Medicine and Health

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

S. Ventz, S. Khozin, et al.

This innovative research, conducted by a talented team including Steffen Ventz, Sean Khozin, and others, unveils a hybrid clinical trial design that melds external control datasets with randomization, optimizing treatment effect inference and addressing confounders in patient characteristics. Through simulations involving ES-SCLC and GBM studies, the study showcases the superiority of this approach over traditional trial methodologies.

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Abstract

This work introduces a hybrid clinical trial design combining external control datasets and randomization to improve the efficiency of treatment effect inference. The design accounts for potential confounders arising from differences in patient characteristics across studies. Simulations and datasets from extensive-stage small cell lung cancer (ES-SCLC) and glioblastoma (GBM) studies illustrate the advantages of this hybrid approach compared to externally controlled trials (ECTs) and randomized controlled trials (RCTs).

Publisher

Nature Communications

Published On

Oct 02, 2022

Authors

Steffen Ventz, Sean Khozin, Bill Louv, Jacob Sands, Patrick Y. Wen, Rifaquat Rahman, Leah Comment, Brian M. Alexander, Lorenzo Trippa

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