Wan Mokhter Wan Mokhzani, Duan Xiaoping, Yang Jin, Mohamed Daud Mohamed Ashraf
School of Medical Sciences, Universiti Sains Malaysia, Health Campus, Kubang Kerian, Kelantan, Malaysia.
Department of Urology, Affiliated Hospital of Chengdu University, Chengdu University, Chengdu, China.
PLoS One. 2025 Feb 12;20(2):e0313557. doi: 10.1371/journal.pone.0313557. eCollection 2025.
To investigate the risk factors for urethral stricture (US) in patients with benign prostatic hyperplasia (BPH) after transurethral resection of the prostate (TURP) and to construct a nomogram model with predictive features.
Clinical data of 400 patients with BPH who underwent TURP between June 2020 and June 2023 at Chengdu University Hospital were retrospectively collected. The data were divided into US group and no US group. Univariate and multivariate logistic regression analyses were performed sequentially to identify independent risk factors associated with US. Based on the results of the multivariate analysis, a nomogram model predicting the risk of US was constructed. We assessed the discriminatory power and calibration of the models using the C index, ROC curves, and calibration plots. In addition, we performed a decision curve analysis to validate the clinical utility of the model.
Data from a total of 400 patients were included in this study, and 35 (8.75%) were diagnosed with US. The results of univariate and multivariate analyses indicated that the following five factors age, prostate size, Preoperative indwelling catheter, Preoperative urethral dilation, Postoperative indwelling catheter time were independent influences on the risk of US. Nomogram model of US was constructed using these independent influences. The area under the curve (AUC) of the subject's operating characteristic was 0.916 (95% CI: 0.868-0.959), and after internal validation, the corrected C-index remained at 0.916. This further validates the accuracy and reliability of the predictive model. Calibration plots and decision curve analyses demonstrated the good clinical value of the column-line diagram model.
The nomogram model we constructed can have some guidance in clinical work.
探讨良性前列腺增生（BPH）患者经尿道前列腺电切术（TURP）后尿道狭窄（US）的危险因素，并构建具有预测特征的列线图模型。
回顾性收集2020年6月至2023年6月在成都大学医院接受TURP的400例BPH患者的临床资料。将数据分为US组和非US组。依次进行单因素和多因素逻辑回归分析，以确定与US相关的独立危险因素。基于多因素分析结果，构建预测US风险的列线图模型。我们使用C指数、ROC曲线和校准图评估模型的辨别力和校准度。此外，我们进行了决策曲线分析以验证模型的临床实用性。
本研究共纳入400例患者的数据，其中35例（8.75%）被诊断为US。单因素和多因素分析结果表明，年龄、前列腺大小、术前留置导尿管、术前尿道扩张、术后留置导尿管时间这五个因素对US风险有独立影响。利用这些独立影响因素构建了US的列线图模型。受试者操作特征曲线下面积（AUC）为0.916（95%CI：0.868 - 0.959），内部验证后校正C指数仍为0.916。这进一步验证了预测模型的准确性和可靠性。校准图和决策曲线分析证明了列线图模型具有良好的临床价值。
我们构建的列线图模型在临床工作中具有一定的指导作用。
