This article was originally published here
Clin Pharmacol Ther. 2021 Oct 16. doi: 10.1002/cpt.2443. Online ahead of print.
In prior work, Friends of Cancer Research convened multiple data partners to establish standardized definitions for oncology real-world endpoints derived from electronic health records (EHR) and claims data. Here, we assessed the performance of real-world overall survival (rwOS) from datasets sourced from EHRs by evaluating the ability of the endpoint to reflect expected differences from a previous randomized controlled trial across 5 data sources, after applying inclusion/exclusion criteria. The KEYNOTE-189 clinical trial protocol of platinum doublet chemotherapy (chemotherapy) versus PD-1 in combination with platinum doublet chemotherapy (PD-1 combination) in first-line non-squamous metastatic non-small cell lung cancer guided retrospective cohort selection. The Kaplan-Meier product limit estimator was used to calculate twelve-month rwOS with 95% confidence intervals (CI) in each data source. Cox proportional hazards models estimated hazard ratios (HR) and associated 95% CI, controlled for prognostic factors. Once the inclusion/exclusion criteria were applied, the five resulting datasets included 155 to 1501 patients in the chemotherapy cohort and 36 to 405 patients in the PD-1 combination cohort. Twelve-month rwOS ranged from 45% to 58% in the chemotherapy cohort and 44% to 68% in the PD-1 combination cohort. The adjusted HR for death ranged from 0.80 (95% CI: 0.69, 0.93) to 1.15 (95% CI: 0.71, 1.85), controlling for age, gender, performance status, and smoking status. This study yielded insights regarding data capture, including ability of RWD to precisely identify patient populations and the impact of criteria on endpoints. Sensitivity analyses could elucidate dataset-specific factors that drive results.