Background: Serum PSA has been widely applied to monitor prostate cancer after treatment. Compared to a single static value, PSA dynamics may provide additional prognostic information. Although PSA velocity and doubling time have demonstrated prognostic value, their clinical utility is limited by the need for prolonged longitudinal PSA follow-up. This study aimed to evaluate the prognostic potential of early postoperative PSA dynamics following radical prostatectomy. Methods: A retrospective cohort study of 3474 patients who underwent radical prostatectomy with available pre- and postoperative serum PSA measurements was analyzed. A population-based approach was used to characterize early postoperative PSA dynamics and estimate the time required for PSA to decline to undetectable levels (<0.1 ng/mL). Accordingly, patients were classified into early remission (≤60 days), delayed remission (>60 days), or persistent PSA (failure to achieve undetectable PSA). Associations between postoperative PSA dynamics and clinical outcomes were evaluated. Results: Biochemical recurrence rates differed across the early remission, delayed remission, and persistent PSA groups (5.3%, 7.7%, and 24.0%). All-cause mortality similarly increased across these groups (1.1%, 1.9%, and 5.8%, respectively). Cox proportional hazards models confirmed the difference in recurrence-free and overall survival among PSA clearance groups. Conclusions: Early postoperative PSA dynamics after radical prostatectomy are strongly associated with recurrence and survival outcomes. Both PSA trajectory patterns and PSA clearance speed carry important prognostic information. Early postoperative PSA monitoring may support risk stratification and guide individualized postoperative surveillance.
Cancers. 2026 Mar 06*** epublish ***
Yukun Tan, Qing H Meng, Merve Dede, Ingold Huang, Hui Song, Ken Chen, Yu Zhang
Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA., Department of Laboratory Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA., Department of Pathology, Kaiser Permanente, Santa Clara, CA 95051, USA., Department of Enterprise Data Engineering & Analytics, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA.