Matching insurance claims data with EMR molecular status data in non-small cell lung cancer (NSCLC) patients: Understanding real-world molecular testing and prevalence rates at the site and investigator level.
e20568 Background: Many targeted therapy clinical trials require a somatic gene mutation/alteration for eligibility. We assessed the feasibility of leveraging Real-World Data (RWD) to enrol NSCLC patients into clinical trials. Methods: US insurance claims data were extracted to identify lung cancer patients. These data were matched with EMR data also containing NSCLC patients’ details regarding the occurrence and results of molecular testing for EGFR, ALK, ROS1, JAK2, HER2 and RET somatic alterations, achieving a level of granular detail beyond that available in each individual dataset. A one-year extraction period was applied, with no gender or age restrictions. Results: Results for the matched dataset are summarised in the table below - the overall patient record match was 89.6%. Conclusions: The observed prevalence correlated reasonably well with literature reported prevalence for the molecular biomarkers associated commercially available targeted therapies in NSCLC (EGFR, ALK, ROS1). The sample size for the remaining biomarkers was too small to draw conclusions, though the presence of data correlating to these is of interest, considering that there are no currently approved targeted therapies in NSCLC tailored to these predictive biomarkers. This approach could be expanded upon to recruit patients into targeted therapy clinical trials as the dataset is fully linkable to sites and investigators. With the emergence of broad genomic profiling, the availability of molecular data to support clinical trial enrolment is also expected to grow.[Table: see text]