Overview
Despite the growing use of electronic health record (EHR) derived real-world data in oncology research, studies estimating medication persistence using EHR data alone remain limited. This study compared two common approaches for estimating treatment persistence—time-to-event (TTE) and non-TTE—among patients with epidermal growth factor receptor (EGFR)-positive advanced non–small cell lung cancer (advNSCLC) receiving EGFR tyrosine kinase inhibitors (TKIs). Using the Flatiron Health EHR-derived US database, researchers analyzed persistence rates for six EGFR TKIs, including erlotinib, gefitinib, dacomitinib, afatinib, osimertinib, and lazertinib.
The study found that the non-TTE approach consistently estimated higher persistence rates than the TTE approach at all time points. The TTE approach measures persistence as the time from EGFR TKI initiation to the first qualifying discontinuation event, defined as initiation of subsequent treatment, death, or a structured activity record followed by a treatment-free period of more than 60 days, providing a cumulative estimate of persistence. The non-TTE approach, on the other hand, measures persistence by the proportion of patients still remaining on EGFR TKIs at different time points, offering a point-in-time snapshot.
Why this matters
Accurately measuring medication persistence is essential for assessing real-world treatment effectiveness and tolerability. This study highlights key differences between TTE and non-TTE approaches, demonstrating how methodological choices influence persistence estimates. By leveraging EHR data, researchers can generate more precise insights into treatment adherence, informing clinical decision-making and drug development. Future work may focus on incorporating competing risks and developing standardized guidance for estimating persistence using EHR data alone, to further enhance evidence generation in oncology research.