Evidence map›Paper›PMID 42078429›Full record

ArticleFrontiers in medicine2026

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

Yuli Luo, Yi Gao, Hongzhi Fang, Changjian Shi, Jie Xu, Xinyi Li, Yunfei Li

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Article in Frontiers in medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Yuli Luo *Department of Urology, Renmin Hospital, Hubei University of Medicine, Shiyan, Hubei, China.
Yi Gao *Department of Urology, Renmin Hospital, Hubei University of Medicine, Shiyan, Hubei, China.
Hongzhi FangDepartment of Urology, Renmin Hospital, Hubei University of Medicine, Shiyan, Hubei, China.
Changjian ShiDepartment of Urology, Renmin Hospital, Hubei University of Medicine, Shiyan, Hubei, China.
Jie XuDepartment of Urology, Renmin Hospital, Hubei University of Medicine, Shiyan, Hubei, China.
Xinyi LiDepartment of Urology, Renmin Hospital, Hubei University of Medicine, Shiyan, Hubei, China.
Yunfei LiDepartment of Urology, Renmin Hospital, Hubei University of Medicine, Shiyan, Hubei, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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 ( 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.

Indexed as

benign prostatic hyperplasiabladder stonesnomogrampredictive modelrisk factors

Identifiers

PMID42078429
PMCPMC13128432

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.