STATISTICAL MODELING USING PREOPERATIVE PROGNOSTIC VARIABLES IN PREDICTING EXTRACAPSULAR EXTENSION AND PROGRESSION AFTER RADICAL PROSTATECTOMY FOR PROSTATE-CANCER

Objective: To predict the risk of extracapsular extension and postoper ative recurrence before radical prostatectomy (RP) for prostate cancer . Methods: We performed multivariate Cox regression analysis on preope rative variables in 260 clinically localized prostate cancer patients who underwent RP. With these data, we constructed a relative risk of r ecurrence (R-r) equation and an equation to predict the probability of extracapsular extension (P-ECE) before RP. Results: R-r is calculated as exp[(0.47 x race + 0.14 x PSA(ST)) + (0.13 x worst biopsy Gleason sum) + (1.03 x stage Tlc) + (1.55 x stage T2b,c)], where PSA(ST) indic ates a sigmoidal transformation of prostate-specific antigen. P-ECE is calculated as 1/[1 + exp(-Z)], where Z = -2.47 + 0.15 (PSA(ST)) + 0.3 1 (worst biopsy Gleason sum) + 0.18 (race) + 0.16 (stage Tlc) + 0.38 ( stage T2b,c). Conclusion: These two equations can be used preoperative ly to predict the probability of extracapsular disease and the risk of prostate-specific antigen recurrence in patients undergoing RP.