PSA Doubling Time and Absolute PSA Predict Metastasis-free Survival in Men With Biochemically Recurrent Prostate Cancer After Radical Prostatectomy

In men with biochemically-recurrent prostate cancer, prostate-specific antigen doubling time <= 7.5 months, prostate-specific antigen >= 0.5 ng/mL, and Gleason score are independent predictors of metastasis-free survival on multivariable analysis. These data can assist physicians during discussions with patients regarding the risk of developing metastatic disease and for clinical trial planning. Introduction: The aim of this study was to investigate the association of prostate-specific antigen (PSA) values on metastasis-free survival (MFS) in men with biochemically recurrent prostate cancer (BRPC) and PSA doubling time (PSADT) < 12 months. This dataset also reflects an update with longer follow-up of our prior publications on the natural history of BRPC in the absence of treatment. Materials and Methods: In this report, we combined databases from the Center for Prostate Disease Research and Johns Hopkins University (CPDR/JHU). In the CPDR/JHU radical prostatectomy database (30,936 total patients), 656 men with BRPC (> 0.2 ng/mL) after prostatectomy and PSADT < 12 months, who received no adjuvant/salvage androgen deprivation and/or radiation therapy, were prospectively followed until radiologic evidence of metastasis and are included in this analysis. Results: Metastasis occurred in 250 of 656 patients with BRPC (median follow-up, 5 years). PSADT < 7.5 months and Gleason score were independent risk factors for distant metastasis in multivariable analysis. Risk of metastasis increased for PSADT 6.01 to 7.50, 4.51 to 6.0, 3.01 to 4.50, and <= 3.0 months, after adjusting for Gleason score. A PSA value >= 0.5 ng/mL significantly and independently increased risk of metastasis in patients with PSADT < 12 months (hazard ratio, 2.79; 95% confidence interval, 1.47-5.29; P = .001). Conclusions: In men with PSADT < 12 months, PSADT <= 7.5 months, PSA >= 0.5 ng/mL, and Gleason score are independent predictors of MFS on multivariable analysis. (C) 2019 Elsevier Inc. All rights reserved.