ArticlePharmacoEconomics2015
Evaluating the Generalisability of Trial Results: Introducing a Centre- and Trial-Level Generalisability Index.
Article in PharmacoEconomics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 2 of them syntheses that pooled it.
What it found
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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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
7 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Identification of tools used to assess the external validity of randomized controlled trials in reviews: a systematic review of measurement properties.BMC medical research methodology · 2022Pooled it
- Pooled it
- Kanuka honey versus aciclovir for the topical treatment of herpes simplex labialis: a randomised controlled trial.BMJ open · 2019Trial
- Timing of dialysis in acute kidney injury using routinely collected data and dynamic treatment regimes.Critical care (London, England) · 2022Article
- Efficacy of a 3% Kānuka oil cream for the treatment of moderate-to-severe eczema: A single blind randomised vehicle-controlled trial.EClinicalMedicine · 2022Article
- The concept of justifiable healthcare and how big data can help us to achieve it.BMC medical informatics and decision making · 2021Review
- Recruitment, screening, and baseline participant characteristics in the WALK 2.0 study: A randomized controlled trial using web 2.0 applications to promote physical activity.Contemporary clinical trials communications · 2016Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
backgroundFew randomised controlled trials (RCTs) recruit centres representatively, which may limit the external validity of trial results.
objectiveThe aim of this study was to propose a proof-of-concept method of assessing the generalisability of the clinical and cost-effectiveness findings of a given RCT.
methodsWe developed a generalisability index (Gix), informed by centre-level characteristics, as a measure of centre and trial representativeness. The centre-level Gix quantifies how representative a centre is in relation to its jurisdiction, e.g. a country or health authority. The trial-level Gix quantifies how representative trial recruitment is in relation to clinical practice in the jurisdiction. Taking a real-world RCT as a case study and assuming trial-wide results to represent 'true jurisdiction values', we used simulation methods to recreate 5000 RCTs and investigate the relationship between trial representativeness, reflected by the standardised trial-Gix, and the deviation of simulated trial results from the 'true values'.
resultsThe simulation study provides evidence that trial results (odds ratio for the primary outcome and incremental quality-adjusted life-years) were influenced by the representativeness of the sample of recruiting centres. Simulated RCTs with the closest results to the 'true values' were those whose recruitment closely mirrored the jurisdiction-wide context. Results appeared robust to six alternative specifications of the Gix.
conclusionsOur findings suggest that an unrepresentative selection of centres limits the external validity of trial results. The Gix may be a valuable tool to help facilitate rational selection of trial centres and ensure the generalisability of results at the jurisdiction level.
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Registered trials
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.