Approaches for Enhanced Extrapolation of Long-Term Survival Outcomes Using Electronic Health Records of Patients With Cancer

Abstract

Objectives

This study aimed to demonstrate enhanced survival extrapolation methods using electronic health record-derived real-world data (RWD).

Methods

The study population included patients diagnosed of ER+/HER2− metastatic breast cancer who started first-line treatment with anastrozole or letrozole between November 18, 2014, and November 18, 2015. Two patient cohorts were constructed: a clinical trial cohort from digitized MONARCH-3 clinical trial results and a RWD cohort from a deidentified electronic health record-derived database. RWD patients were weighted to trial baseline covariate distributions. Standard parametric approaches were applied to trial data and a “best-fit” model was selected. We demonstrate traditional and enhanced hybrid (pooling with weighted RWD at start, 75%, or end of trial) extrapolation approaches.

Results

Observed and estimated 5-year progression-free survival (PFS) rates in extrapolating the trial control arm (n = 165) were comparable across all methods. Compared with the observed 5-year mean PFS in the RWD cohort (n = 118) of 20.4 months (95% confidence interval [CI] 16.9-23.8), there was some variation among studied methods. Best-fit standard parametric model (log-normal) had 5-year mean PFS of 21.3 months (95% CI 18.2-24.9), and for the hybrid methods in order of estimate conservativeness was start of trial (20.8 months; 95% CI 18.5-23.2), 75% of trial (21.3 months; 95% CI 18.1-24.5), and end of trial (21.8 months; 95% CI 18.8-25.2).

Conclusions

Our study leverages RWD to enhance long-term survival extrapolation. Future use cases should include applying patient eligibility criteria, weighting on baseline characteristics, and choice of time window to add RWD to trial data.

Authors

Xiaoliang Wang Blythe J. Adamson Andrew Briggs Katherine Tan Danielle Bargo Shuhag Ghosh Shrujal Baxi Scott Ramsey

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