Unblinded Adaptive Statistical Information Design Based on Clinical Endpoint or Biomarker

Wang, Sue‐Jane; Brannath, Werner; Brückner, Matthias; Hung, H. M. James; Koch, Armin

doi:10.1080/19466315.2013.791639

Cited by 21 publications

(19 citation statements)

References 30 publications

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“…Difficulties faced in interpreting research findings with heterogeneity across interim stages have been discussed in detail [ 119 – 123 ]. Although it is hard to distinguish heterogeneity due to change from that influenced by operational bias, we believe there is a need to explore stage-wise heterogeneity by presenting key patient characteristics and results by independent stages and treatment groups.…”

Section: Interpretation Of Trial Resultsmentioning

confidence: 99%

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

Pallmann

Bedding

Choodari‐Oskooei

et al. 2018

BMC Med

523

449

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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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Section: Interpretation Of Trial Resultsmentioning

confidence: 99%

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

Pallmann

Bedding

Choodari‐Oskooei

et al. 2018

BMC Med

523

449

View full text Add to dashboard Cite

show abstract

“…Marked differences in treatment effects between stages may arise (for example, discussed in item 15b) making overall interpretation of their results difficult 92110267269270271272. The presence of heterogeneity questions the rationale for combining results from independent stages to produce overall evidence, as is also the case for combining individual studies in a meta-analysis 92273.…”

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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“…The draft guidance then recognizes two categories of adaptive designs: those which are generally well‐understood and for which established approaches to implementation are available, and others whose properties are less well‐understood and for which the community needs to collect more experience, although this distinction seems arbitrary to some extent because there are open questions in both categories. Regulatory statisticians specifically from the FDA continuously contribute to methodological research, for some recent contributions see , see also .…”

Section: Regulatory and Industry Perspectivesmentioning

confidence: 99%

Twenty‐five years of confirmatory adaptive designs: opportunities and pitfalls

Bauer

Bretz

Dragalin

et al. 2015

Statistics in Medicine

187

203

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'Multistage testing with adaptive designs' was the title of an article by Peter Bauer that appeared 1989 in the German journal Biometrie und Informatik in Medizin und Biologie. The journal does not exist anymore but the methodology found widespread interest in the scientific community over the past 25 years. The use of such multistage adaptive designs raised many controversial discussions from the beginning on, especially after the publication by Bauer and Köhne 1994 in Biometrics: Broad enthusiasm about potential applications of such designs faced critical positions regarding their statistical efficiency. Despite, or possibly because of, this controversy, the methodology and its areas of applications grew steadily over the years, with significant contributions from statisticians working in academia, industry and agencies around the world. In the meantime, such type of adaptive designs have become the subject of two major regulatory guidance documents in the US and Europe and the field is still evolving. Developments are particularly noteworthy in the most important applications of adaptive designs, including sample size reassessment, treatment selection procedures, and population enrichment designs. In this article, we summarize the developments over the past 25 years from different perspectives. We provide a historical overview of the early days, review the key methodological concepts and summarize regulatory and industry perspectives on such designs. Then, we illustrate the application of adaptive designs with three case studies, including unblinded sample size reassessment, adaptive treatment selection, and adaptive endpoint selection. We also discuss the availability of software for evaluating and performing such designs. We conclude with a critical review of how expectations from the beginning were fulfilled, and -if not -discuss potential reasons why this did not happen.

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Unblinded Adaptive Statistical Information Design Based on Clinical Endpoint or Biomarker

Cited by 21 publications

References 30 publications

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

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

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

Twenty‐five years of confirmatory adaptive designs: opportunities and pitfalls

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