食管癌患者术后呼吸衰竭的危险因素及其预测模型构建  

Risk factors for postoperative respiratory failure in patients with esophageal cancer and the prediction model establishment

作　　者：杨博 白悦 郎丽丽 曹群 朱公建 庄雷云 孙大强[3] YANG Bo;BAI Yue;LANG Lili;CAO Qun;ZHU Gongjian;ZHUANG Leiyun;SUN Daqiang(Department of Thoracic Surgery,Sun Yat-sen University Cancer Center Gansu Hospital,Lanzhou,730050,P.R.China;Gansu University of Chinese Medicine,Lanzhou,730000,P.R.China;Department of Thoracic Surgery,Tianjin Chest Hospital,Tianjin,300222,P.R.China)

机构地区：[1]中山大学附属肿瘤医院甘肃医院胸外科,兰州730050 [2]甘肃中医药大学,兰州730000 [3]天津市胸科医院胸外科,天津300222

出　　处：《中国胸心血管外科临床杂志》2025年第3期353-359,共7页Chinese Journal of Clinical Thoracic and Cardiovascular Surgery

基　　金：甘肃省自然科学基金(22JR5RA647);2023陇原青年创新创业人才(个人)项目(211278291049)。

摘　　要：目的探索食管癌患者术后呼吸衰竭(respiratory failure,RF)的危险因素,构建基于最小绝对收缩和选择算子(least absolute shrinkage and selection operator,LASSO)-logistic回归的预测模型,并对所建模型进行可视化处理。方法回顾性纳入2020—2023年在中山大学附属肿瘤医院甘肃医院胸外科接受手术治疗的食管癌患者,根据术后是否发生RF,将患者分为RF组和非RF(non-respiratory failure,NRF)组。收集两组患者的临床资料,应用LASSO-logistic回归优化模型的特征选择,构建预测模型。基于Bootstrap法重复抽样1000次对模型进行内部验证。结果共纳入217例患者,其中RF组24例,男22例、女2例,平均年龄(63.33±9.10)岁;NRF组193例,男161例、女32例,平均年龄(62.14±8.44)岁。LASSO-logistic回归分析显示,一秒率(forced expiratory volume in one second/forced vital capacity,FEV1/FVC)占预计值的百分比(percentage of FEV1/FVC to predicated value,FEV1/FVC%pred)[OR=0.944,95%CI(0.897,0.993),P=0.026]、术后吻合口瘘[OR=4.106,95%CI(1.457,11.575),P=0.008]、术后肺部感染[OR=3.776,95%CI(1.373,10.388),P=0.010]是食管癌术后RF的危险因素。根据上述危险因素构建预测模型,受试者工作特征曲线下面积为0.819[95%CI(0.737,0.901)]。校准曲线Hosmer-Lemeshow检验表明该模型具有良好的拟合优度(P=0.527)。决策曲线显示阈值概率在5%~50%时模型具有良好的临床净收益。结论FEV1/FVC%pred、术后吻合口瘘、术后肺部感染是食管癌患者术后RF的危险因素,基于LASSO-logistic回归分析法构建的预测模型有望帮助医务人员筛选出高危患者,以便进行早期个体化干预。Objective To explore the risk factors for postoperative respiratory failure(RF)in patients with esophageal cancer,construct a predictive model based on the least absolute shrinkage and selection operator(LASSO)-logistic regression,and visualize the constructed model.Methods A retrospective analysis was conducted on patients with esophageal cancer who underwent surgical treatment in the Department of Thoracic Surgery,Sun Yat-sen University Cancer Center Gansu Hospital from 2020 to 2023.Patients were divided into a RF group and a non-RF(NRF)group according to whether RF occurred after surgery.Clinical data of the two groups were collected,and LASSO-logistic regression was used to optimize feature selection and construct the predictive model.The model was internally validated by repeated sampling 1000 times based on the Bootstrap method.Results A total of 217 patients were included,among which 24 were in the RF group,including 22 males and 2 females,with an average age of(63.33±9.10)years;193 were in the NRF group,including 161 males and 32 females,with an average age of(62.14±8.44)years.LASSO-logistic regression analysis showed that the percentage of forced expiratory volume in one second/forced vital capacity(FEV1/FVC)to predicted value(FEV1/FVC%pred)[OR=0.944,95%CI(0.897,0.993),P=0.026],postoperative anastomotic fistula[OR=4.106,95%CI(1.457,11.575),P=0.008],and postoperative lung infection[OR=3.776,95%CI(1.373,10.388),P=0.010]were risk factors for postoperative RF in patients with esophageal cancer.Based on the above risk factors,a predictive model was constructed,with an area under the receiver operating characteristic curve of 0.819[95%CI(0.737,0.901)].The Hosmer-Lemeshow test for the calibration curve showed that the model had good goodness of fit(P=0.527).The decision curve showed that the model had good clinical net benefit when the threshold probability was between 5%and 50%.Conclusion FEV1/FVC%pred,postoperative anastomotic fistula,and postoperative lung infection are risk factors for postoperative RF in

关 键 词：食管癌 呼吸衰竭 LASSO-logistic回归 预测模型 

分 类 号：R563.8[医药卫生—呼吸系统] R735.1[医药卫生—内科学]