Journal article
An Overview of Statistical and Operational Considerations Related to the Shared Control in Platform Trials
Journal of statistical theory and practice, Vol.19(4), 86
12/2025
DOI: 10.1007/s42519-025-00500-z
Abstract
Traditional, two arm randomized controlled trials are the gold standard for evaluating the efficacy of experimental interventions, but the need for flexible and efficient trial designs has increased. Trial designs using a master protocol, such as the platform trial, have been proposed as an option. Trials governed by a master protocol utilize an overarching study infrastructure to answer multiple research questions. Platform trials test multiple interventions against a common control arm and allow arms to enter and exit the study, increasing efficiency in evaluating the efficacy of experimental interventions. This increased efficiency, however, comes with unique considerations from both statistical and operational perspectives in the design, conduct, and analysis of platform trials. In this manuscript we discuss some key considerations for platform trials in general and specific challenges related to the shared control arm. Some of these challenges are related to fundamental trial features, including randomization and blinding. In a platform trial, participants are often randomized in a two-stage fashion to reduce operational complexities and more similarly mirror the process of randomization within a traditional two-arm randomized controlled trial. This approach to randomization, along with the chosen method for blinding within the trial, can have important implications when considering the ability to pool together control participants into a shared control arm for analyses. Overall, the platform trial requires unique considerations for its implementation, and users should be prepared to address these in order to realize the potential benefits and efficiencies of this trial design.
Details
- Title: Subtitle
- An Overview of Statistical and Operational Considerations Related to the Shared Control in Platform Trials
- Creators
- Megan E. McCabe - University of Alabama at BirminghamKert Viele - University of KentuckyChristopher S. Coffey - University of IowaEmine O. Bayman - Department of Biostatistics, University of Iowa, Department of Anesthesia, University of Iowa
- Resource Type
- Journal article
- Publication Details
- Journal of statistical theory and practice, Vol.19(4), 86
- DOI
- 10.1007/s42519-025-00500-z
- ISSN
- 1559-8608
- eISSN
- 1559-8616
- Publisher
- Springer International Publishing
- Language
- English
- Date published
- 12/2025
- Academic Unit
- Biostatistics; Anesthesia
- Record Identifier
- 9984963622202771
Metrics
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