Variant allele frequency as a predictor of treatment response to osimertinib in EGFR-mutated NSCLC

Background: Osimertinib has been approved as a treatment option for epidermal growth factor receptor (EGFR) mutated non-small cell lung cancer (NSCLC). However, despite the identification of common mutations, there are still no additional pathological factors that can be used to predict treatment response and improvement in survival. Methods: This retrospective study utilized data from a multi-center registry of NSCLC patients with EGFR mutations who were treated with first-line osimertinib therapy between March 2017 and December 2024. The variant allele frequency (VAF) was evaluated as a potential predictive factor for overall survival (OS). Results: For the cohort of 147 patients who met eligibility requirements, the mean OS was 25.5 months (95% CI 20.28-30.75) and progression-free survival (PFS) was 21.4 months (95% CI 17.38-25.37). The mean OS was 19.7 months (95% CI 14.21-25.10) for VAF <30% and 31.4 months (95% CI 23.15-39.56) for VAF ≥30%. The mean PFS was 18.2 months (95% CI 12.94-23.46) for VAF <30% and 25.0 months (95% CI 19.14-30.94) for VAF ≥30%. In the subgroup of EGFR ex 19del the mean OS was 21.1 months (95% CI 11.04-31.25) for VAF <30% and 36.6 months (95% CI 25.61-47.50) for VAF ≥30% and for the subgroup with EGFR ex21 L858R the mean OS was 18.7 months (95% CI 12.36-25.00) for VAF <30% and 25.5 months (95% CI 13.78-37.22) for VAF ≥30%. Conclusion: Our study demonstrated that the VAF is a significant factor in predicting OS and PFS in EGFR mutant patients treated with osimertinib. Patients with a VAF ≥30% showed significantly improved OS and PFS compared to those with a VAF <30%. Specifically, the mean OS was longer for patients with higher VAF in both the overall cohort and in subgroups with EGFR exon 19 deletions and exon 21 L858R mutations. These findings suggest that VAF could serve as a valuable predictive biomarker for treatment outcomes in EGFR-mutated NSCLC patients, highlighting its potential role in personalizing treatment strategies.