Shen Cheng, Ni Haishun, Chen Zhan, You Junjie, Zheng Bing
Department of Urology, Affiliated Hospital 2 of Nantong University, Nantong City, Jiangsu Province, China.
Jiangsu Nantong Urological Clinical Medical Center, Nantong City, Jiangsu Province, China.
Sci Prog. 2025 Jul-Sep;108(3):368504251363901. doi: 10.1177/00368504251363901. Epub 2025 Jul 29.
ObjectiveThis study sought to develop a prediction model for double-J pipe scab following radical total cystectomy.MethodsThis retrospective study included clinical data on 175 patients who underwent routine double-J pipe replacement after radical total cystectomy. A double-J pipe scab was the nomogram's outcome. Boruta feature selection and the least absolute shrinkage selection operator (LASSO) approach were employed to predictions as efficiently as possible. Using multiple logistic regression, predictive models were created and displayed as nomograms. Nomogram performance was assessed using decision curve analysis, calibration plots, and receiver operating characteristic (ROC) curves. By computing the validation cohort's performance, the model was internally validated.ResultsThis study covered 175 patients in total. In twenty-nine individuals (16.57%), a double-J pipe scab formed. Every participant was randomly split into two groups: training ( = 122) and validation ( = 53). As predictors, this nomogram included urine leukocytes, urinary PH, daily water intake, BMI, and double-J pipe brand. Excellent identification performance is indicated by the training and verification groups' ROC curves, while the calibration curves demonstrate both groups' excellent correction outcomes.ConclusionThis study establishes a foundation for preventing and treating double-J pipe stones. It has a substantial predictive value for the occurrence of double-J pipe stones in the double-J pipe following radical total cystectomy.
目的
本研究旨在建立根治性全膀胱切除术后双J管结痂的预测模型。
方法
这项回顾性研究纳入了175例行根治性全膀胱切除术后常规更换双J管患者的临床资料。双J管结痂是列线图的结果。采用Boruta特征选择和最小绝对收缩选择算子(LASSO)方法以尽可能高效地进行预测。使用多元逻辑回归创建预测模型并将其显示为列线图。使用决策曲线分析、校准图和受试者工作特征(ROC)曲线评估列线图性能。通过计算验证队列的性能对模型进行内部验证。
结果
本研究共纳入175例患者。29例(16.57%)形成双J管结痂。每位参与者被随机分为两组:训练组(n = 122)和验证组(n = 53)。该列线图纳入尿液白细胞、尿pH值、每日饮水量、BMI和双J管品牌作为预测因素。训练组和验证组的ROC曲线表明具有出色的识别性能,而校准曲线表明两组均具有出色的校正结果。
结论
本研究为双J管结石的防治奠定了基础。对根治性全膀胱切除术后双J管中双J管结石的发生具有重要的预测价值。