Evidence map›Paper›PMID 36414953›Full record

Trial reportTrials2022

Interpreting a Bayesian phase II futility clinical trial.

Jonathan Beall, Christy Cassarly, Renee Martin

Abstract readClinical Trial, Phase II
In one paragraph

Trial report in Trials, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. Review
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

3 authors.

Jonathan Beall *Department of Public Health Sciences, Medical University of South Carolina, Charleston, SC, USA. bealljo@musc.edu.ORCID http://orcid.org/0000-0003-2135-2606
Christy Cassarly *Department of Public Health Sciences, Medical University of South Carolina, Charleston, SC, USA.
Renee Martin *Department of Public Health Sciences, Medical University of South Carolina, Charleston, SC, 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 U01NS087748
6 · The paper itself

Abstract

backgroundA resurgence of research into phase II trial design in the mid-2000s led to the use of futility designs in a wide variety of disease areas. Phase II futility studies differ from efficacy studies in that their null hypothesis is that treatment, relative to control, does not meet or exceed the level of benefit required to justify additional study. A rejection of the null hypothesis indicates that the treatment should not proceed to a larger confirmatory trial.

methodsBayesian approaches to the design of phase II futility clinical trials are presented and allow for the quantification of key probabilities, such as the predictive probability of current trial success or even the predictive probability of a future trial's success.

resultsWe provide an illustration of the design and interpretation of a phase II futility study constructed in a Bayesian framework. We focus on the operating characteristics of our motivating trial based on a simulation study, as well as the general interpretation of trial outcomes, type I, and type II errors in this framework.

conclusionsPhase II futility clinical trials, when designed under in a Bayesian framework, offer an alternative approach to the design of mid-phase studies which provide unique benefits relative to trials designed in a frequentist framework and designs which focus on treatment efficacy.

Indexed as

Medical FutilityResearch DesignBayes TheoremComputer SimulationHumansProbabilityBayesianClinical trialFutilityPhase II

Identifiers

PMID36414953
PMCPMC9682669

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.