Background: Epidermal growth factor receptor (EGFR)-mutated advanced adenocarcinoma of the lung is among the most prevalent mutation types. The treatment paradigm for this condition is rapidly evolving. This study focuses on the clinical outcomes in resource-limited settings. The findings aim to guide treatment strategies for such populations.
Methods: A retrospective analysis was conducted on 51 patients aged over 18 years with EGFR-positive nonsquamous lung carcinoma treated at Aga Khan University Hospital between January 2017 and December 2021. Data were collected using nonprobability consecutive sampling and reviewed retrospectively from patient records. Statistical analyses were performed using Statistical Package for Social Science version 20.0. Continuous data were analysed using an independent sample T-test, while categorical data were assessed using the Cox regression test. Kaplan–Meier survival curves were generated to evaluate overall survival (OS) and progression-free survival (PFS), and the log-rank test was used to compare median PFS. A p-value of <0.05 was considered statistically significant for all analyses.
Results: The median age of the cohort was 60 years, with a gender distribution of 56% females and 44% males. A total of 98% of the patients presented with de novo stage IV lung adenocarcinoma. All patients had EGFR-mutated adenocarcinoma, and the majority (80.4%) were nonsmokers. Mutational analysis revealed the following: Exon 19 deletion in 56.9% of patients, Exon 20 insertion in 9.8%, Exon 21 mutations in 19.6%, compound mutations in 7.8%, other mutations in 2.0% and the de novo T790M mutation in 3.9%. Among the cohort, 82% received at least one line of EGFR tyrosine kinase inhibitors (TKIs). The median PFS with TKIs was 15 months, and the median OS with first-line TKIs was 38 months.
Conclusion: This study demonstrates that EGFR-targeted therapy, when used in a first-line setting, significantly improves OS and PFS in this population. Further research is warranted to optimise treatment strategies, particularly in resource-limited settings.
