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A Study Design for Augmenting the Control Group in a Randomized Controlled Trial: A Quality Process for Interaction Among Stakeholders.

Yunling XuNelson LuLilly YueRam Tiwari
Published in: Therapeutic innovation & regulatory science (2020)
There is an increasing demand for utilization of external data, such as historical study data and patient registry data, to augment the control group in a randomized controlled trial. While such a study design could reduce the time and cost, how to maintain the study validity and integrity is one major statistical challenge that needs to be carefully addressed. We discuss a study design quality process to enhance the study validity and integrity when using this approach. The discussed quality process is tailored to the confirmatory study using a 2-stage design with an emphasis on the interaction process among stakeholders. In an example, the quality process covers a 2-step assessment of the similarity in patient characteristics between the current study and the external data source, and between the treatment and augmented control groups.
Keyphrases
  • electronic health record
  • big data
  • machine learning
  • quality improvement