基于血清学指标构建Ⅲ~Ⅳ期非小细胞肺癌列线图模型  

Construction of Nomogram Model for StageⅢ-ⅣNon-Small Cell Lung Cancer Patients Based on Serological Indicators

作　　者：周义斌 张晓元 张菁菁 张嘉伟 闫洪超[1] 王婧[1] ZHOU Yibin;ZHANG Xiaoyuan;ZHANG Jingjing(Dongzhimen Hospital,Beijing University of Chinese Medicine,Beijing 100007,China)

机构地区：[1]北京中医药大学东直门医院,100007 [2]潍坊市中医院,261041

出　　处：《医学研究杂志》2024年第11期27-34,共8页Journal of Medical Research

基　　金：国家自然科学基金资助项目(面上项目)(82172760)。

摘　　要：目的 探讨血清学指标及临床特征对Ⅲ~Ⅳ期非小细胞肺癌(non-small cell lung cancer, NSCLC)患者总生存期的预测价值,并构建预测Ⅲ~Ⅳ期NSCLC患者预后的列线图模型。方法 采用回顾性分析方法,收集2012年1月~2022年12月于北京中医药大学东直门医院住院治疗的272例Ⅲ~Ⅳ期NSCLC患者的临床资料,按照6∶4的比例随机分为建模组(n=163)和验证组(n=109)。通过受试者工作特征(receiver operating characteristic, ROC)曲线确定连续变量最佳截断值,将其转换为二分类变量。对建模组相关临床资料进行单因素COX回归分析,初步筛选出差异有统计学意义(P<0.05)的相关变量。进一步利用赤池信息准则(akaike information criterion, AIC)对相关变量进行筛选,选择AIC值最小的模型用于构建列线图。结果 最终以中性粒细胞与单核细胞比值、D-二聚体、γ-谷氨酰转移酶、手术史4个变量用于构建Ⅲ~Ⅳ期NSCLC患者1、3、5年总生存期列线图。建模组C指数为0.789(95%CI:0.757~0.821),验证组C指数为0.692(95%CI:0.592~0.792)。各组预测1、3、5年生存率的ROC曲线下面积均>0.6,提示该模型具有较好的区分度。建模组与验证组决策曲线分析显示,列线图相较于TNM分期模型具有更高的净获益。根据X-tile软件对患者进行危险度分层,分层后Kaplan-Meier生存曲线分析显示,模型对高、低风险患者具有较好的区分度。结论 本研究构建的列线图对Ⅲ~Ⅳ期NSCLC患者预后具有较好的预测价值,该列线图可以作为TNM分期的补充,有助于临床医师个体化评估患者生存情况。Objective To explore the predictive value of serological indicators and clinical characteristics on overall survival(OS)in stageⅢ-Ⅳnon-small cell lung cancer(NSCLC)patients and to construct a nomogram model for predicting the prognosis of stageⅢ-ⅣNSCLC patients.Methods A retrospective analysis was conducted,and clinical data of 272stageⅢ-ⅣNSCLC patients admitted to Dongzhimen Hospital,Beijing University of Chinese Medicine from January 2012 to December 2022 were collected.The patients were randomly divided into training group(n=163)and validation group(n=109)at a ratio of 6:4.Receiver operating characteristic(ROC)curve analysis was used to determine the optimal cut-off values for continuous variables,which were then converted into binary variables.Univariate COX regression analysis was performed on the clinical data of the training group to preliminarily screen out relevant variables with statistical significance(P<0.05).Further,the akaike information criterion(AIC)was used to screen the relevant variables,and the model with the smallest AIC value was selected to construct the nomogram.Results Finally,four variables including neutrophil to monocyte ratio,D-dimer,gamma-glutamyl transferase,and surgical history were used to construct nomogram for predicting 1-year,3-year and 5-year OS in stageⅢ-ⅣNSCLC patients.The C-index was 0.789(95%CI:0.757-0.821)for the training group and 0.692(95%CI:0.592-0.792)for the validation group.The area under the ROC curve for predicting 1-year,3-year,and 5-year survival rates was all>0.6,indicating good discriminative ability of the model.Decision curves analysis for both groups showed that the nomogram had higher net benefit compared to the TNM staging model.X-tile software was used to stratify patients by risk,and Kaplan-Meier survival curves showed good discriminatory ability of the model for high-and low-risk patients.Conclusion The nomogram constructed in this study has good predictive value for the prognosis of stageⅢ-ⅣNSCLC patients and can serve as a supple

关 键 词：非小细胞肺癌 列线图 预后因素 血清学指标 

分 类 号：R734[医药卫生—肿瘤]