结肠癌根治术后严重并发症危险因素分析及动态列线图预测模型构建OA北大核心CSTPCD
Risk factors for comprehensive complication index after radical resection of colon cancer and establishment of its dynamic nomogram prediction model
目的 探讨结肠癌根治术后综合并发症指数(CCI)≥26.2分的独立危险因素,以此建立动态网页列线图预测模型并进行验证.方法 回顾性收集2020年11月-2022年4月于江南大学附属医院接受根治性手术的结肠癌患者的临床资料,基于入院时间分为主要队列(2020年11月-2021年10月,n=438)与验证队列(2021年11月-2022年4月,n=196).根据CCI计算器(http://www.assessurgery.com)得出所有患者的CCI评分,采用单因素和多因素logistic回归分析结肠癌患者术后CCI≥26.2的危险因素,并构建列线图模型.采用受试者工作特征(ROC)曲线、C指数及校准曲线评估列线图模型的区分度和一致性,决策曲线分析评估模型的临床获益,并对模型进行内部验证.结果 主要队列438例患者中,63例(14.4%)术后CCI≥26.2分.多因素logistic回归分析显示,年龄≥60岁(OR=2.662,95%CI 1.341～5.285,P=0.005)、低第3腰椎旁骨骼肌指数(L3MI)(OR=4.572,95%CI 2.435～8.583,P<0.001)、NRS2002 评分≥3 分(OR=4.281,95%CI 2.304～7.952,P<0.001)和术前伴有肠梗阻(OR=3.785,95%CI 1.971～7.268,P<0.001)是结肠癌患者术后CCI≥26.2分的独立危险因素.据此建立静态及网页版动态列线图预测模型(https://jndxfsyywcwksyf.shinyapps.io/DynNomCCI/).列线图模型的C指数和曲线下面积(AUC)分别为0.742和0.787;校准曲线显示模型的预测概率与实际概率具有较好的一致性;内部验证显示模型具有良好的区分度(C指数=0.722,AUC=0.795)和预测一致性;决策曲线分析显示该预测模型具有临床获益和应用价值.结论 基于4个独立危险因素构建的动态列线图模型能够便捷、可靠地预测结肠癌术后CCI≥26.2分的概率,有助于优化术前评估体系,制定精准的个体化诊疗方案,促进患者快速康复.
Objective To investigate the independent risk factors of comprehensive complication index(CCI)≥26.2 after radical resection of colon cancer,and use these factors to establish and verify a dynamic web-based nomogram model.Methods The clinical data of colon cancer patients who underwent radical resection in the Affiliated Hospital of Jiangnan University from November 2020 to April 2022 were retrospectively collected,and divided into main cohort(November 2020 to October 2021,n=438)and validation cohort(November 2021 to April 2022,n=196).CCI scores of all patients were obtained based on CCI calculator(http://www.assessurgery.com).Univariate and multivariate logistic regression analysis were performed to identify the risk factors for CCI≥26.2,and a nomogram model was constructed.Receiver operator characteristic curve(ROC),C index and calibration curve were used to evaluate the differentiation and consistency of predictive nomogram model,and the decision curve analysis was conducted to assess the clinical benefits of the model.Internal validation of the model is performed in the validation cohort.Results A total of 438 patients were identified in present study,of which 63 cases(14.4%)had CCI≥26.2.Multivariate logistic regression analysis revealed that age≥60 years(OR=2.662,95%CI 1.341-5.285,P=0.005),low third lumbar spine skeletal muscle mass index(L3MI;OR=4.572,95%CI 2.435-8.583,P<0.001),NRS2002≥3(OR=4.281,95%CI 2.304-7.952,P<0.001),and preoperative bowel obstruction(OR=3.785,95%CI 1.971-7.268,P<0.001)were significant independent risk factors for postoperative CCI≥26.2.Based on these results,a static and web-based dynamic nomogram was established(https://jndxfsyywcwksyf.shinyapps.io/DynNomCCI/).The C-index and area under the curve(AUC)of the nomogram were 0.742 and 0.787,respectively.The calibration curve indicated a good consistency between the predicted probability and the actual probability.In the validation cohort,the nomogram also presented good discrimination(C-index=0.722,AUC=0.795)and predictive consistency.The decision curve analysis indicated the clinical benefit and application value of the nomogram prediction model.Conclusion This easy-to-use dynamic nomogram based on 4 independent risk factors can conveniently and reliably predict the probability of CCI≥26.2 after radical resection of colon cancer,which helps optimize the preoperative evaluation system,formulate precise individualized treatment strategies,and enhance recovery after surgery.
史益凡;沈晓明;杨增辉;夏李;许炳华;鲍传庆
江南大学附属医院胃肠外科,江苏无锡 214122
临床医学
结肠癌综合并发症指数骨骼肌指数列线图模型
colon cancercomprehensive complication indexskeletal muscle mass indexnomogram model
《解放军医学杂志》 2024 (004)
416-425 / 10
This work was supported by the Wuxi Municipal Health Commission Youth Scientific Research Project(Q202049) 无锡市卫生健康委员会青年基金项目(Q202049)
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