Design considerations for Factorial Adaptive Multi-Arm Multi-Stage (FAST) clinical trials

Trials. 2024 Sep 12;25(1):608. doi: 10.1186/s13063-024-08400-6.

Abstract

Background: Multi-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.

Methods: Simulation 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.

Results: The 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.

Conclusions: Motivated 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.

Keywords: Adaptive design; Clinical trial; Factorial design; Multi-arm; Multi-stage.

MeSH terms

  • Clinical Trials as Topic* / methods
  • Computer Simulation*
  • Data Interpretation, Statistical
  • Endpoint Determination
  • Humans
  • Models, Statistical
  • Research Design*
  • Sample Size
  • Time Factors
  • Treatment Outcome