Computed Tomography,Clinical Features And Tumor Markers Associated With Epidermal Growth Factor Receptor Mutation Status In Lung Adenocarcinoma

Objective:A retrospective study was conducted on the patients with lung adenocarcinoma detected by EGFR gene mutation,and the relationship between EGFR gene mutation and clinical features,CT imaging signs and tumor markers was analyzed.Methods:To collect lung adenocarcinoma patients who were genetically tested during the first affiliated Hospital of China Medical University from Month 2015 to October2017.These patients were not treated and had complete clinical,pathological,imaging and tumor markers.The main research contents include:(1)The type of EGFR gene mutation(2)Clinical features : age,sex,smoking history,drinking history,TNM staging(3)CT image datas:size,position,shape,density,degree of enhancement,cavitation/bubble-like lucency,air bronchogram,lobulation,speculation,pleural tags,calcification,necrosis,emphysema,pleural effusion,lymph node metastasis,pulmonary metastasis,pleural metastasis,distant transfer.(4)tumor markers:CEA?CA125?CA153?CA199.The statistical software adopts the SPSS22.0,the group analysis of the classification variables using the card square test,The group analysis of continuous variables adopts independent sample U test,and p<0.05 is statistically significant for difference.Multiple logistic regression analysis and ROC curves was performed.Results:EGFR mutation were found in 99(63.87%)of155patients.Mutation were found more frequently in a female patients(P=0.004).EGFR mutation rate is unrelated with age,smoking history,drinking history and TNM staging(P>0.05).The mutation rate in tumors containing no air bronchogram(p=0.003)and pulmonary metastasis(P=0.002)was higher than that in tumors excepting it,but which was unrelated with cavitation/bubble-like lucency,lobulation,speculation,pleural tags,calcification,necrosis,lymph node metastasis,pleural metastasis and distant transfer(P>0.05).The correlation between with high CEA expression and EGFR gene mutation is statistically significant(p=0.002),no correlations have been found between EGFR gene mutation and other markers,such as CA125,CA153 and CA199(P>0.05).Multiple logistic regression analysis showed that gender(female)(OR,3.042;95%CI,1.210–7.644),airbronchogram(OR,0.214;95%CI,0.075–0.614),pulmonary metastasis(OR,3.323,95% CI,1.422–7.765),and high CEA expression(OR,4.872;95% CI,1.837–12.920)wereimportant predictors of EGFR mutation.ROC curve analysis showed that use of clinical variables combined with CT features(area under the ROC curve = 0.767 and 0.726)was superior to use of clinical variables alone(area under the ROC curve = 0.695).Conclusion: In patients with lung adenocarcinoma,air bronchogram,pulmonary metastasis and high CEA expression had a moderate predictive value for EGFR mutation status.CT imaging features of lung adenocarcinomas in combination with clinical variables can be used to prognosticate EGFR mutation status better than use of clinical variables alone.