Gu Zhuoran, Zheng Zongtai, Zhang Wentao, Mao Shiyu, Wang Shuai, Geng Jiang, Yao Xudong
Department of Urology, Shanghai Tenth People's Hospital; Institute of Urinary Oncology, Tongji University School of Medicine, Shanghai, China.
Department of Radiology, Shanghai Tenth People's Hospital, Tongji University School of Medicine, Shanghai, China.
Front Surg. 2023 Jan 6;9:1071093. doi: 10.3389/fsurg.2022.1071093. eCollection 2022.
This study aimed to develop a nomogram to predict the recovery of immediate urinary continence in laparoscopic radical prostatectomy (LRP) patients.
A prediction model was developed based on a dataset of 154 LRP patients. Immediate urinary continence was defined as free from using pads within 7 days after the removal of the urinary catheter. The least absolute shrinkage and selection operator regression (LASSO) model was applied to screen the features. Multivariate logistic regression analysis was used to establish prediction model integrating the features selected from the LASSO regression analysis. Receiver operating curve (ROC), calibration and decision curve analysis (DCA) were used to assess the model's discrimination, calibration and clinical utility.
The identified features of the prediction model included age, body mass index (BMI) and three pelvic anatomic parameters measured by MRI: membranous urethral length (MUL), intravesical prostatic protrusion length (IPPL) and puborectalis muscle width (PMW). The nomogram showed good discrimination with an are under the curve(AUC) of 0.914 (95% CI, 0.865-0.959, < 0.001). Moreover, good calibration was showed in the model. Lastly, DCA showed that the nomogram was clinically useful.
The developed novel nomogram that can predict the possibility for post-prostatectomy patients to recover immediate urinary continence could be used as a counseling tool to explain urinary incontinence to patients after LRP.
本研究旨在开发一种列线图，以预测腹腔镜根治性前列腺切除术（LRP）患者即时尿失禁的恢复情况。
基于154例LRP患者的数据集开发了一种预测模型。即时尿失禁定义为拔除导尿管后7天内无需使用尿垫。应用最小绝对收缩和选择算子回归（LASSO）模型筛选特征。采用多因素逻辑回归分析建立整合LASSO回归分析中所选特征的预测模型。采用受试者工作特征曲线（ROC）、校准和决策曲线分析（DCA）评估模型的辨别力、校准度和临床实用性。
预测模型确定的特征包括年龄、体重指数（BMI）以及通过MRI测量的三个盆腔解剖参数：膜性尿道长度（MUL）、膀胱内前列腺突出长度（IPPL）和耻骨直肠肌宽度（PMW）。列线图显示出良好的辨别力，曲线下面积（AUC）为0.914（95%CI，0.865-0.959，P<0.001）。此外，模型显示出良好的校准度。最后，DCA表明列线图具有临床实用性。
所开发的新型列线图可预测前列腺切除术后患者即时尿失禁恢复的可能性，可作为一种咨询工具，向LRP术后患者解释尿失禁情况。
