High‐Concordance Detection Across Diverse Biospecimens EGFR Mutation in a Large‐Scale NSCLC Cohort Using Droplet Digital PCR and Next‐Generation Sequencing

Vollständiger Abstract

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ABSTRACT Accurate detection and quantification of EGFR mutations are essential for molecular stratification in non‐small cell lung cancer (NSCLC). While next‐generation sequencing (NGS) enables comprehensive genomic profiling, droplet digital PCR (ddPCR) offers high sensitivity for predefined mutations. Large‐scale evaluations of ddPCR performance across diverse clinical specimen types remain limited. This retrospective study analyzed 936 analytical mutation‐target records from 747 NSCLC patients with NGS‐detected EGFR mutations. The records represented native DNA or corresponding pre‐capture NGS‐library derivatives from fresh tumor tissue, formalin‐fixed paraffin‐embedded tissue, plasma‐derived cell‐free DNA, and pleural effusion supernatant. ddPCR results were compared with NGS for mutation detection and variant allele frequency quantification using correlation and Bland–Altman analyses. Across all 936 analytical records, ddPCR showed a high overall positive percent agreement (PPA) with NGS (98.82%; 925/936; exact 95% CI, 97.91%–99.41%). Mutation‐specific PPAs were 98.93% for L858R (370/374; exact 95% CI, 97.28%–99.71%), 99.48% for Ex19del (385/387; exact 95% CI, 98.15%–99.94%), and 97.14% for T790M (170/175; exact 95% CI, 93.46%–99.07%). VAFs measured by ddPCR and NGS were strongly correlated (Pearson's r = 0.975). Concordance varied by mutation type and sample matrix, with greater variability observed in high‐VAF samples and plasma cfDNA. Paired analyses demonstrated high consistency between native DNA and pre‐capture NGS libraries. ddPCR provides reliable detection and quantification of clinically relevant EGFR mutations across multiple specimen types and processing states. ddPCR represents a practical complement to NGS for EGFR mutation analysis in NSCLC.