Summary
Defining frontline therapy using electronic health record (EHR) derived data is not straightforward considering treatment data from various networks may not always be readily available in the structured elements of the patient record. Data completeness requirements are often used in analyses of RWD to identify patients who are hypothesized to have missing treatment data as a way to mitigate against the potential for misclassification of frontline treatment. Specific to Flatiron data, the 90-day gap rule has been used to exclude patients who have 90 days or more between their clinical eligibility date (e.g., advanced cancer diagnosis) and the start of structured EHR activity, which may be indicative of missing treatment data.
This study evaluated the 90-day-gap rule’s ability to flag patients with treatment misclassification due to missing frontline treatment information. It was found that removing the 90-day-gap rule as an exclusion criterion can increase the number of patients available for analysis in a data set which can be crucial for analyses of rare disease subtypes or patient subgroups. While doing so may increase the prevalence of patients with line of therapy sequence misclassification, the prevalence is low and unlikely to introduce substantial misclassification bias. In light of these findings, the 90-day-gap rule is no longer recommended as an analytic tool for identifying patients with misclassified frontline treatment. Additionally, modifying the gap rule using different gap durations (e.g., 30 or 180 days) did not improve the rule.
Why this matters
The research provides a clear path forward to increase patients available for study in real-world data sets while providing evidence on the low prevalence of misclassification of frontline treatment data in Flatiron data. This research continues to build on our understanding of EHR-derived real-world data, contributing to improved RWD options to be used in future research.