| Objective: Lung cancer is one of the most common tumors in the world.Adenocarcinoma is a common pathological type of lung cancer.The purpose of this study is to analyze the relationship between EGFR mutation and clinical and imaging features of lung adenocarcinoma,so as to provide simple and convenient indicators for the prediction and treatment of EGFR gene mutation lung adenocarcinoma.Methods: From January 2017 to June 2019,a total of 456 patients with lung adenocarcinoma who had been treated in Shengjing Hospital for EGFR gene detection were enrolled.327 patients were excluded according to the standard,and 129 of them were finally selected,including 78 in EGFR mutation group and 51 in wild group.Their age,gender,smoking history,CEA,NSE and other clinical characteristics and lung CT manifestations were recorded,and the relationship between EGFR gene mutation and EGFR gene mutation was analyzed Department.Results:Total of 129 patients were included in this study,61.2% of them were EGFR mutation patients,60(46.5%)were male patients,the average age(64.5 years old;age range 48-91 years old),69(53.5%)were female patients,the average age(61.2 years old;age range 39-84 years old).There was a significant difference in age between male and female patients(P = 0.016),and there was a significant difference in EGFR mutation rate between female and male patients(P = 0.023).There was a difference in gene mutation between non-smokers and smokers(P = 0.011).There was no significant difference in tumor stage,CEA,NSE and EGFR gene mutation.Among the imaging features,ground glass nodule(P = 0.006),pleural effusion(P = 0.036),vascular bundle sign(P ≤ 0.001)were associated with EGFR gene mutation.However,there was no significant correlation between EGFR mutation and CT features such as tumor diameter,lobular sign,prick sign and pleural depression sign(P > 0.05).The results of logistic regression analysis indicated that age,smoking history,ground glass nodule,and vascular cluster sign had predictive value for EGFR mutation.Conclusion:The clinical and imaging features of lung adenocarcinoma patients have clinical application value in predicting EGFR gene mutation... |
