ArticleTrials2024
Design considerations for Factorial Adaptive Multi-Arm Multi-Stage (FAST) clinical trials.
Article in Trials, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
3 citing papers in PubMed.
- Developing Interim Outcome Measures for Multi-Arm Multistage Clinical Trials in Multiple Sclerosis.Neurology · 2026Article
- CRISPR and Artificial Intelligence in Neuroregeneration: Closed-Loop Strategies for Precision Medicine, Spinal Cord Repair, and Adaptive Neuro-Oncology.International journal of molecular sciences · 2025Review
- Properties of adaptive, cluster-randomised controlled trials with few clusters: a simulation study.Implementation science : IS · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
Abstract
backgroundMulti-Arm, Multi-Stage (MAMS) clinical trial designs allow for multiple therapies to be compared across a spectrum of clinical trial phases. MAMS designs fall under several overarching design groups, including adaptive designs (AD) and multi-arm (MA) designs. Factorial clinical trials designs represent a combination of factorial and MAMS trial designs and can provide increased efficiency relative to fixed, traditional designs. We explore design choices associated with Factorial Adaptive Multi-Arm Multi-Stage (FAST) designs, which represent the combination of factorial and MAMS designs.
methodsSimulation studies were conducted to assess the impact of the type of analyses, the timing of analyses, and the effect size observed across multiple outcomes on trial operating characteristics for a FAST design. Given multiple outcomes types assessed within the hypothetical trial, the primary analysis approach for each assessment varied depending on data type.
resultsThe simulation studies demonstrate that the proposed class of FAST trial designs can offer a framework to potentially provide improvements relative to other trial designs, such as a MAMS or factorial trial. Further, we note that the design implementation decisions, such as the timing and type of analyses conducted throughout trial, can have a great impact on trial operating characteristics.
conclusionsMotivated by a trial currently under design, our work shows that the FAST category of trial can potentially offer benefits similar to both MAMS and factorial designs; however, the chosen design aspects which can be included in a FAST trial need to be thoroughly explored during the planning phase.
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