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Thursday, January 11
Thu, Jan 11, 11:00 AM - 12:45 PM
Crystal Ballroom B
Pragmatic Use of Large Health Data Sources

Treatment Effect on Progression Free Survival in Oncology Assessed Using Electronic Health Records: A Simulation Study (304205)

Amy Abernethy, Flatiron Health  
Ariel Bourla, Flatiron Health  
Geoff Calkins, Flatiron Health  
Joe Chang , Flatiron Health  
Sandra Griffith , Flatiron Health  
*Elizabeth Sweeney, Flatiron Health  
Paul You, Flatiron Health 

Keywords: electronic health records, progression free survival, simulation, survival analysis, oncology

In oncology, progression free survival (PFS) is defined as the time to detection of disease progression or death, and is commonly captured in clinical trials as an endpoint to evaluate treatment efficacy. In trial settings, progression is assessed at regular intervals. In contrast, progression from electronic health record (EHR) data is collected at variable intervals when patients see their oncologist. There is growing interest in using EHR data to measure treatment effects in real-world settings in order to improve the efficiency of conducting clinical studies and increase the number of questions that can be feasibly asked. Therefore, to better understand how sensitive EHR-derived real world progression variable is to treatment effects, we have designed a set of simulations of progression in both the clinical trial and rwP settings. We simulate two major sources of error (variable progression assessments and error from extracting data from the EHR), and measures the impact of these errors on our ability to detect a known treatment effect. We use these simulations to generate practical guidelines about how to use progression data from the EHR to test hypotheses in observation