Afatinib in Untreated Stage IIIB/IV Lung Adenocarcinoma with Major Uncommon Epidermal Growth Factor Receptor (EGFR) Mutations (G719X/L861Q/S768I): A Multicenter Observational Study in Taiwan

Background Real-world clinical experience with afatinib as a treatment for advanced lung adenocarcinoma harboring uncommon epidermal growth factor receptor (EGFR) mutations (G719X, L861Q and S768I) has rarely been reported. Objective We aimed to perform a retrospective multicenter study to analyze afatinib therapy in untreated advanced lung adenocarcinoma harboring uncommon EGFR mutations. Patients and Methods Between May 2014 and June 2021, the data of 90 stage IIIB/IV lung adenocarcinoma patients with uncommon EGFR mutations (G719X/L861Q/S768I) treated with first-line afatinib from the cancer center database of Linkou, Tucheng, and Kaohsiung Chang Gung Memorial Hospitals were retrospectively retrieved and analyzed. Results Afatinib had an objective response rate (ORR) of 63.3% and a disease control rate (DCR) of 86.7%. The median progression-free survival (PFS) with first-line afatinib therapy was 17.3 months (95% confidence interval (CI), 12.07–22.53), and the median overall survival (OS) was 28.5 months (95% CI, 20.22–36.77) in all study patients. In the multivariate analysis, poor performance (Eastern Cooperative Oncology Group performance status (ECOG PS) ≥ 2) and brain and liver metastases were independent predictors of unfavorable PFS. The G719X mutation (alone+compound) was an independent predictor of favorable PFS (hazard ratio (HR) = 0.578; 95% CI, 0.355−0.941; P = 0.027). Most afatinib-related adverse events (AEs) were limited to grades 1 and 2 and were manageable. Conclusions First-line afatinib therapy is effective and safe for advanced lung adenocarcinoma harboring uncommon EGFR mutations. The G719X mutation was an independent factor associated with a favorable outcome. Poor performance (ECOG PS ≥ 2), brain metastasis, and liver metastasis were predictive factors of shorter PFS with first-line afatinib therapy. Graphical Abstract