Construction and verification of a predictive model for immediate social urinary control recovery after robot assisted radical prostatectomy for prostate cancer
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摘要:目的
构建并验证预测机器人辅助前列腺癌根治术(RARP)患者拔管后即刻社会性尿控恢复情况的列线图模型。
方法回顾性分析确诊前列腺癌并由单一术者行手术治疗的64例患者的临床资料, 评估患者拔除尿管后的即刻社会性尿控恢复情况。采用LASSO回归进行特征筛选，将选取的特征进行多元Logistic回归分析，确定独立危险因素，并构建列线图模型。采用受试者工作特征(ROC)曲线、Hosmer-Lemeshow检验和校准曲线、临床决策曲线(DCA)分析模型的鉴别性、校准性和临床实用性。
结果构建列线图模型的变量包括D'Amico分级、外提肌距离。ROC曲线的曲线下面积(AUC)为0.742(95%CI: 0.500~0.913, P＜0.001)，表明该模型具有较好的鉴别性; 校准曲线表明该模型具有较好的校准能力; DCA显示该模型具有较好的临床实用性。
结论本研究构建的列线图模型可以预测RARP患者术后即刻社会性尿控恢复情况，能够进一步量化即刻达到社会性尿控的概率。
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关键词:
- 前列腺癌 /
- 机器人辅助前列腺癌根治术 /
- 拔管 /
- 即刻社会性尿控 /
- 列线图模型
Abstract:ObjectiveTo construct and verify a nomogram model for predicting social urinary control recovery in patients undergoing robot-assisted radical prostatectomy (RARP) immediately after extubation.
MethodsA retrospective analysis was conducted on the clinical data of 64 patients diagnosed with prostate cancer and treated by a single surgeon. The immediate urinary control status of the patients after removal of the catheter was evaluated, and LASSO regression was used for feature screening. Multiple Logistic regression was performed on the selected features to determine independent risk factors and establish a predictive model. And the discriminability, calibration, and clinical practicality of the model were evaluated using receiver operating curve (ROC), Hosmer Lemeshow test and calibration curve, and clinical decision curve (DCA) analysis.
ResultsThe variables in the outcome prediction model include D'Amico grading and distance of the levator muscle. The area under the ROC curve (AUC) was 0.742 (95%CI, 0.500 to 0.913, P < 0.001), indicating that the model had good discriminability. The calibration curve indicated that the model had good calibration ability. The DCA curve showed good clinical practicality.
ConclusionThe clinical predictive model developed inthis study can predict the recovery of immediate social urinary control in patients with RARP after surgery, which can further quantify the probability of achieving immediate social continence.
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图 1 尿道解剖学特征
ILD: 提肌内边界到前列腺尖尾缘以下尿道的最窄距离(轴向T2加权图像); OLD: 与ILD(轴向T2加权图像)相同的水平上测量的离提肌外缘的距离; MUL: 膜性尿道长度; OIM: 闭孔内肌厚度; PMW: 耻骨直肠肌厚度; PSC: 尿道周围括约肌厚度; UWT: 尿道壁厚度。
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图 2 LASSO回归模型筛选人口统计学和临床特征
A: 9个变量的LASSO系数剖面，根据log lambda序列绘制了系数剖面图; B: LASSO模型中最优参数(lambda)的选择采用了K折交叉验证(k=15), 最优lambda会产生3个系数非零的特征，在最小均方误差以及与最小均方误差相隔1个标准误的位置画出虚线，本研究采用的是与最小均方误差相隔1个标准误时的lambda值。
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图 6 列线图模型的决策曲线分析
DCA曲线表示即刻社会性尿控预测模型; All曲线表示假设没有患者实现即刻社会性尿控; None曲线表示假设所有患者都实现即刻社会性尿控。
表 1 2组患者基线临床特征比较(x±s)[n(%)]
基线临床特征 分类 达到组(n=18) 未达到组(n=46) P D′Amico分级 低危 8(44.4) 4(8.7) 0.004 中危 3(16.7) 14(30.4) 高危 7(38.9) 28(60.9) 术中出血量/mL 150.0±102.0 186.0±108.0 0.221 体质量指数/(kg/m2) 23.6±2.0 24.7±3.1 0.087 年龄/岁 65.6±8.3 68.8±6.1 0.149 前列腺体积/mm3 42.6±24.6 35.9±11.6 0.283 症状严重程度 轻度 11(61.1) 29(63.0) 0.431 中度 3(16.7) 12(26.1) 重度 4(22.2) 5(10.9) 神经保留状况 不保留 13(72.2) 36(78.3) 0.807 保留单侧 3(16.7) 7(15.2) 保留双侧 2(11.1) 3(6.5) 
下载: 导出CSV
表 2 预测因素
变量 β OR 95%CI P D′Amico分级 0.837 2.309 1.092~5.130 0.004 外提肌距离 0.217 1.241 1.043~1.550 0.017
下载: 导出CSV
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