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, =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, =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.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6357894PMC
http://dx.doi.org/10.2147/LCTT.S181406DOI Listing

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