Evidence map›Paper›PMID 41190638›Full record

ReviewClinical trials (London, England)2026

A review of use of external data and update on reporting standards in Sequential Multiple-Assignment Randomised Trials.

Isaac J Egesa, Laura Bonnett, Richard Emsley, Anthony Marson, Catrin T Smith

Abstract readReview
In one paragraph

Review in Clinical trials (London, England), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

5 authors.

Isaac J EgesaHealth Data Science, Institute of Population Health, University of Liverpool, Liverpool, UK.ORCID 0000-0003-0483-1517
Laura BonnettHealth Data Science, Institute of Population Health, University of Liverpool, Liverpool, UK.ORCID 0000-0002-6981-9212
Richard EmsleyInstitute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK.ORCID 0000-0002-1218-675X
Anthony MarsonInstitute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, UK.
Catrin T SmithHealth Data Science, Institute of Population Health, University of Liverpool, Liverpool, UK.

Funding

Medical Research Council MR/W006049/1
6 · The paper itself

Abstract

backgroundThe Sequential Multiple-Assignment Randomised Trial (SMART) design is considered the gold standard for developing adaptive interventions, which tailor treatments to individual patient characteristics and responses. While SMART offers a rigorous framework aligned with real-world clinical decision-making, it is often complex, time-consuming, and costly. As interest in SMART design grows, there is increasing recognition for the need to improve its implementation through more explicit guidance and best practices. Efficiency gains may also be possible by incorporating external data to inform their design, conduct, and analysis. This review aimed to identify all published trials using the SMART design, summarise their design, conduct, and reporting practices and evaluate the use of external data in their implementation.

methodsWe searched PubMed, Medline, PsycINFO, Scopus, and Web of Science databases for all SMART up to June 30, 2024. External data were defined as non-simulated individual patient data collected outside the main SMART to supplement or inform the main trial.

resultsWe included 80 SMART, of which 35 (44%) were completed and 45 (56%) were ongoing. Most trials reported two phases of randomisation (93%), with the primary aim focusing on evaluating main effects (81%) of interventions at the first stage of randomisation. There was inadequate reporting of several key aspects, including sample size estimation, statistical analysis software, allocation concealment, data missingness, multiple testing, sensitivity analysis, and the use of SMART in the title. Seventeen (21%) SMART (4-completed trials and 13-trial protocols) referred to the use of external data from electronic health records (n = 12) and registries (n = 5). External data was used for recruitment (n = 11), outcome measures (n = 6), and to provide baseline covariate information (n = 1).

conclusionSMART designs are increasingly used to develop adaptive interventions across diverse clinical contexts, yet key methodological features and basic components remain inconsistently reported. This limits transparency, reproducibility, and potential for translation into routine care. Although external data are widely used in standard randomised controlled trials, their use in the SMART is still limited, likely due to methodological and infrastructural challenges and the absence of tailored reporting standards. To improve the efficiency and generalisability of SMART designs, expert-led extensions of CONSORT and SPIRIT guidelines are needed, including specific recommendations for reporting external data use. Future research should explore optimal external data sources for informing SMART components and promote interdisciplinary collaboration and training to support high-quality implementation.

Indexed as

Randomized Controlled Trials as TopicResearch DesignHumansadaptive interventionsexternal dataroutine dataSequential Multiple-Assignment Randomised Trialsystematic review

Identifiers

PMID41190638
PMCPMC12909610

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.