Abstract
Background: As the commonest EGFR-TKI being used in Hong Kong, gefitinib has shown to be efficacious and safe as first-line treatment for L858R mutation and exon 19 deletions with less gastrointestinal and cutaneous adverse events than erlotinib and afatinib. The evidence for therapeutic efficacy for uncommon and complex EGFR mutations, on the other hand, is lacking. It is important to explore whether or not gefitinib is helpful for uncommon and complex EGFR mutations.
Objectives: To assess the therapeutic efficacy of gefitinib, as measured by progression-free survival and overall survival, among advanced-stage lung cancer patients with common, uncommon, and complex EGFR mutations.
Methods: This retrospective cohort study included 241 Chinese patients with advanced non-smallcell carcinoma of the lung harboring EGFR mutations and received gefitinib 250 mg daily as firstline treatment. The progression-free survival (PFS) and overall survival (OS) for patients with different EGFR mutations, namely exon 19 deletions, L858R mutation in exon 21, uncommon EGFR mutations, and complex EGFR mutations, were analyzed.
Results: Among the 241 patients, 118 (49%) had exon 19 deletion, 104 (43%) had L858R mutation in exon 21, 6 (2.5%) had uncommon EGFR mutations, and 13 (5.4%) had complex EGFR mutations. The mean age was 69. 72% of the patients were female, and 81% were non-smokers. Patients with complex EGFR mutations, regardless of the presence of exon 19 deletion and L858R mutation as the component, have better PFS and OS than patients with single common EGFR mutations (Exon 19 deletion or L858R mutation). Patients with uncommon EGFR mutations have inferior PFS and OS than those with common EGFR mutations.
Conclusion: Gefitinib is a possible option for patients with complex EGFR mutations, while it may not be the preferred treatment option in patients with single uncommon EGFR mutations.
Keywords: Non-small cell carcinoma, gefitinib, EGFR tyrosine kinase inhibitor, EGFR mutations, uncommon EGFR mutations, complex EGFR mutations.
Graphical Abstract
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