Effect of epidermal growth factor receptor gene mutation on the prognosis of pathological stage II–IIIA (8th edition TNM classification) primary lung cancer after curative surgery

Abstract

ObjectivesThis retrospective study aimed to elucidate the effect of epidermal growth factor receptor (EGFR) gene mutations on the prognosis of patients with pathological stage II–IIIA primary lung cancer after curative surgery. Materials and methodsWe enrolled 539 patients with p-stage II–IIIA (8th edition tumor–node–metastasis [TNM] classification) lung cancer who underwent curative resection at Kanagawa Cancer Center between January 2010 and December 2020 and whose tumors were tested for EGFR mutations. Relapse-free survival (RFS) and overall survival (OS) of patients with EGFR-mutant lung cancer (Mt, n = 126) including EGFR exon 21 L858R point mutation and EGFR exon 19 deletion mutation and EGFR mutation-wild lung cancer (Wt, n = 413) were analyzed using Kaplan–Meier curves and compared using a log-rank test. Cox regression analysis was performed to evaluate the effects of EGFR gene mutations on RFS and OS at each stage. ResultsThere were 56/256 patients with p-stage II EGFR-Mt/Wt and 70/157 patients with p-stage IIIA EGFR-Mt/Wt. The 5-year RFS rate of patients with EGFR-Mt/Wt was 46.6%/52.0% (p = 0.787) for p-stage II and 17.4%/29.7% (p = 0.929) for p-stage IIIA. The 5-year OS rate was 92.0%/65.7% (p = 0.001) for p-stage II and 56.0%/39.3% (p = 0.016) for p-stage IIIA. EGFR-Mt was not an independent prognostic factor for OS of patients with p-stage IIIA lung cancer (hazard ratio [HR], 0.95; 95% confidence interval [CI], 0.51–1.76; p = 0.872); however, EGFR-Mt was an independent favorable prognostic factor for OS of patients with p-stage II lung cancer (HR, 0.59; 95% CI, 0.36–0.96; p = 0.034). ConclusionThe OS of lung cancer patients with p-stage II or IIIA, classified according to the 8th edition TNM classification, was remarkably favorable. Incorporating EGFR mutations to the anatomical TNM classification may lead to a more accurate prognosis prediction.