LAUSR

Background The significance of uncommon EGFR mutations in newly diagnosed advanced non-small-cell lung cancer (NSCLC) patients is incompletely known. We aimed to analyze the demographic profile, outcome, and treatment attributes of these patients. Patients and methods We retrospectively surveyed 5,738 advanced NSCLC patients who underwent EGFR testing in our center from 2013 to 2017 by in-house primer probes on real time PCR platform. Descriptive data were accumulated from electronic medical records. Survival plot was calculated using Kaplan–Meier method and compared between groups using log-rank test. Results Out of 1,260 EGFR mutation-positive patients, 83 (6.58%) had uncommon mutations in isolation or in various combinations. Uncommon mutations were more frequent in men, never-smokers, and adenocarcinomas. Overall, exon 18 G719X, exon 20 insertion, exon 20 T790M, exon 20 S768I, and exon 21 (L858R/L861Q) were present in 9.6%, 19.3%, 12%, 3.6%, and 3.6% patients, respectively. Dual mutation positivity was found in 50.6% patients. On classifying patients as per tyrosine kinase inhibitor (TKI) sensitivity, it was found that majority of the patients had a combination TKI sensitive and insensitive mutations. The median duration of follow-up was 13 months. Five patients were lost to follow-up. Median progression-free survival on first line therapy was 6.7 months (95% CI: 4.8–8.5). Median overall survival (OS) of patients who received TKI during the course of their disease was 20.2 months (95% CI: 11.4–28.9). Median overall survival (mOS) of the entire cohort was 15.8 months (95% CI: 10.1–21.5). Among all uncommon mutations, patients with dual mutations did better, with an mOS time of 22.6 months (95% CI: 8.2–37.0, P=0.005). It was observed that TKI sensitive/TKI insensitive dual mutations had a superior OS of 28.2 months (95% CI: 15.2–41.2, P=0.039) as compared to TKI sensitive and TKI insensitive EGFR mutations. Conclusion Uncommon EGFR mutations constitute a heterogeneous group, hence, it is imperative to understand each subgroup more to define optimal treatment.