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April 20, 2026Open Access

Establishment and validation of a risk scoring model for predicting the risk of bladder stones in patients with benign prostatic hyperplasia

Key Points

This research aims to identify risk factors for bladder stones in patients with benign prostatic hyperplasia and develop a predictive model.
Conducted a retrospective analysis with 446 BPH patients, split into training and validation sets.
Utilized univariate and multivariate logistic regression, ROC analysis, and correlation analysis.
Identified independent risk factors through LASSO regression and validated model performance with AUC and calibration tests.
Seven risk factors for bladder stones were identified: age, IPSS, serum uric acid, IPP, PUA, TPV, and urinary red blood cell count.
The nomogram achieved an AUC of 0.865 in the training set and 0.882 in the validation set, indicating excellent discrimination.
Model calibration was deemed accurate, supporting its clinical utility.

Abstract

Purpose The aim of this study is to identify independent risk factors for bladder stones in patients with benign prostatic hyperplasia (BPH), and to develop and validate a nomogram prediction model for assessing the risk of bladder stones in this patient population. Methods Retrospective analysis included 446 BPH patients (106 with bladder stones, 340 without) who underwent transurethral resection of the prostate (2023–2025). Univariate ROC (receiver operating characteristic), correlation analysis, LASSO regression, and multivariate logistic regression were used for variable screening and model construction. The cohort was split into training (70%) and validation (30%) sets. Model performance was evaluated via AUC (discrimination), calibration curves, Hosmer-Lemeshow test (calibration), and DCA (clinical utility). Results Seven independent risk factors were identified: age, IPSS (International Prostate Symptom Score), serum uric acid, IPP (intravesical prostatic protrusion), PUA (prostatic urethral angle), TPV (total prostate volume), and urinary red blood cell count. The nomogram showed excellent discrimination (AUC: 0.865 in training set, 0.882 in validation set), good calibration ( p 0.05), and robust clinical utility. Conclusion The nomogram overcomes univariate and multicollinearity limitations, enabling precise individualized risk assessment of bladder stones in BPH patients. It serves as a reliable tool for clinicians to guide personalized monitoring and prevention, potentially reducing incidence and healthcare burdens.

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