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

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.