Risk prediction for 12-month post-prostatectomy urinary incontinence to support survivorship care: development and same-center temporal validation of a perioperative model
Year: 2026
Type: article
Study design: Observational Study
Abstract: Background: Persistent post-prostatectomy urinary incontinence (PPI) is a survivorship problem after radical prostatectomy with continuing implications for daily function, rehabilitation, follow-up, and supportive care. Risk stratification could help target these services, but uncommon events constrain model complexity and require evaluation beyond discrimination. Objective: To develop a perioperative model for PPI 12 months after catheter removal using LASSO-penalized logistic regression, compare it with a constrained gradient boosting machine (GBM), and examine temporal performance in a later same-center cohort. Methods: The development cohort comprised 726 patients with 51 PPI events (7.0%) and 19 candidate predictors. LASSO tuning used the one-standard-error rule within resampling, and the strategies were compared by nested repeated stratified five-fold cross-validation. The selected LASSO model was refitted to the full development cohort and applied without coefficient updating or recalibration to 465 later patients with 38 events (8.2%). Evaluation included ROC-AUC, average precision, Brier score, calibration-in-the-large (CITL), calibration slope, threshold-dependent measures, and decision-curve analysis. Results: Eight original predictors were retained: age, preoperative International Prostate Symptom Score, ln(1 + prostate-specific antigen), operative time, postoperative hospital stay, smoking history, hypertension, and neurovascular bundle preservation. Nested internal validation yielded a ROC-AUC of 0.913 (95% CI 0.871-0.946), average precision of 0.542 (0.404-0.675), and Brier score of 0.046 (0.035-0.058) for LASSO, versus 0.896, 0.488, and 0.048 for constrained GBM. In the temporal cohort, ROC-AUC was 0.836 (0.763-0.900), average precision 0.409 (0.277-0.564), and Brier score 0.062 (0.045-0.081). CITL was 0.445 (0.012-0.808) and the calibration slope 0.850 (0.621-1.174), indicating average underprediction. At the development-derived threshold of 0.128, sensitivity was 0.500 and specificity 0.913. Decision-curve analysis indicated potential net benefit across thresholds of 2-30%. Conclusion: The LASSO model retained useful temporal discrimination but underestimated absolute risk, and the development-derived cutoff did not transport well. It is therefore better suited to continuous risk estimation for survivorship follow-up and rehabilitation planning than to a fixed binary triage rule. Independent geographic validation, local calibration assessment, and prospective evaluation of clinical impact are required before routine use.
Source: Frontiers in Public Health
Authors: Lang Tang, Ming Hao, Mengru Luo, Shizhu Li
Institutions: Guizhou University, The First People's Hospital of Guiyang
Language: English
Subfield: Urology
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $3,801
OpenAlex ID: W7223116595