Evidence mapPaperPMID 34749778Full record

SynthesisTrials2021

Use of external evidence for design and Bayesian analysis of clinical trials: a qualitative study of trialists' views.

Gemma L Clayton, Daisy Elliott, Julian P T Higgins, Hayley E Jones

Abstract readSystematic Review
In one paragraph

Synthesis in Trials, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

4 authors.

Gemma L ClaytonDepartment of Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK. gemma.clayton@bristol.ac.uk.ORCID http://orcid.org/0000-0002-9525-2758
Daisy ElliottDepartment of Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK.
Julian P T HigginsDepartment of Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK.
Hayley E JonesDepartment of Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK.

Funding

Medical Research Council MR/L004933/2Medical Research Council MR/M014533/1Medical Research Council PhDnational institute for health research (nihr) applied research collaboration west (arc west) at university hospitals bristol and weston nhs foundation trust and the nihr bristol biomedical research centre at university hospitals bristol and weston nhs foun NF-SI-0617-10145
6 · The paper itself

Abstract

backgroundEvidence from previous studies is often used relatively informally in the design of clinical trials: for example, a systematic review to indicate whether a gap in the current evidence base justifies a new trial. External evidence can be used more formally in both trial design and analysis, by explicitly incorporating a synthesis of it in a Bayesian framework. However, it is unclear how common this is in practice or the extent to which it is considered controversial. In this qualitative study, we explored attitudes towards, and experiences of, trialists in incorporating synthesised external evidence through the Bayesian design or analysis of a trial.

methodsSemi-structured interviews were conducted with 16 trialists: 13 statisticians and three clinicians. Participants were recruited across several universities and trials units in the United Kingdom using snowball and purposeful sampling. Data were analysed using thematic analysis and techniques of constant comparison.

resultsTrialists used existing evidence in many ways in trial design, for example, to justify a gap in the evidence base and inform parameters in sample size calculations. However, no one in our sample reported using such evidence in a Bayesian framework. Participants tended to equate Bayesian analysis with the incorporation of prior information on the intervention effect and were less aware of the potential to incorporate data on other parameters. When introduced to the concepts, many trialists felt they could be making more use of existing data to inform the design and analysis of a trial in particular scenarios. For example, some felt existing data could be used more formally to inform background adverse event rates, rather than relying on clinical opinion as to whether there are potential safety concerns. However, several barriers to implementing these methods in practice were identified, including concerns about the relevance of external data, acceptability of Bayesian methods, lack of confidence in Bayesian methods and software, and practical issues, such as difficulties accessing relevant data.

conclusionsDespite trialists recognising that more formal use of external evidence could be advantageous over current approaches in some areas and useful as sensitivity analyses, there are still barriers to such use in practice.

Indexed as

Research PersonnelBayes TheoremHumansQualitative ResearchUnited KingdomBayesian analysisEvidence synthesisInformative prior distributionsMeta-epidemiologyQualitativeTrials

Identifiers

PMID34749778
PMCPMC8577005

What Socratic 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 Socratic graph.