The design and evaluation of hybrid controlled trials that leverage external data and randomization

Steffen Ventz (), Sean Khozin, Bill Louv, Jacob Sands, Patrick Y. Wen, Rifaquat Rahman, Leah Comment, Brian M. Alexander and Lorenzo Trippa
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Steffen Ventz: University of Minnesota
Sean Khozin: CancerLinQ
Bill Louv: Project Data Sphere
Jacob Sands: Dana-Farber Cancer Institute
Patrick Y. Wen: Dana-Farber Cancer Institute
Rifaquat Rahman: Dana-Farber Cancer Institute
Leah Comment: Foundation Medicine, Inc
Brian M. Alexander: Dana-Farber Cancer Institute
Lorenzo Trippa: Dana-Farber Cancer Institute

Nature Communications, 2022, vol. 13, issue 1, 1-11

Abstract: Abstract Patient-level data from completed clinical studies or electronic health records can be used in the design and analysis of clinical trials. However, these external data can bias the evaluation of the experimental treatment when the statistical design does not appropriately account for potential confounders. In this work, we introduce a hybrid clinical trial design that combines the use of external control datasets and randomization to experimental and control arms, with the aim of producing efficient inference on the experimental treatment effects. Our analysis of the hybrid trial design includes scenarios where the distributions of measured and unmeasured prognostic patient characteristics differ across studies. Using simulations and datasets from clinical studies in extensive-stage small cell lung cancer and glioblastoma, we illustrate the potential advantages of hybrid trial designs compared to externally controlled trials and randomized trial designs.

Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:nat:natcom:v:13:y:2022:i:1:d:10.1038_s41467-022-33192-1

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DOI: 10.1038/s41467-022-33192-1

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