PREOPERATIVE MODEL FOR PREDICTING PROSTATE SPECIFIC ANTIGEN RECURRENCE AFTER RADICAL PROSTATECTOMY USING PERCENT OF BIOPSY TISSUE WITH CANCER, BIOPSY GLEASON GRADE AND SERUM PROSTATE SPECIFIC ANTIGEN

Abstract

We developed a preoperative model to risk stratify patients for prostate specific antigen (PSA) failure following radical prostatectomy (RP) and identify those at high risk who would be potential candidates for neoadjuvant clinical trials. A retrospective survey of 459 patients from the SEARCH Database treated with RP between 1990 and 2002 was done. Multivariate analysis was used to compare the preoperative variables of patient age, race, PSA, biopsy Gleason score, clinical stage and percent of prostate needle biopsy tissue with cancer for the ability to predict time to PSA recurrence following RP. Significant independent predictors were combined to create a novel risk grouping model. On multivariate analysis biopsy Gleason score (p < 0.001), percent of biopsy tissue with cancer (p < 0.001) and serum PSA (p = 0.001) were the only significant independent predictors of PSA failure. Combining these 3 significant predictors of PSA failure using previously published cutoff points for each variable generated a 4 tier preoperative model for predicting biochemical failure following RP (HR 1.91 for each 1 risk category increase, CI 1.62 to 2.26, p < 0.001). The model further stratified patients who were already stratified into low, intermediate and high risk groups based on a previously described model using PSA, biopsy Gleason score and clinical stage. A simplified table was developed to predict the risk of biochemical recurrence within 2 years following surgery, as stratified by percent of tissue with cancer, PSA and biopsy Gleason score. A combination of serum PSA, biopsy Gleason score and percent of prostate biopsy tissue with cancer define a new preoperative model for predicting PSA failure following RP. This model further stratified patients who were already stratified based on PSA, biopsy Gleason score and clinical stage, and it can be used preoperatively to identify patients at high risk who would be candidates for neoadjuvant clinical trials. Using this model an easy to use table was developed to predict preoperatively the 2-year risk of PSA recurrence following RP.