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.
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 riskwas 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 (withcasesdefined 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 receiver-operating 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.
Both GC and CAPRA-S were significant independent predictors of CSM. GC was shown to reclassify many men stratified to high risk based on CAPRA-S ≥6 alone. Patients with both high GC and high CAPRA-S risk scores were at markedly elevated post-RP risk for lethal prostate cancer. If validated prospectively, these findings suggest that integration of a genomic-clinical classifier may enable better identification of those post-RP patients who should be considered for more aggressive secondary therapies and clinical trials.
The Cancer of the Prostate Risk Assessment Postsurgical (CAPRA-S) and the Decipher genomic classifier (GC) were significant independent predictors of prostate cancer–specific mortality. These findings suggest that integration of a genomic-clinical classifier may enable better identification of those post–radical prostatectomy patients who should be considered for more aggressive secondary therapies and clinical trials.
Keywords: Prostate neoplasms, Prostatectomy, Biomarkers, RNA, Risk stratification, CAPRA-S.
a Departments of Urology and Epidemiology & Biostatistics, University of California, San Francisco, San Francisco, CA, USA
b GenomeDx Biosciences, Vancouver, British Columbia, Canada
c Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA
d Department of Urology, Mayo Clinic, Rochester, MN, USA
These authors made equal contributions.
© 2014 Published by Elsevier B.V.