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Cited by 829Statistical Methods in Clinical TrialsStatistical Methods and Bayesian InferencePharmaceutical studies and practices

Adaptive designs in clinical trials: why use them, and how to run and report them

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Pallmann, Philip, Bedding, Alun W., Choodari-Oskooei, Babak, Dimairo, Munyaradzi, Flight, Laura, Hampson, Lisa V., Holmes, Jane, Mander, Adrian P. +8 more·2018·BMC Medicine
DOI 10.1186/s12916-018-1017-7PMC PMC5830330
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Abstract

Adaptive designs can make clinical trials more flexible by utilising results accumulating in the trial to modify the trial's course in accordance with pre-specified rules. Trials with an adaptive design are often more efficient, informative and ethical than trials with a traditional fixed design since they often make better use of resources such as time and money, and might require fewer participants. Adaptive designs can be applied across all phases of clinical research, from early-phase dose escalation to confirmatory trials. The pace of the uptake of adaptive designs in clinical research, however, has remained well behind that of the statistical literature introducing new methods and highlighting their potential advantages. We speculate that one factor contributing to this is that the full range of adaptations available to trial designs, as well as their goals, advantages and limitations, remains unfamiliar to many parts of the clinical community. Additionally, the term adaptive design has been misleadingly used as an all-encompassing label to refer to certain methods that could be deemed controversial or that have been inadequately implemented.We believe that even if the planning and analysis of a trial is undertaken by an expert statistician, it is essential that the investigators understand the implications of using an adaptive design, for example, what the practical challenges are, what can (and cannot) be inferred from the results of such a trial, and how to report and communicate the results. This tutorial paper provides guidance on key aspects of adaptive designs that are relevant to clinical triallists. We explain the basic rationale behind adaptive designs, clarify ambiguous terminology and summarise the utility and pitfalls of adaptive designs. We discuss practical aspects around funding, ethical approval, treatment supply and communication with stakeholders and trial participants. Our focus, however, is on the interpretation and reporting of results from adaptive design trials, which we consider vital for anyone involved in medical research. We emphasise the general principles of transparency and reproducibility and suggest how best to put them into practice.

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  • Digital clinical trials could leverage multiple sources of participants' data to enable automatic phenotyping and subgrouping, which could be useful for adaptive clinical trial designs that use ongoing results to modify the trial in real time.

    “Digital clinical trials could leverage multiple sources of participants' data to enable automatic phenotyping and subgrouping 34 , which could be useful for adaptive clinical trial designs that use ongoing results to modify the trial in real time 39,40 .”

    From Multimodal biomedical AI (2022) · cites this paper as [39]

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Authors
Pallmann, P., Bedding, A. W., Choodari-Oskooei, B., Dimairo, M., Flight, L., Hampson, L. V., Holmes, J., Mander, A. P., Odondi, L., Sydes, M. R., Villar, S. S., Wason, J. M. S., Weir, C. J., Wheeler, G. M., Yap, C., & Jaki, T.
Affiliations
  • Lancaster University (GB)
  • Roche (United Kingdom) (GB)
  • University of Sheffield (GB)
  • AstraZeneca (United Kingdom) (GB)
  • University of Oxford (GB)
  • University of Cambridge (GB)
  • MRC Clinical Trials Unit at UCL (GB)
  • University of Edinburgh (GB)
  • Cancer Research UK Clinical Trials Unit (GB)
Corresponding author
Pallmann, Philip
ORCID
Venue
BMC Medicine
Publisher
Springer Science and Business Media LLC
Published
2018-02-28
Volume
16
Issue
1
Pages
29-29
ISSN
1741-7015 (ISSN-L)
DOI
10.1186/s12916-018-1017-7
PMC
PMC5830330
OpenAlex
W2791498037
Cited by
829
References
155
Citations by year
2026: 93 · 2025: 131 · 2024: 124 · 2023: 131 · 2022: 94 · 2021: 100 · 2020: 97 · 2019: 50 · 2018: 7 · 2014: 1
FWCI
52.90
Type
journal article
Language
en
Open access
Licence
cc-by
Locations
  • BMC Medicine (publishedVersion, cc-by)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • White Rose Research Online (University of Leeds, The University of Sheffield, University of York) (acceptedVersion)
  • ORCA Online Research @Cardiff (Cardiff University) (acceptedVersion)
  • University of Birmingham Research Portal (University of Birmingham) (submittedVersion, other-oa)
  • Edinburgh Research Explorer (University of Edinburgh) (submittedVersion, cc-by)
  • Apollo (University of Cambridge) (submittedVersion, cc-by)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
  • UCL Discovery (University College London) (submittedVersion)
  • University of Birmingham Research Portal (University of Birmingham) (submittedVersion, cc-by)
  • Spiral (Imperial College London) (submittedVersion, cc-by)
  • Apollo
  • Apollo (cc-by)
Funders
  • Medical Research Council (MR/L004933/1-R/N/P/B1, MR/K025635/1, MC_UU_12023/29, MC_UU_12023/24, MC_UU_12023/25, MC_EX_UU_G0800814, G0800860)
  • Programme Grants for Applied Research (NIHR-SRF-2015-08-001, DRF-2015-08-013)
  • Cancer Research UK (C22436/A15958)
Topics
  • Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Clinical Trials
  • Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Bayesian Inference
  • Health Sciences › Medicine › Pediatrics, Perinatology and Child Health › Pharmaceutical studies and practices
Keywords
adaptive design, clinical trial design, dose escalation, confirmatory trials, trial reporting, trial interpretation, transparency, reproducibility, research ethics approval, stakeholder communication, trial funding
MeSH terms
Clinical Trials as Topic, Humans, Research Design, Reproducibility of Results

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