Development process of a consensus-driven CONSORT extension for randomised trials using an adaptive design

Dimairo, Munyaradzi; Coates, Elizabeth; Pallmann, Philip; Todd, Susan; Julious, Steven A.; Jaki, Thomas; Wason, James; Mander, Adrian; Weir, Christopher J.; König, Franz; Walton, Marc K.; Biggs, Katie; Nicholl, Jon; Hamasaki, Toshimitsu; Proschan, Michael A.; Scott, John; Ando, Yumiko; Hind, Daniel; Altman, Douglas G.

doi:10.1186/s12916-018-1196-2

Cited by 36 publications

(51 citation statements)

References 88 publications

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“…However, there may be a case for continuing the trial to completion, with the goal of narrowing the confidence interval on the treatment effect sufficiently to rule out any clinically relevant benefit. In more generality, CONSORT guidelines for adaptive designs are currently under development [14], which may lead to improved reporting practices; however, adequately reporting conditional power calculations is not a requirement of the current guidelines.…”

Section: Discussionmentioning

confidence: 99%

A systematic survey of randomised trials that stopped early for reasons of futility

Walter

Han

Guyatt

et al. 2020

BMC Med Res Methodol

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Background: Randomised trial protocols may incorporate interim analyses, with the potential to stop the study for futility if early data show insufficient promise of a treatment benefit. Previously, we have shown that this approach will theoretically lead to mis-estimation of the treatment effect. We now wished to ascertain the importance of this phenomenon in practice. Methods: We reviewed the methods and results in a set of trials that had stopped for futility, identified through an extensive literature search. We recorded clinical areas, interventions, study design, outcomes, trial setting, sponsorship, planned and actual treatment effects, sample sizes; power; and if there was a data safety monitoring board, or a published protocol. We identified: if interim analyses were pre-specified, and how many analyses actually occurred; what pre-specified criteria might define futility; if a futility analysis formed the basis for stopping; who made the decision to stop; and the conditional power of each study, i.e. the probability of statistically significant results if the study were to continue to its complete sample size. Results: We identified 52 eligible trials, covering many clinical areas. Most trials had multiple centres, tested drugs, and 40% were industry sponsored. There were 75% where at least one interim analysis was planned a priori; a majority had only one interim analysis, typically with about half the target total sample size. A majority of trials did not pre-define a stopping rule, and a variety of reasons were given for stopping. Few studies calculated and reported low conditional power to justify the early stop. When conditional power could be calculated, it was typically low, especially under the current trend hypothesis. However, under the original design hypothesis, a few studies had relatively high conditional power. Data collection often continued after the interim analysis. Conclusions: Although other factors will typically be involved, we conclude that, from the perspective of conditional power, stopping early for futility was probably reasonable in most cases, but documentation of the basis for stopping was often missing or vague. Interpretation of truncated trials would be enhanced by improved reporting of stopping protocols, and of their actual execution.

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Section: Discussionmentioning

confidence: 99%

A systematic survey of randomised trials that stopped early for reasons of futility

Walter

Han

Guyatt

et al. 2020

BMC Med Res Methodol

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“…The ACE Steering Committee [13] agreed a definition of an AD (Box 1) consistent with the literature [14][15][16][17][18].…”

Section: Adaptive Designs: Definition Current Use and Reportingmentioning

confidence: 86%

The Adaptive designs CONSORT Extension (ACE) Statement: A checklist with explanation and elaboration guideline for reporting randomised trials that use an adaptive design

Dimairo

Pallmann

Wason

et al. 2019

Preprint

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Background Adaptive designs (ADs) allow pre-planned changes to an ongoing trial without compromising the validity of conclusions and it is essential to distinguish pre-planned from unplanned changes that may also occur. The reporting of ADs in randomised trials is inconsistent and needs improving. Incompletely reported AD randomised trials are difficult to reproduce and are hard to interpret and synthesise. This consequently hampers their ability to inform practice as well as future research and contributes to research waste. Better transparency and adequate reporting will enable the potential benefits of ADs to be realised. Methods This extension to the Consolidated Standards Of Reporting Trials (CONSORT) 2010 Statement was developed to enhance the reporting of randomised AD clinical trials. We developed an Adaptive designs CONSORT Extension (ACE) guideline through a two-stage Delphi process with input from multidisciplinary key stakeholders in clinical trials research in the public and private sectors from 21 countries, followed by a consensus meeting. Members of the CONSORT Group were involved during the development process. Results The paper presents the ACE checklists for AD randomised trial reports and abstracts, as well as an explanation with examples to aid the application of the guideline. The ACE checklist is comprised of seven new items, nine modified items, six unchanged items for which additional explanatory text clarifies further considerations for ADs, and 20 unchanged items not requiring further explanatory text. The ACE abstract checklist has one new item, one modified item, one unchanged item with additional explanatory text for ADs, and 15 unchanged items not requiring further explanatory text. Conclusions The intention is to enhance transparency and improve reporting of AD randomised trials to improve the interpretability of their results and reproducibility of their methods, results and inference. We also hope indirectly to facilitate the much-needed knowledge transfer of innovative trial designs to maximise their potential benefits.

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“…Finally, we note one primary possible avenue for future development of the web application: numerous papers have now provided designs for adaptive multi-arm trials (e.g., [42,43]), and software for their determination in certain settings [44,45]. Given the evidential increased interest in such designs [46], allowing for their determination would be a valuable extension to our application. The specific values that can be seen are those that correspond to the trial described in [38].…”

Section: Discussionmentioning

confidence: 99%

A web application for the design of multi-arm clinical trials

Grayling

Wason

2020

BMC Cancer

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Multi-arm designs provide an effective means of evaluating several treatments within the same clinical trial. Given the large number of treatments now available for testing in many disease areas, it has been argued that their utilisation should increase.However, for any given clinical trial there are numerous possible multi-arm designs that could be used, and choosing between them can be a difficult task. This task is complicated further by a lack of available easy-to-use software for designing multi-arm trials.To aid the wider implementation of multi-arm clinical trial designs, we have developed a web application for sample size calculation when using a variety of popular multiple comparison corrections. Furthermore, the application supports sample size calculation to control several varieties of power, as well as the determination of optimised arm-wise allocation ratios. It is built using the Shiny package in the R programming language, is free to access on any device with an internet browser, and requires no programming knowledge to use. The application provides the core information required by statisticians and clinicians to review the operating characteristics of a chosen multi-arm clinical trial design. We hope that it will assist with the future utilisation of such designs in practice. 1 arXiv:1906.09178v1 [stat.CO]

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Development process of a consensus-driven CONSORT extension for randomised trials using an adaptive design

Cited by 36 publications

References 88 publications

A systematic survey of randomised trials that stopped early for reasons of futility

A systematic survey of randomised trials that stopped early for reasons of futility

The Adaptive designs CONSORT Extension (ACE) Statement: A checklist with explanation and elaboration guideline for reporting randomised trials that use an adaptive design

A web application for the design of multi-arm clinical trials

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