Using Electronic Health Records to Derive Control Arms for Early Phase Single‐Arm Lung Cancer Trials: Proof‐of‐Concept in Randomized Controlled Trials. Issue 2 (11th October 2019)

• Record Type: Journal Article
• Authors: Carrigan, Gillis; Whipple, Samuel; Capra, William B.; Taylor, Michael D.; Brown, Jeffrey S.; Lu, Michael; Arnieri, Brandon; Copping, Ryan; Rothman, Kenneth J.
• Is Part Of: Clinical pharmacology & therapeutics. Volume 107:Issue 2(2020)
• Page Start: 369
• Page End: 377
• Publication Date: 2019-10-11
• Subjects: Pharmacology -- Periodicals; Therapeutics -- Periodicals; 615.5
• DOI: 10.1002/cpt.1586
• Languages: English
• ISSNs: 0009-9236

Abstract

Abstract : Oncology drug development increasingly relies on single‐arm clinical trials. External controls (ECs) derived from electronic health record (EHR) databases may provide additional context. Patients from a US‐based oncology EHR database were aligned with patients from randomized controlled trials (RCTs) and trial‐specific eligibility criteria were applied to the EHR dataset. Overall survival (OS) in the EC‐derived control arm was compared with OS in the RCT experimental arm. The primary outcome was OS, defined as time from randomization or treatment initiation (EHR) to death. Cox regression models were used to obtain effect estimates using EHR data. EC‐derived hazard ratio estimates aligned closely with those from the corresponding RCT with one exception. Comparing log HRs among all RCT and EC results gave a Pearson correlation coefficient of 0.86. Properly selected control arms from contemporaneous EHR data could be used to put single‐arm trials of OS in advanced non‐small cell lung cancer into context.