基于18F-FDG PET-CT代谢参数的风险模型对非小细胞肺癌EGFR基因突变的预测价值及效能评价  

The predictive value and efficacy of the risk model based on the metabolic parameters of 18F-FDG PET-CT for EGFR gene mutations in non-small cell lung cancer

作　　者：姜阳 马晓伟 董楚宁 肖哲 李娴 王云华[1] Jiang Yang;Ma Xiaowei;Dong Chuning;Xiao Zhe;Li Xian;Wang Yunhua(PET Image Center,the Second Xiangya Hospital,Central South University,Changsha 410011,China)

机构地区：[1]中南大学湘雅二医院PET影像中心,长沙410011

出　　处：《中华放射学杂志》2020年第7期688-693,共6页Chinese Journal of Radiology

基　　金：中南大学临床大数据项目基金(20140132)。

摘　　要：目的探讨基于18F-脱氧葡萄糖(FDG)PET-CT代谢参数风险模型在预测非小细胞肺癌(NSCLC)表皮生长因子受体(EGFR)基因突变中的价值并评价其效能。方法回顾性分析2017年1月至2018年6月中南大学湘雅二医院有EGFR检测结果且治疗前接受本院18F-FDG PET-CT显像的105例NSCLC患者,根据EGFR是否突变将其分为EGFR突变组(n=40)和EGFR野生组(n=65)。采用独立样本t检验和Mann-Whitney U检验及χ^2检验比较两组患者间多种因素差异,使用多因素logistic回归筛选独立影响因子,构建风险预测模型和列线图。以受试者操作特征(ROC)曲线评价模型诊断效能,通过Hosmer-Lemeshow(H-L)检验评价模型的校准度。结果EGFR野生组和EGFR突变组NSCLC患者中性别、吸烟史、血清癌胚抗原(CEA)水平、肿瘤长径、病理类型、甲状腺转录因子-1(TTF-1)表达、天冬氨酸蛋白酶A(NapsinA)表达等差异有统计学意义(P<0.05)。EGFR突变组患者的肿瘤代谢体积(MTV)与病灶糖酵解总量(TLG)分别为4.4(4.5,37.1)cm3、46.6(21.2,118.2),EGFR野生组患者的MTV与TLG分别为7.4(3.2,13.5)cm3、95.4(26.4,345.1),EGFR突变组患者的MTV与TLG均显著低于野生组,两组差异具有统计学意义(Z=-2.452,P=0.014;Z=-2.379,P=0.017)。ROC曲线分析显示最大标准摄取值(SUVmax)、MTV和TLG预测EGFR基因突变的曲线下面积(AUC)分别为0.597、0.643和0.639。多因素logistic回归分析表明性别、肿瘤长径、SUVmax、MTV是预测EGFR突变的独立影响因素,其比值比[OR(95%可信区间)]分别为3.811(1.508~9.629)、1.679(0.899~3.136)、0.928(0.848~1.015)和0.924(0.865~0.986)。建立风险预测模型和列线图,经ROC曲线评价模型的灵敏度为80.0%,特异度为66.2%,阳性预测值为68.8%,阴性预测值为75.3%,AUC(95%可信区间)为0.775(0.687~0.864)。经H-L检验显示该模型具有较好的准确性(χ^2=3.872,P=0.869)。结论基于18F-FDG PET-CT代谢参数风险模型在预测NSCLC患者EGFR基因突变中有较大的应用Objective To explore the value and efficacy of the risk model based on the metabolic parameters of 18F-FDG PET-CT in predicting epidermal growth factor receptor(EGFR)gene mutations in non-small cell lung cancer(NSCLC).Methods This retrospectives study reviewed 105 NSCLC patients who were tested for EGFR gene expression and underwent 18F-FDG PET-CT exam prior to treatment from Jan 2017 to June 2018 in our hospital.The patients were divided into EGFR mutations group(n=40)and EGFR wild type group(n=65).The differences between the different groups were analyzed in several clinical characteristics and three metabolic parameters based on 18F-FDG PET-CT,including the maximal standard uptake value(SUVmax),metabolic tumor volume(MTV),total lesion glycolysis(TLG)of the primary tumor.Multivariate logistic regression analysis was performed to identify predictors of EGFR mutations,and the risk prediction model and nomogram graph were constructed.Diagnostic efficiency of the model was done by the receiver operating characteristics(ROC)curve analysis,and the Calibration plot was performed by Hosmer-Lemeshow(H-L)test to evaluate the calibration scale of the model.Results There were statistically significant differences in gender,smoking status,serum CEA level,length of tumor,pathological types,TTF-1 and NapsinA expression between the EGFR mutant groups and EGFR wild-type groups(all P<0.05).The MTV and TLG of EGFR mutation group were 4.4(4.5,37.1)cm3 and 46.6(21.2,118.2),respectively.The MTV and TLG of EGFR wild type group were 7.4(3.2,13.5)cm3 and 95.4(26.4,345.1),respectively.The MTV and TLG of EGFR mutation group were significantly lower than those of EGFR wild type group(Z=-2.452,P=0.014;Z=-2.379,P=0.017).ROC curve analysis showed area under the curve(AUC)predicted by SUVmax,MTV and TLG for EGFR mutations was 0.597,0.643 and 0.639,respectively.Multivariate analysis demonstrated that gender,length of tumor,SUVmax and MTV were independent predictors of EGFR mutations,with the odds ratio(OR)values(95%CI)as 3.811(1.508-9.629),1.6

关 键 词：受体 表皮生长因子 癌 非小细胞肺 正电子发射断层显像术 

分 类 号：R734.2[医药卫生—肿瘤]