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

Sandra D Griffith, Melisa Tucker, Bryan Bowser, Geoffrey Calkins, Che-Hsu Joe Chang, Ellie Guardino, Sean Khozin, Josh Kraut, Paul You, Deb Schrag, Rebecca A Miksad, Sandra D Griffith, Melisa Tucker, Bryan Bowser, Geoffrey Calkins, Che-Hsu Joe Chang, Ellie Guardino, Sean Khozin, Josh Kraut, Paul You, Deb Schrag, Rebecca A Miksad

Abstract

Introduction: 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 standard clinical trial metrics. The best approach for collecting similar endpoints from EHRs remains unknown. We evaluated the feasibility of a RECIST-based methodology to assess EHR-derived real-world progression (rwP) and explored non-RECIST-based approaches.

Methods: In this retrospective study, cohorts were randomly selected from Flatiron Health's database of de-identified patient-level EHR data in advanced non-small cell lung cancer. A RECIST-based approach tested for feasibility (N = 26). Three non-RECIST approaches were tested for feasibility, reliability, and validity (N = 200): (1) radiology-anchored, (2) clinician-anchored, and (3) combined. Qualitative and quantitative methods were used.

Results: A RECIST-based approach was not feasible: cancer progression could be ascertained for 23% (6/26 patients). Radiology- and clinician-anchored approaches identified at least one rwP event for 87% (173/200 patients). 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 months (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 (Spearman's rho 0.65-0.66). Abstractors preferred the clinician-anchored approach as it provided more comprehensive context.

Conclusions: RECIST cannot adequately assess cancer progression in EHR-derived data because of 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.

Funding: Flatiron Health Inc., which is an independent subsidiary of the Roche group.

Keywords: Carcinoma, non-small cell lung; Endpoints; Immunotherapy; PD-1; PD-L1; Real-world evidence.

Figures

Fig. 1
Fig. 1
Using the EHR to generate a cancer progression endpoint
Fig. 2
Fig. 2
Assessing applicability of RECIST for defining cancer progression in real-world EHR data in experiment 1. Twenty-six patient charts were randomly selected from the overall cohort of 7584 patients with at least 2 clinical visits and 2 lines of therapy (LoT). RECIST criteria were applied and the numbers of patients meeting the various criteria were recorded
Fig. 3
Fig. 3
rwPFS, rwTTP, and OS in experiment 2. Kaplan–Meier estimate curves for overall survival and a progression-free survival (PFS) or b time to progression (TTP), for all three non-RECIST abstraction approaches

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