Epidermal growth factor receptor tyrosine kinase inhibitors for de novo T790M mutation: A retrospective study of 44 patients

THORACIC CANCER(2022)

引用 5|浏览2
暂无评分
摘要
Background This study aimed to evaluate possible treatment strategies for patients with de novo T790M mutation-positive (T790M+) non-small-cell lung cancer (NSCLC). Methods Patients diagnosed with de novo T790M+ NSCLC and treated with epidermal growth factor receptor tyrosine kinase inhibitors (EGFR-TKIs) between 2011 and 2018 at a regional hospital in Taiwan were retrospectively reviewed. Their clinicopathological characteristics and subsequent treatment information were collected, and potential prognostic factors were identified using univariate and multivariate analyses. Results All tumors with T790M mutations coexisted with sensitizing mutations. Through the last follow-up in May 2021, afatinib and osimertinib demonstrated better progression-free survival (PFS, p < 0.01) and overall survival (OS, p < 0.01) than gefitinib and erlotinib. Additionally, patients with low T790M ratios had better PFS than those with high T790M ratios, implying that the proportion of T790M+ tumors determined the response to EGFR-TKIs. Multivariate analysis confirmed that both EGFR-TKI treatment (osimertinib hazard ratio [HR] 0.06, 95% confidence interval [CI] 0.01-0.30; afatinib HR 0.09, 95% CI 0.02-0.39) and a low T790M ratio (HR 0.29, 95% CI 0.12-0.69) were independently favorable prognostic factors for patients with de novo T790M+ NSCLC. Median PFS was 6.1 (95% CI 4.4-7.8) months. In addition, patients treated with first-generation (1G)/second-generation (2G) EGFR-TKIs followed by osimertinib (n = 8) demonstrated the best OS compared with patients treated with frontline osimertinib (n = 5) or 1G/2G EGFR-TKIs without osimertinib (n = 28, p < 0.01). Conclusion Sequential TKIs may represent an alternative option for de novo T790M mutation, particularly frontline afatinib and tumors with low T790M ratios.
更多
查看译文
关键词
afatinib, lung cancer, osimertinib, T790M mutation
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要