CSM. Design, setting, and participants: A cohort of 1010 patients at high risk of recurrence after RP were treated at the Mayo Clinic between 2000 and 2006. High risk was defined by any of the following: preoperative prostate-specific antigen >20 ng/ml, pathologic Gleason score � 8, or stage pT3b. A case-cohort random sample identified 225 patients (with cases defined as patients who experienced CSM), among whom CAPRA-S and GC could be determined for 185 patients. Outcome measurements and statistical analysis: The scores were evaluated individually and in combination using concordance index (c-index), decision curve analysis, reclassification, cumulative incidence, and Cox regression for the prediction of CSM. Results and limitations: Among 185 men, 28 experienced CSM. The c-indices for CAPRA-S and GC were 0.75 (95% confidence interval [CI], 0.55–0.84) and 0.78 (95% CI, 0.68–0.87), respectively. GC showed higher net benefit on decision curve analysis, but a score combining CAPRA-S and GC did not improve the area under the receiveroperating characteristic curve after optimism-adjusted bootstrapping. In 82 patients stratified to high risk based on CAPRA-S score � 6, GC scores were likewise high risk for 33 patients, among whom 17 had CSM events. GC reclassified the remaining 49 men as low to intermediate risk; among these men, three CSM events were observed. In multivariable analysis, GC and CAPRA-S as continuous variables were independently prognostic of CSM, with hazard ratios (HRs) of 1.81 ( p < 0.001 per 0.1-unit change in score) and 1.36 ( p = 0.01 per 1-unit change in score). When categorized into risk groups, the multivariable HR for high CAPRA-S scores (� 6) was 2.36 ( p = 0.04) and was 11.26 ( p < 0.001) for high GC scores (� 0.6). For patients with both high GC and high CAPRA-S scores, the cumulative incidence of CSM was 45% at 10 yr. The study is limited by its retrospective design.