ArticleScientific reports2025
Development and validation of a nomogram for predicting prostatic urethral involvement in bladder cancer.
Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- A Dynamic Online Nomogram for Predicting Postoperative Acute Kidney Injury After Sleeve Gastrectomy.Medical science monitor : international medical journal of experimental and clinical research · 2026Article
- Article
- Development of a radiomics and clinical feature-based nomogram for preoperative prediction of pathological grade in bladder cancer.Frontiers in oncology · 2025Article
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Authors and funding
11 authors.
Funding
Abstract
To identify risk factors for prostatic urethral involvement (PUI) in bladder cancer and develop an accurate nomogram prediction model. We retrospectively analyzed 295 male patients with bladder urothelial carcinoma undergoing transurethral prostatic biopsy. Risk factors of PUI in bladder cancer were assessed through univariate and multivariate logistic regression analyses. A nomogram model for predicting clinical outcomes was constructed based on the independent risk factors of PUI. The performance of the model was internally validated by 'leave-one-out' cross-validation (LOOCV) and calibration curve. The decision curve analysis (DCA) was applied to evaluate the clinical utility. Further evaluation of PUI and associated risk factors within the context of non-muscle-invasive bladder cancer (NMIBC) were assessed using the same methods. Multivariate analysis revealed that the tumor multiplicity (OR = 2.44, 95% CI 1.17-5.26, P = 0.019), trigonal/neck tumor location (OR = 7.42, 95% CI 4.00-14.24, P < 0.001), high-grade tumor (OR = 5.17, 95% CI 1.52-21.95, P = 0.014), and recurrent carcinoma (OR = 4.39, 95% CI 2.32-8.63, P < 0.001) were identified as independent risk factors for PUI in bladder cancer (all P < 0.05). A final prediction nomogram was established based on these four independent risk factors. After internally validated by LOOCV, the nomogram showed strong discrimination (area under the curve, AUC = 0.8, 95%CI 0.749-0.851) and excellent calibration. DCA further confirmed the model's clinical utility across a wide range of risk thresholds. Subgroup analysis in NMIBC yielded consistent results (AUC = 0.819, 95%CI 0.764-0.874). This nomogram provides a robust tool to stratify PUI risk in bladder cancer, guiding selective prostatic biopsies and personalized management. Integration into clinical workflows may reduce understaging and optimize outcomes. Further external validation is warranted.
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