Generating real-world tumor burden endpoints from electronic health record data: Comparison of RECIST, radiology-anchored, and clinician-anchored approaches for abstracting real-world progression in non-small cell lung cancer

Abstract

Real-world evidence derived from electronic health records (EHRs) is increasingly recognized as a supplement to evidence generated from traditional clinical trials. In oncology, tumor-based Response Evaluation Criteria in Solid Tumors (RECIST) endpoints are collected in clinical trials. The best approach for collecting similar endpoints from EHRs remains unknown. We evaluated the feasibility of a traditional RECIST-based methodology to assess EHR-derived real-world progression (rwP) and explored non-RECIST-based approaches. In this retrospective study, cohorts were randomly selected from Flatiron Healths database of patient-level EHR data in advanced non-small cell lung cancer. A RECIST-based approach was tested for feasibility (N=26). Three non-RECIST abstraction approaches were tested for feasibility, reliability, and validity (N=200): (1) radiology-anchored, (2) clinician-anchored, and (3) combined. RECIST-based cancer progression could be ascertained from the EHRs of 23% of patients (6/26). In 87% of patients (173/200), at least one rwP event was identified using both the radiology- and clinician-anchored approaches. rwP dates matched 90% of the time. In 72% of patients (124/173), the first clinician-anchored rwP event was accompanied by a downstream event (e.g., treatment change); the association was slightly lower for the radiology-anchored approach (67%; 121/180). Median overall survival (OS) was 17 months (95% confidence interval [CI]: 14, 19). Median real-world progression-free survival (rwPFS) was 5.5 (95% CI: 4.6, 6.3) and 4.9 months (95% CI: 4.2, 5.6) for clinician-anchored and radiology-anchored approaches, respectively. Correlations between rwPFS and OS were similar across approaches (Spearmans rho: 0.65-0.66). Abstractors preferred the clinician-anchored approach as it provided more comprehensive context. RECIST cannot adequately assess cancer progression in EHR-derived data due to missing data and lack of clarity in radiology reports. We found a clinician-anchored approach supported by radiology report data to be the optimal, and most practical, method for characterizing tumor-based endpoints from EHR-sourced data.