Optimal Definition of Biochemical Recurrence in Patients Who Receive Salvage Radiotherapy Following Radical Prostatectomy for Prostate Cancer

Purpose This study proposed the optimal definition of biochemical recurrence (BCR) after salvage radiotherapy (SRT) following radical prostatectomy for prostate cancer. Materials and Methods Among 1,117 patients who had received SRT, data from 205 hormone-naive patients who experienced postSRT prostate-specific antigen (PSA) elevation were included in a multi-institutional database. The primary endpoint was to determine the PSA parameters predictive of distant metastasis (DM). Absolute serum PSA levels and the prostate-specific antigen doubling time (PSA-DT) were adopted as PSA parameters. Results When BCR was defined based on serum PSA levels ranging from 0.4 ng/mL to nadir+2.0 ng/mL, the 5-year probability of DM was 27.6%-33.7%. The difference in the 5-year probability of DM became significant when BCR was defined as a serum PSA level of 0.8 ng/ml or higher (1.0-2.0 ng/mL). Application of a serum PSA level of >= 0.8 ng/mL yielded a c-index value of 0.589. When BCR was defined based on the PSA-DT, the 5-year probability was 22.7%-39.4%. The difference was significant when BCR was defined as a PSA-DT <= 3 months and <= 6 months. Application of a PSA-DT <= 6 months yielded the highest c-index (0.660). These two parameters complemented each other; for patients meeting both PSA parameters, the probability of DM was 39.5%-44.5%; for those not meeting either parameter, the probability was 0.0%-3.1%. Conclusion A serum PSA level > 0.8 ng/mL was a reasonable threshold for the definition of BCR after SRT. In addition, a PSA-DT <= 6 months was significantly predictive of subsequent DM, and combined application of both parameters enhanced predictability.

Automated summary

This study proposed the optimal definition of biochemical recurrence after salvage radiotherapy following radical prostatectomy. Serum PSA levels and PSA doubling time were important predictive parameters for distant metastasis, and their combined application enhanced predictability.