Prediction of biochemical recurrence after robot‐assisted radical prostatectomy: Analysis of 784 Japanese patients

Objectives To examine biochemical recurrence after robot‐assisted radical prostatectomy in J apanese patients, and to develop a risk stratification model for biochemical recurrence. Methods The study cohort consisted of 784 patients with localized prostate cancer who underwent robot‐assisted radical prostatectomy without neoadjuvant or adjuvant endocrine therapy. The relationships of biochemical recurrence with perioperative findings were evaluated. The prognostic factors for biochemical recurrence‐free survival were evaluated using C ox proportional hazard model analyses. Results During the follow‐up period, 80 patients showed biochemical recurrence. The biochemical recurrence‐free survival rates at 1, 3, and 5 years were 92.2%, 85.2% and 80.1%, respectively. In univariate analysis, the prostate‐specific antigen level, prostate‐specific antigen density, biopsy G leason score, percent positive core, pathological T stage, pathological G leason score, lymphovascular invasion, perineural invasion and positive surgical margin were significantly associated with biochemical recurrence. In multivariate analysis, prostate‐specific antigen density ≥0.4 ( P = 0.0011), pathological T stage ≥3a ( P = 0.002), pathological G leason score ≥8 ( P = 0.007) and positive surgical margin ( P < 0.0001) were independent predictors of biochemical recurrence. The patients were stratified into three risk groups according to these factors. The 5‐year biochemical recurrence‐free survival rate was 89.4% in the low‐risk group, 65.6% in the intermediate‐risk group and 30.3% in the high‐risk group. Conclusions The prostate‐specific antigen density, pathological T stage, pathological G leason score and positive surgical margin were independent prognostic factors for biochemical recurrence. The risk stratification model developed using these four factors could help clinicians identify patients with a poor prognosis who might be good candidates for clinical trials of alternative management strategies.