Predicting risk of prostate specific antigen recurrence after radical prostatectomy with the center for prostate disease research and cancer of the prostate strategic urologic research endeavor databases

Purpose: Biostatistical models to predict stage or outcome in patients with clinically localized prostate cancer with pretreatment prostate specific a ntigen (PSA), Gleason sum on biopsy or prostatectomy specimen, clinical or pathological stage and other variables, including ethnicity, have been deve loped. However, to date models have relied on small subsets from academic c enters or military populations that may not be representative. Our study va lidates and updates a model published previously with the Cancer of the Pro state Strategic Urologic Research Endeavor (CaPSURE, UCSF, Urology Outcomes Research Group and TAP Pharmaceutical Products, Inc.), a large multicenter , community based prostate cancer database and Center for Prostate Disease Research (CPDR), a large military database. Materials and Methods: We validated a biostatistical model that includes pr etreatment PSA, highest Gleason sum on prostatectomy specimen, prostatectom y organ confinement status and ethnicity, including white and black patient s. We then revised it with the Cox regression analysis of the combined 503 PSA era surgical cases from the CPDR prospective cancer database and 1,012 from the CaPSURE prostate cancer outcomes database. Results: The original equation with 3 risk groups stratified CaPSURE cases into distinct categories with 7-year disease-free survival rates of 72%, 42 .1% and 27.6% for low, intermediate and high risk men, respectively. Parame ter estimates obtained from a Cox regression analysis provided a revised mo del equation that calculated the relative risk of recurrence as: exponent ( exp)[(0.54 x Race) + (0.05 x sigmoidal transformation of PSA [PSA(ST)]) + ( 0.23 x Postop Gleason) + (0.69 x Pathologic stage). The relative risk of re currence, as calculated by the aforementioned equation, was used to stratif y the cases into 4 risk groups. Very low-4.7 or less, low-4.7 to 7.1, high- 7.1 to 16.7 and very high-greater than 16.7, and patients at risk had 7-yea r disease-free survival rates of 85.4%, 66.0%, 50.6% and 21.3%, respectivel y. Conclusions: With a broad cohort of community based, academic and military cases, we developed an equation that stratifies men into 4 discrete risk gr oups of recurrence after radical prostatectomy and confirmed use of a prior 3 risk group model. Although the variables of ethnicity, pretreatment PSA, highest Gleason sum on prostatectomy specimen and organ confinement status on surgical pathology upon which the model is based are easily obtained, m ore refined modeling with additional variables are needed to improve predic tion of intermediate risk in individuals.