The effectiveness of afatinib in patients with lung adenocarcinoma harboring complex epidermal growth factor receptor mutation

BACKGROUND AND AIMS: Epidermal growth factor receptor tyrosine kinase inhibitors (EGFR TKIs) are effective against classical EGFR mutations in lung cancer. However, their effectiveness and the prognosis of lung cancer patients with complex EGFR mutations are not well delineated. Therefore, we aimed to investigate the treatment effectiveness of different EGFR TKIs in patients with complex EGFR mutations. PATIENTS AND METHODS: From 2005 to 2020, we collected lung adenocarcinoma tissue samples for EGFR mutation analysis using direct Sanger sequencing. Patients with EGFR mutations treated with EGFR TKIs as first-line treatment were enrolled. Clinical characteristics, EGFR mutation status, treatment response, progression-free survival (PFS), and overall survival (OS) were analyzed. RESULTS: Among 2675 patients with EGFR mutations, 239 (8.9%) had complex EGFR mutations, of whom 125 received EGFR TKI treatment as first-line treatment. Multivariate analysis revealed that afatinib was a more favorable factor for PFS than gefitinib [hazard ratio (HR), 2.01; 95% confidence interval (CI), 1.11–3.62] and erlotinib (HR, 2.61; 95% CI, 1.31–5.22), especially in patients with uncommon mutation patterns. Afatinib treatment as first-line treatment was also associated with longer OS compared with erlotinib (HR, 2.48; 95% CI, 1.20–5.12). Classical mutation pattern was associated with longer PFS (p = 0.001) and OS (p = 0.020). Secondary T790M was detected in 22 of 52 (42.3%) patients who had re-biopsied tissue samples after acquiring resistance to EGFR TKIs. There was no significant difference in secondary T790M formation after acquired resistance to the three EGFR TKIs (p = 0.261). Furthermore, three (5.8%) patients had small-cell lung cancer transformation. CONCLUSION: Afatinib is an effective first-line treatment for patients with lung adenocarcinoma harboring complex EGFR mutations, especially those with uncommon mutation patterns.