基于血清肿瘤标志物构建非小细胞肺癌患者预后的预测模型  

Construction of prediction model of non-small cell lung cancer patients based on serum tumor markers

作　　者：郭佳佳[1] 郜永月 毛哲哲 GUO Jiajia;GAO Yongyue;MAO Zhezhe(Handan Central Hospital,Hebei Handan 056002,China.)

机构地区：[1]邯郸市中心医院,河北邯郸056002

出　　处：《现代肿瘤医学》2024年第14期2554-2560,共7页Journal of Modern Oncology

基　　金：河北省医学科学研究课题计划项目(编号:20220552)。

摘　　要：目的:分析血清肿瘤标志物对非小细胞肺癌(NSCLC)患者术后预后的影响,基于此构建列线图(Nomogram)预测模型。方法:选取2017年1月至2020年2月我院收治的143例NSCLC患者,根据其术后三年生存状态分为死亡组(n=51)和生存组(n=92)。比较两组患者一般临床资料,多因素COX回归风险模型分析影响NSCLC患者预后的独立风险因素,R软件“rms”包构建Nomogram预测模型。结果:两组患者年龄、肿瘤最大直径、肿瘤分期、分化程度、脉管癌栓、CEA、NSE、AFP、CA125、CA199的比较差异均有统计学意义(P<0.05)。分化程度(低分化)、CEA(>8.45 ng/mL)、NSE(>18.17 ng/mL)、CA199(>40.73 U/mL)是影响NSCLC患者预后的独立危险因素(P<0.05)。Nomogram预测模型的C-index为0.847(0.807~0.886),校准曲线趋近于理想曲线;决策曲线结果显示,风险阈值>0.13时此预测模型可以提供额外的临床净收益。结论:低分化、高CEA、高NSE、高CA199是NSCLC患者死亡的独立危险因素,基于此构建的Nomogram预测模型为NSCLC患者预后的防治提供重要的策略指导。Objective:To analyze the effects of serum tumor markers on postoperative prognosis of patients with non-small cell lung cancer(NSCLC),and build a Nomogram prediction model based on this analysis.Methods:A total of 143 patients with NSCLC admitted to our hospital from January 2017 to February 2020 were selected and divided into death group(n=51)and survival group(n=92)according to their survival status three years after surgery.General clinical data of the two groups were compared,and multivariate COX regression risk model was used to analyze the independent risk factors affecting the prognosis of patients with NSCLC.A Nomogram prediction model was constructed by R software"rms"package.Results:There were statistically significant differences in age,maximum tumor diameter,tumor stage,degree of differentiation,vascular cancer thrombus,CEA,NSE,AFP,CA125 and CA199 between 2 groups(P<0.05).Differentiation degree(low differentiation),CEA(>8.45 ng/mL),NSE(>18.17 ng/mL)and CA199(>40.73 U/mL)were independent risk factors for prognosis of NSCLC patients(P<0.05).The C-index of Nomogram prediction model was 0.847(0.807~0.886),and the calibration curve was close to the ideal curve.The decision curve results showed that the prediction model provided additional clinical net benefit when the risk threshold was>0.13.Conclusion:Low differentiation,high CEA,high NSE,and high CA199 are independent risk factors for death in patients with NSCLC.This Nomogram model will provide important strategic guidance for prevention and treatment of prognosis in patients with NSCLC.

关 键 词：非小细胞肺癌 肿瘤标志物 预后 预测模型 

分 类 号：R734.2[医药卫生—肿瘤]