Evidence map›Paper›PMID 41035030›Full record

ReviewBMC medicine2025

Practical guidance for conducting high-quality and rapid interim analyses in adaptive clinical trials.

Helen Mossop, Zoë Walmsley, Nina Wilson, Opeyemi Agbeleye, Michelle Bardgett, Alex Bevin-Nicholls, Matthew Breckons, Michael Cole, Dawn Craig, Munyaradzi Dimairo and 12 more

Abstract readReview
In one paragraph

Review in BMC medicine, 2025. 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. Article
  2. 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

22 authors.

Helen Mossop *Population Health Sciences Institute, Newcastle University, Newcastle Upon Tyne, UK.ORCID http://orcid.org/0000-0002-6260-3734
Zoë Walmsley *Population Health Sciences Institute, Newcastle University, Newcastle Upon Tyne, UK.ORCID http://orcid.org/0000-0002-1253-6668
Nina Wilson *Population Health Sciences Institute, Newcastle University, Newcastle Upon Tyne, UK.ORCID http://orcid.org/0000-0001-5908-1720
Opeyemi AgbeleyeNIHR Innovation Observatory, Newcastle University, Newcastle Upon Tyne, UK.ORCID http://orcid.org/0009-0008-6529-427X
Michelle BardgettNewcastle Clinical Trials Unit, Newcastle University, Newcastle Upon Tyne, UK.ORCID http://orcid.org/0000-0003-1393-2010
Alex Bevin-NichollsPopulation Health Sciences Institute, Newcastle University, Newcastle Upon Tyne, UK.ORCID http://orcid.org/0000-0003-3791-6402
Matthew BreckonsPopulation Health Sciences Institute, Newcastle University, Newcastle Upon Tyne, UK.ORCID http://orcid.org/0000-0003-3057-6767
Michael ColePopulation Health Sciences Institute, Newcastle University, Newcastle Upon Tyne, UK.ORCID http://orcid.org/0000-0003-3426-3717
Dawn CraigPopulation Health Sciences Institute, Newcastle University, Newcastle Upon Tyne, UK.ORCID http://orcid.org/0000-0002-5808-0096
Munyaradzi DimairoClinical Trials Research Unit, Sheffield Centre for Health and Related Research (SCHARR), University of Sheffield, Sheffield, UK.ORCID http://orcid.org/0000-0002-9311-6920
Helen HancockPopulation Health Sciences Institute, Newcastle University, Newcastle Upon Tyne, UK.ORCID http://orcid.org/0000-0002-1494-8551
Martin LawMedical Research Council Biostatistics Unit, University of Cambridge, Cambridge, UK.ORCID http://orcid.org/0000-0001-9594-348X
Andre LopesCRUK Cancer Trials Centre, University College London, London, UK.ORCID http://orcid.org/0000-0002-1405-7337
Nurulamin M NoorDepartment of Medicine, University of Cambridge, Cambridge, UK.ORCID http://orcid.org/0000-0003-3426-6408
Chizoba OparahNIHR Innovation Observatory, Newcastle University, Newcastle Upon Tyne, UK.ORCID http://orcid.org/0009-0008-9993-7683
Philip PallmannCentre for Trials Research, Cardiff University, Cardiff, UK.ORCID http://orcid.org/0000-0001-8274-9696
Julia PhillipsonNewcastle Clinical Trials Unit, Newcastle University, Newcastle Upon Tyne, UK.ORCID http://orcid.org/0000-0002-1358-4223
David S RobertsonMedical Research Council Biostatistics Unit, University of Cambridge, Cambridge, UK.ORCID http://orcid.org/0000-0001-6207-0416
M Dawn TearePopulation Health Sciences Institute, Newcastle University, Newcastle Upon Tyne, UK.ORCID http://orcid.org/0000-0003-3994-0051
Katie H ThomsonNIHR Innovation Observatory, Newcastle University, Newcastle Upon Tyne, UK.ORCID http://orcid.org/0000-0002-9614-728X
Christina YapClinical Trials and Statistics Unit, The Institute of Cancer Research, London, UK.ORCID http://orcid.org/0000-0002-6715-2514
James M S WasonPopulation Health Sciences Institute, Newcastle University, Newcastle Upon Tyne, UK. james.wason@newcastle.ac.uk.ORCID http://orcid.org/0000-0002-4691-126X

Funding

National Institute for Health and Care Research NIHR200173National Institute for Health and Care Research NIHR301614
6 · The paper itself

Abstract

backgroundAdaptive designs are increasingly being used in clinical trials within diverse clinical areas. They can offer advantages over traditional non-adaptive approaches, including improved efficiency and patient benefit. The level of improvement observed in practice depends to a large degree on conducting interim analyses (at which adaptations can be made to the trial based on collected data) rapidly and to a high standard.

methodsThe ROBust INterims for adaptive designs (ROBIN) project aimed to identify best practice for conducting high-quality and rapid interim analyses. This was done through evidence synthesis of published work, qualitative research with trial stakeholders working at public sector clinical trials units, engagement with patients and the public, and a meeting of trial stakeholders to discuss findings and agree recommendations.

resultsThis paper provides recommendations for teams that conduct adaptive trials about how to ensure interim analyses are done rapidly and to a high standard. We break down recommendations by stage of the trial. We also identify a lack of methodology on how best to involve patients in adaptive trials and related decision-making. A limitation of our recommendations is that the research was mostly focused on UK academic settings, although we believe much of the recommendations are relevant in other countries and to industry-sponsored trials.

conclusionsWhen following the recommendations outlined in this paper, the process of planning and executing interim analyses will be smoother; in turn, this will lead to more benefits from using adaptive designs.

Indexed as

Adaptive Clinical Trials as TopicClinical Trials as TopicResearch DesignHumansAdaptive trialInterim analysisTrial conduct

Identifiers

PMID41035030
PMCPMC12487222

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.