Abstract
5033 Background: Almost 50,000 men per year will present with biochemical recurrence (BCR) following local treatment for prostate cancer. These men with rising PSAs as the lone indicator of recurrence present a management dilemma due to their varied outcomes with only a proportion developing subsequent metastatic disease. Thus, there is a clear need to improve patient risk stratification in this context. Here, we evaluate Decipher, a genomic classifier (GC) in men with BCR following radical prostatectomy (RP) for its ability to predict metastasis. Methods: The 22-marker GC was validated in a prospectively designed case-cohort study of 1,010 clinically high-risk RP patients. 219 patients, including 85 who developed BCR at least 6 months post-RP were subjected to microarray analysis and GC scores were generated. Survival ROC curves, weighted Cox proportional hazards, and decision curves were used to compare the performance of the GC to Gleason score (GS), PSA doubling time (PSAdT) and time to BCR (ttBCR). Results: GC scores significantly stratified these men into those who would or would not develop metastasis after BCR (8% versus 40% of patients developed metastasis at 3 years following BCR depending on GC score category, p<0.001). The AUC for GC was 0.82 (95% CI, 0.76-0.86), compared to that of GS 0.64 (0.58-0.70), PSAdT 0.69 (0.61-0.77) and ttBCR 0.52 (0.46-0.59). In decision curve analysis, the GC had the highest overall ‘net benefit’ and in multivariable modeling with clinicopathologic variables, only GC (p=0.006) and GS (p=0.046) scores were significant predictors of metastasis. Conclusions: When compared to clinicopathologic variables, the GC better predicted metastatic progression among men with BCR following RP. While confirmatory studies in additional patient populations are required, these results suggest that use of the GC can allow for better selection of men requiring additional treatment at the time of BCR.
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