非小细胞肺癌患者术后下肢深静脉血栓形成的列线图预测模型构建与评估

Construction and evaluation of a nomogram prediction model for postoperative deep vein thrombosis of lower extremities in patients with non-small cell lung cancer

目的 构建预测非小细胞肺癌患者术后下肢深静脉血栓(DVT)形成风险的列线图模型,并评估模型的区分度和一致性。方法 选取2016年1月~2022年3月本院收治的术后发生DVT的非小细胞肺癌患者60例(发生DVT组),同期选取本院收治的术后未发生DVT的非小细胞肺癌患者70例(未发生DVT组)。收集患者临床资料,Logistic回归分析影响非小细胞肺癌患者术后DVT形成的危险因素。采用R软件构建预测非小细胞肺癌患者术后DVT形成风险的列线图模型,并使用ROC曲线及校准曲线验证列线图模型的区分度和一致性。结果 发生DVT组患者合并糖尿病比例、肺腺癌比例、肺癌Ⅲ期比例、术前化疗比例、开胸手术比例、年龄≥70岁比例高于未发生DVT组患者,差异有统计学意义(P<0.05);多因素Logistic回归显示,合并糖尿病、肺腺癌、肺癌Ⅲ期、年龄≥70岁是非小细胞肺癌患者术后DVT的危险因素(P<0.05);内部验证显示构建的列线图预测模型具有较好的区分度(ROC曲线下面积为0.900)与一致性(Hosmer-Lemeshow拟合优度检验χ~2=6.016,P=0.538);外部验证结果显示校准曲线预测概率与实际概率接近,有良好的一致性及区分度。结论 研究构建的非小细胞肺癌患者术后DVT风险的列线图预测模型具有较好的区分度和一致性。

Objective To construct a nomogram model to predict the risk of postoperative deep vein thrombosis(DVT) in patients with non-small cell lung cancer,and to evaluate the discrimination and consistency of the model.Methods From January 2016 to March 2022,60 patients with non-small cell lung cancer who developed DVT after the operation were selected in this hospital(DVT group),at the same time,70 patients with non-small cell lung cancer who did not develop DVT after operation in our hospital were selected(non-DVT group).The clinical data of patients were collected,and Logistic regression was used to analyze the risk factors affecting the formation of DVT in patients with non-small cell lung cancer.R software was used to construct a nomogram model to predict the risk of postoperative DVT in patients with non-small cell lung cancer,and the ROC curve and calibration curve were used to verify the discrimination and consistency of the nomogram model.Results The proportion of patients with diabetes mellitus,lung adenocarcinoma,stage III lung cancer,preoperative chemotherapy,thoracotomy,and age ≥70 years old in the DVT group was higher than that in the non-DVT group,with statistical significance(P<0.05).Multivariate Logistic regression showed the risk factors of postoperative DVT in patients with diabetes mellitus,lung adenocarcinoma,lung cancer stage III,and non-small cell lung cancer aged ≥70 years(P<0.05).Internal verification showed that the constructed nomogram prediction model had good differentiation(area under the ROC curve was 0.900) and consistency(Hosmer-Lemeshow goodness of fit test χ~2=6.016,P=0.538).External verification results show that the predicted probability of the calibration curve is close to the actual probability,and has good consistency and differentiation.Conclusion The nomogram prediction model for postoperative DVT risk in patients with non-small cell lung cancer established in the study has good differentiation and consistency.