Addressing Challenges and Opportunities of “Less Well-Understood” Adaptive Designs

He, Weili; Gallo, Paul; Miller, Emma R.; Jemiai, Yannis; Maca, Jeff; Koury, Ken; Fan, Xiaoyin; Jiang, Qi; Wang, Cunshan; Lin, Min

doi:10.1177/2168479016663265

Cited by 10 publications

(14 citation statements)

References 28 publications

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“…For example, use of statistical methods that combine data across stages may become questionable or may make overall results uninterpretable. AD randomised trials whose integrity was severely compromised by disclosure of interim results have resulted in regulators questioning the credibility of conclusions 201202. Most AD randomised trials, 76% (52/68)49 and 60% (151/251),112 did not disclose methods to minimise potential operational bias during interim analyses.…”

Section: The Ace Checklistmentioning

confidence: 99%

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. 2020

BMJ

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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.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.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 comprises 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.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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Section: The Ace Checklistmentioning

confidence: 99%

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. 2020

BMJ

View full text Add to dashboard Cite

show abstract

“…For example, use of statistical methods that combine data across stages may become questionable or may make overall results uninterpretable. AD randomised trials whose integrity was severely compromised by disclosure of interim results resulted in regulators questioning the credibility of conclusions [209,210]. Most AD randomised trials, 76% (52/68) [117] and 60% (151/251) [125], did not disclose methods to minimise potential operational bias during interim analyses.…”

Section: Fig 1 Legendmentioning

confidence: 99%

“…Of note, part of the Bayesian community argue that it is not principled to control frequentist operating characteristics in Bayesian ADs [252], although these can be computed and presented [22,160,253]. decisions taken, present logistical challenges, or diminish the efficiency of the AD depending on their prevalence and the objective of the adaptations [209]. It is therefore useful for readers to understand how overrunning participants were dealt with at interim analyses especially after a terminal adaptation decision (e.g., when a trial or treatment arms were stopped early for efficacy or futility).…”

Section: Fig 1 Legendmentioning

confidence: 99%

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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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“…For a comparison of effect‐based versus nuisance parameter–based sample size re‐estimation and the respective operational and regulatory challenges, we refer to existing literature. ()…”

Section: Introductionmentioning

confidence: 99%

Sample size re‐estimation incorporating prior information on a nuisance parameter

Mütze

Schmidli

Friede

2017

Pharmaceutical Statistics

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Prior information is often incorporated informally when planning a clinical trial. Here, we present an approach on how to incorporate prior information, such as data from historical clinical trials, into the nuisance parameter-based sample size re-estimation in a design with an internal pilot study. We focus on trials with continuous endpoints in which the outcome variance is the nuisance parameter. For planning and analyzing the trial, frequentist methods are considered. Moreover, the external information on the variance is summarized by the Bayesian meta-analytic-predictive approach. To incorporate external information into the sample size re-estimation, we propose to update the meta-analytic-predictive prior based on the results of the internal pilot study and to re-estimate the sample size using an estimator from the posterior. By means of a simulation study, we compare the operating characteristics such as power and sample size distribution of the proposed procedure with the traditional sample size re-estimation approach that uses the pooled variance estimator. The simulation study shows that, if no prior-data conflict is present, incorporating external information into the sample size re-estimation improves the operating characteristics compared to the traditional approach. In the case of a prior-data conflict, that is, when the variance of the ongoing clinical trial is unequal to the prior location, the performance of the traditional sample size re-estimation procedure is in general superior, even when the prior information is robustified. When considering to include prior information in sample size re-estimation, the potential gains should be balanced against the risks.

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Addressing Challenges and Opportunities of “Less Well-Understood” Adaptive Designs

Cited by 10 publications

References 28 publications

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

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

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

Sample size re‐estimation incorporating prior information on a nuisance parameter

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