Evidence map›Paper›PMID 39261887›Full record

ArticleTrials2024

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

Jonathan Beall, Jordan Elm, Matthew W Semler, Li Wang, Todd Rice, Hooman Kamel, William Mack, Akshitkumar M Mistry

Abstract read
In one paragraph

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.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Jonathan BeallDepartment of Public Health Sciences, Medical University of South Carolina, Charleston, SC, USA. bealljo@musc.edu.ORCID http://orcid.org/0000-0003-2135-2606
Jordan ElmDepartment of Public Health Sciences, Medical University of South Carolina, Charleston, SC, USA.
Matthew W SemlerDepartment of Medicine, Division of Allergy, Pulmonary, and Critical Care Medicine, Vanderbilt University Medical Center, Nashville, TN, USA.
Li WangDepartment of Biostatistics, Vanderbilt University School of Medicine, Nashville, TN, USA.
Todd RiceDepartment of Medicine, Division of Allergy, Pulmonary, and Critical Care Medicine, Vanderbilt University Medical Center, Nashville, TN, USA.
Hooman KamelDepartment of Neurology, Weill Cornell Medicine, New York, NY, USA.
William MackDepartment of Neurosurgery, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.
Akshitkumar M MistryDepartment of Neurosurgery, University of Louisville, Louisville, KY, USA.

Funding

Workshop to Identify Collaborative Project(s) for the NIH StrokeNet and the Japan NEtwork for Clinical Stroke Trials (NECST)U01NS087748 · NINDS · MEDICAL UNIVERSITY OF SOUTH CAROLINA · PI Catherine R. Dillon, Jordan J. Elm · 2014 to 2026
$14.1M
NINDS NIH HHS 5U01NS087748-0NINDS NIH HHS U01 NS087748
6 · The paper itself

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.

Indexed as

Clinical Trials as TopicComputer SimulationResearch DesignData Interpretation, StatisticalEndpoint DeterminationHumansModels, StatisticalSample SizeTime FactorsTreatment OutcomeAdaptive designClinical trialFactorial designMulti-armMulti-stage

Identifiers

PMID39261887
PMCPMC11391813

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.