Analysis of clinical, pathological and CT features of epidermal growth factor receptor exon 19 and 21 mutations in lung adenocarcinoma
10.3760/cma.j.cn112149-20220126-00078
- VernacularTitle:肺腺癌表皮生长因子受体基因外显子19及21突变的临床、病理及CT特征分析
- Author:
Jiwen HUO
1
;
Qi LI
;
Tianyou LUO
;
Fajin LYU
Author Information
1. 重庆医科大学附属第一医院放射科，重庆 400016
- Keywords:
Adenocarcinoma;
Lung;
Tomography, X-ray computed;
Epidermal growth factor receptor
- From:
Chinese Journal of Radiology
2023;57(2):142-149
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To investigate the clinical, pathological and CT characteristics of lung adenocarcinoma patients with epidermal growth factor receptor (EGFR) 19 and 21 exon mutations.Methods:Clinical, pathological and imaging data of 683 patients with lung adenocarcinoma in the First Affiliated Hospital of Chongqing Medical University from December 2012 to December 2020 were retrospectively analyzed. According to the gene mutation status, patients were divided into EGFR common loci mutation group (exons 19 or 21) with 382 cases (mutation group), including 19 exon mutation in 165 cases (exon 19 mutation subgroup) and 21 exon mutation in 217 cases (exon 21 mutation subgroup), and EGFR negative mutation group with 301 cases (negative mutation group). Independent sample t-test and χ 2 test were used to compare those features between mutation group and negative mutation group, exon 19 mutation subgroup and exon 21 mutation subgroup. The indicators with statistically significant differences in univariate analysis were included in binary logistic regression analysis to screen out independent predictors and establish the model. Receiver operating characteristic curve and area under curve (AUC) were used to evaluate the predictive performance of the model or index. Results:There were significant differences between mutation group and negative mutation group in gender distribution, smoking history, the proportion of solid-dominated growth pattern, peripheral distribution, tumor maximum diameter (3 cm as the cut-off point) distribution, spiculation, ground-glass opacity (GGO), air bronchogram, vascular convergence sign, pleural retraction, the number of lung metastases (10 as the cut-off point), pleural effusion, necrosis, and lymph node metastasis in lung adenocarcinoma patients ( P<0.05). The logistic regression showed that female (OR=5.230,95%CI 3.534-7.740, P<0.001), non-smoking history (OR=2.970, 95%CI 1.986-4.443, P<0.001), GGO (OR=3.092, 95%CI 1.746-5.477, P<0.001), absence of necrosis (OR=1.754, 95%CI 1.047-2.939, P=0.033), vascular convergence sign (OR=3.129, 95%CI 1.971-4.969, P<0.001), pleural retraction (OR=2.434, 95%CI 1.680-3.526, P<0.001), and the number of lung metastases≥10 (OR=2.242, 95%CI 1.284-3.915, P=0.005) were independent predictors of EGFR exon 19 and 21 mutations, and the AUC of the logistic model based on these predictors in predicting EGFR exon 21 and 19 mutations in lung adenocarcinoma was 0.804. There were significant differences between EGFR exon 19 mutation subgroup and EGFR 21 mutation subgroup in gender distribution, the proportion of acinar-dominated growth pattern, peripheral distribution, vascular convergence sign, pleural retraction ( P<0.05). The logistic regression showed that vascular convergence sign (OR=1.833, 95%CI 1.187-2.831, P=0.006) was independent predictor of EGFR exon 21, the AUC of vascular convergence sign for distinguishing EGFR exon 19 and EGFR 21 mutation was 0.604. Conclusions:There are some differences in the clinical, pathological, and CT features of patients between EGFR common loci mutation and EGFR negative mutations, EGFR exon 19 and exon 21 mutations in lung adenocarcinoma. Familiarity with these differences is helpful for the individualized treatment of patients with unknown gene mutation status of lung adenocarcinoma.
