LAUSR

OBJECTIVES Afatinib, a second-generation epidermal growth factor receptor (EGFR) tyrosine kinase inhibitor (TKI), is used for EGFR-mutant non-small cell lung cancer (NSCLC). However, there are few reports about its resistance mechanisms. The aims of this study are to evaluate resistance mechanisms of afatinib compared with other TKIs and analyze the performance of repeat biopsy which is critical for subsequent treatment. MATERIALS AND METHODS We screened EGFR-mutant NSCLC patients who started first-line afatinib, gefitinib, or erlotinib from 2014 to 2016, and included patients who acquired resistance. Among those patients, T790 M mutation rates and histologic transformation were compared as an acquired resistance mechanism. RESULTS A total of 524 patients started EGFR-TKIs, and 347 experienced disease progression until April 2018. After excluding nine patients with de novo T790 M mutations or who were treated with two TKIs before repeat biopsy, 338 patients were included. Among these patients, 263 (78%) were successfully biopsied and evaluated for EGFR mutations and histologic transformation. T790 M mutation was documented in 35 (41%) of 86 evaluable patients in afatinib group, which is significantly lower than in gefitinib (55%, 73/133) and erlotinib groups (57%, 25/44) (p =  0.026). In multivariate analysis considering both baseline EGFR mutation types (deletion 19 or L858R) and sex, the odds ratio for T790M in afatinib group was 0.45 (95% confidence interval: 0.254-0.795, p =  0.006), compared with gefitinib or erlotinib groups. Five histologic transformations (two small cell, three squamous cell) were detected in afatinib group, while one small cell transformation was detected in gefitinib group, and no transformations were detected in erlotinib group. CONCLUSIONS In our clinical practice, repeat biopsy was possible in nearly four of five patients. Although T790 M mutation appears to be the main resistance mechanism for afatinib, it affects a lower proportion of patients than observed with first-generation TKIs.