Prediction model for biochemical recurrence after radical prostatectomy based on pathological features

doi:10.3969/j.issn.1006-7795.2026.02.007

Abstract

Abstract: Objective To explore pathological features that might affect biochemical recurrence in patients with prostate cancer following radical prostatectomy, and to establish a risk prediction model for biochemical recurrence. Methods A total of 237 prostate cancer patients who underwent radical prostatectomy were retrospectively enrolled. Clinical and pathological data were retrieved. Biochemical recurrence data were collected from outpatient follow-up records, and Kaplan-Meier analysis was performed to assess the influence of different pathological features on biochemical recurrence-free survival (BRS). Cox regression analyses were performed to identify risk factors for BRS. A prediction model and nomogram for 12-month BRS were established with these risk factors. Results Pathological stage, International Society of Urological Pathology (ISUP) grade group, positive basal and bladder neck margin, and phosphatase and tensin homolog (PTEN) deletion were independent risk factors for BRS. Based on these factors, a prediction model and nomogram for 12-month BRS were built, and showed good discrimination (C-index = 0.810). Conclusion The biochemical recurrence prediction model for prostate cancer based on pathological features provides an easily accessible personalized prognostic assessment tool for clinical practice, which helps guide postoperative adjuvant treatment decisions and the formulation of intensive surveillance protocols.

Key words: prostate cancer, radical prostatectomy, pathological feature, biochemical recurrence, nomogram, prognosis

CLC Number:

Xiong Tianyu, Zhao Youquan, Xie Ping, Niu Yinong. Prediction model for biochemical recurrence after radical prostatectomy based on pathological features[J]. Journal of Capital Medical University, 2026, 47(2): 267-274.

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