Ability of cell-cycle progression score to predict risk for progression to metastatic disease and disease-specific mortality in prostate cancer patients after prostatectomy.
5524 Background: Prostate cancer treatment aims to prevent metastatic disease (METS) and disease-specific mortality (DSM). A major challenge is to identify those at highest risk so additional intervention can be initiated earlier when it has a better chance of success. Pathologic parameters alone have limited ability to predict METS and DSM, but data suggests biomarkers can improve risk discrimination. Methods: Eligible patients had: (1) prostate cancer treated with radical prostatectomy (RP; 1988-1995); (2) available tissue for cell-cycle progression (CCP) testing that resulted in a valid score; (3) preoperative prostate-specific antigen (PSA); (4) no neoadjuvant therapy; and (5) clinical follow-up (N = 360). Cancer of the prostate risk assessment post-surgical (CAPRA-S) was combined with CCP into a combined cell-cycle risk score (CCR = 0.38 × CAPRA-S + 0.57 × CCP). Results: Median follow-up was 23.5 years for patients alive at last follow-up. Overall, 11% (41/360) developed METS and 9% (33/360) had DSM. CCP score added significant information to CAPRA-S when predicting METS (p = 0.001) and DSM (p = 0.001). CCR score was also a significant predictor of METS and DSM (p-values < 1×10−8). CCP and CCR scores were prognostic of METS in patients with rising post-RP PSA. Of patients with biochemical recurrence (BCR), 25% (41/163) developed METS. CAPRA-S alone was predictive of these events (p = 0.01) but was significantly improved with the addition of CCP (Hazard Ratio [HR] = 1.69 [95% Confidence Interval (CI) 1.13, 2.52], p = 0.014). CCR was also highly prognostic (HR = 1.56 [95% CI 1.20, 2.03], p = 0.001). CCR score discriminated risk of METS both post-RP and after post-RP BCR (Table). Conclusions: Overall, the CCR score significantly predicted METS and DSM in prostate cancer post-RP and was also highly prognostic in those with a post-RP rising PSA. It is therefore a useful tool for determining who is at greatest risk of treatment failure and may benefit from earlier intervention. [Table: see text]