Evidence map›Paper›PMID 42549731›Full record

ArticleClinical trials (London, England)2026

Adaptive versus fixed designs in confirmatory clinical trials: centering the choice on ethics.

Stef Baas, Lukas Pin, David S Robertson, Frank Bretz, Hearn Jay Cho, Laura Flight, Rieke van der Graaf, Mackenzie Graham, Peter Jacko, Thomas Jaki and 18 more

Abstract read
In one paragraph

Article 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

28 authors.

Stef BaasMRC Biostatistics Unit, University of Cambridge, UK.ORCID 0000-0002-5890-1165
Lukas PinMRC Biostatistics Unit, University of Cambridge, UK.ORCID 0009-0003-9512-681X
David S RobertsonMRC Biostatistics Unit, University of Cambridge, UK.ORCID 0000-0001-6207-0416
Frank BretzAdvanced Quantitative Sciences, Novartis Pharma AG, Basel, Switzerland.ORCID 0000-0002-2008-8340
Hearn Jay ChoThe Multiple Myeloma Research Foundation, Norwalk, CT, USA.
Laura FlightNational Institute for Health and Care Excellence, Manchester, UK.
Rieke van der GraafDepartment of Bioethics and Health Humanities, University Medical Center Utrecht, The Netherlands.ORCID 0000-0003-4907-7044
Mackenzie GrahamEthox Centre, Oxford Population Health, University of Oxford, UK.ORCID 0000-0001-6870-1370
Peter JackoDepartment of Management Science, Lancaster University, UK.ORCID 0000-0003-3376-0260
Thomas JakiMRC Biostatistics Unit, University of Cambridge, UK.
Jonathan KimmelmanDepartment of Equity, Ethics and Policy, McGill University, Montreal, QC, Canada.ORCID 0000-0003-1614-6779
Andrea ManfrinMedicines and Healthcare products Regulatory Agency, London, UK.
Richard MilneRAND Europe, Cambridge, UK.
Pavel MozgunovMRC Biostatistics Unit, University of Cambridge, UK.ORCID 0000-0001-6810-0284
Philip PallmannCentre for Trials Research, Cardiff University, UK.ORCID 0000-0001-8274-9696
Tom ParkeBerry Consultants UK Ltd, Abingdon, UK.ORCID 0009-0009-5322-7763
Mahesh K B ParmarInstitute of Clinical Trials and Methodology, MRC Clinical Trials Unit, University College London, UK.
Vinciane PirardGlobal Medical Affairs Rare Diseases, Sanofi Belgium SA, Machelen, Belgium.ORCID 0009-0004-6737-9809
Kate SahanEthox Centre, Oxford Population Health, University of Oxford, UK.ORCID 0000-0001-5948-5581
Jerome Amir SinghHoward College School of Law, University of KwaZulu-Natal, Durban, South Africa.
Brian D M TomMRC Biostatistics Unit, University of Cambridge, UK.ORCID 0000-0002-3335-9322
John C WhittakerMRC Biostatistics Unit, University of Cambridge, UK.ORCID 0000-0002-3529-2379
Katie WozniakThe Multiple Myeloma Research Foundation, Norwalk, CT, USA.
David WrightRespiratory and Immunology Biometrics and Statistical Innovation, BioPharmaceuticals R&D, AstraZeneca, Cambridge, UK.ORCID 0000-0003-1990-888X
Haiyan ZhengDepartment of Mathematical Sciences, University of Bath, UK.ORCID 0000-0002-3385-2117
Alex John LondonPhilosophy Department, Carnegie Mellon University, Pittsburgh, PA, USA.ORCID 0000-0002-6450-0309
Mark SheehanEthox Centre, Oxford Population Health, University of Oxford, UK.ORCID 0000-0002-7191-901X
Sofía S VillarMRC Biostatistics Unit, University of Cambridge, UK.ORCID 0000-0001-7755-2637

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundBecause confirmatory clinical trials are costly, large-scale endeavors, the choice of their design carries significant weight. While the current methodological landscape offers tools to address residual pre-trial uncertainty through prespecified adaptations to design elements, design choices remain frequently constrained by prevailing orthodoxies.

methodsWe examine how unacknowledged design uncertainties (e.g., sample size calculations based on incorrect effect size or variance estimates) impact the statistical, ethical, and resource-stewardship goals of confirmatory trials. We contrast how fixed and adaptive design strategies handle these uncertainties, detailing the operational safeguards, firewalls, and trade-offs (e.g., complexity, operational bias) required to preserve trial integrity.

resultsStrict adherence to default templates prevents stakeholders from matching the design strategy to the specific complexities of the research question. We observe that the gold standard status of fixed designs often obscures their limitations in handling design uncertainties. A rigid adherence to these conventions can ethically hinder a trial's ability to deliver conclusive results. Conversely, while adaptive designs can offer tools to efficiently reduce uncertainty, we acknowledge that adaptive elements are not without cost; their implementation requires rigorous safeguards to manage specific risks to trial integrity and potential operational biases.

conclusionTo better align clinical research with its ethical and scientific mandates, we issue two calls to action. First, trial designers, including statisticians, must clearly articulate how target and design uncertainties impact ethical obligations, promoting an open-minded evaluation of both fixed and adaptive methods. Second, stakeholders must foreground ethical considerations during design selection, requiring explicit justification for the use-or non-use-of adaptive elements. The ethical path forward is not to default to the old or blindly adopt the new, but to explicitly justify the chosen design based on its responsiveness to the specific uncertainties of the trial. We posit that trial design must transition from a habit-based process to one where pre-trial uncertainties are openly discussed and addressed.

Indexed as

Clinical Trials as TopicResearch DesignHumansSample SizeUncertaintybioethicsdesign of experimentsdesign uncertiantymulti-stakeholder perspectivestrial integrity

Identifiers

PMID42549731
PMCPMC13624349

What OpenQuestion holds

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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.