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

BMJ ◽  
2020 ◽  
pp. m115 ◽  
Author(s):  
Munyaradzi Dimairo ◽  
Philip Pallmann ◽  
James Wason ◽  
Susan Todd ◽  
Thomas Jaki ◽  
...  
Keyword(s):  
Clinical Trials ◽  
Adaptive Design ◽  
Randomised Trial ◽  
Adaptive Designs ◽  
Future Research ◽  
Randomised Trials ◽  
Public And Private ◽  
Key Stakeholders ◽  
Potential Benefits ◽  
Explanatory Text

AbstractAdaptive 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.

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

2019 ◽  
Author(s):  
Munyaradzi Dimairo ◽  
Philip Pallmann ◽  
James Wason ◽  
Susan Todd ◽  
Thomas Jaki ◽  
...  
Keyword(s):  
Clinical Trials ◽  
Adaptive Design ◽  
Randomised Trial ◽  
Adaptive Designs ◽  
Future Research ◽  
Randomised Trials ◽  
Public And Private ◽  
Key Stakeholders ◽  
Potential Benefits ◽  
Explanatory Text

Abstract 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.

scholarly journals The People’s Trial: Supporting the Public’s Understanding of Randomised Trials.

2021 ◽  
Author(s):  
Elaine Finucane ◽  
Ann O’Brien ◽  
Shaun Treweek ◽  
John Newell ◽  
Kishor Das ◽  
...  
Keyword(s):  
Clinical Trials ◽  
Gold Standard ◽  
Randomised Trial ◽  
Health Claims ◽  
Public Understanding ◽  
Randomised Trials ◽  
Online Surveys ◽  
The Public ◽  
Trial Conduct ◽  
Robust Evidence

Abstract BackgroundRandomised trials are considered the gold standard in providing robust evidence on the effectiveness of interventions. However, there are relatively few initiatives to help increase public understanding of what randomised trials are and why they are important. This limits the overall acceptance of and public participation in clinical trials. The People’s Trial aims to help the public learn about randomised trials, to understand why they matter, and to be better equipped to think critically about health claims. MethodsUsing a reflexive approach, we describe the processes of development, conduct and dissemination of The People’s Trial. ResultsOver 3000 members of the public, from 72 countries, participated in The People’s Trial. Through a series of online surveys, the public chose the question The People’s Trial would try to answer and decided the components of the trial question. In December 2019, 991 participants were recruited to a trial to answer the question identified and prioritised by the public, i.e., ‘Does reading a book in bed make a difference to sleep in comparison to not reading a book in bed?’ We called this trial The Reading Trial.We report processes of The People’s Trial in seven phases, paralleling the steps of a randomised trial, i.e., question identification and prioritisation, recruitment, randomisation, trial conduct, data analysis, and sharing of findings. We describe the decisions we made, the processes we used, the challenges we encountered, and the lessons we learned. ConclusionThe People’s trial engaged members of the public successfully in the design, conduct, and dissemination of a randomised trial demonstrating the potential for such initiatives to help the public learn about randomised trials, to understand why they matter, and to be better equipped to think critically about health claims. Trial Registration The Reading Trial was registered 4th December 2019 on ClinicalTrials.gov, ID: NCT04185818.

A Bayesian Hybrid Adaptive Randomisation Design for Clinical Trials with Survival Outcomes

2016 ◽  
Vol 55 (01) ◽  
pp. 4-13
Author(s):  
M. Moatti ◽  
S. Zohar ◽  
W. F. Rosenberger ◽  
S. Chevret
Keyword(s):  
Clinical Trial ◽  
Multiple Myeloma ◽  
Clinical Trials ◽  
Adaptive Design ◽  
Hazard Ratio ◽  
Adaptive Designs ◽  
Stopping Rules ◽  
Phase Iii ◽  
Optimal Criterion ◽  
Fully Bayesian

SummaryBackground: Response-adaptive randomisation designs have been proposed to im -prove the efficiency of phase III randomised clinical trials and improve the outcomes of the clinical trial population. In the setting of failure time outcomes, Zhang and Rosen -berger (2007) developed a response-adaptive randomisation approach that targets an optimal allocation, based on a fixed sample size. Objectives: The aim of this research is to propose a response-adaptive randomisation procedure for survival trials with an interim monitoring plan, based on the following optimal criterion: for fixed variance of the esti -mated log hazard ratio, what allocation minimizes the expected hazard of failure? We demonstrate the utility of the design by re -designing a clinical trial on multiple myeloma. Methods: To handle continuous monitoring of data, we propose a Bayesian response-adap -tive randomisation procedure, where the log hazard ratio is the effect measure of interest. Combining the prior with the normal likelihood, the mean posterior estimate of the log hazard ratio allows derivation of the optimal target allocation. We perform a simu lationstudy to assess and compare the perform -ance of this proposed Bayesian hybrid adaptive design to those of fixed, sequential or adaptive – either frequentist or fully Bayesian – designs. Non informative normal priors of the log hazard ratio were used, as well as mixture of enthusiastic and skeptical priors. Stopping rules based on the posterior dis -tribution of the log hazard ratio were com -puted. The method is then illus trated by redesigning a phase III randomised clinical trial of chemotherapy in patients with multiple myeloma, with mixture of normal priors elicited from experts. Results: As expected, there was a reduction in the proportion of observed deaths in the adaptive vs. non-adaptive designs; this reduction was maximized using a Bayes mix -ture prior, with no clear-cut improvement by using a fully Bayesian procedure. The use of stopping rules allows a slight decrease in the observed proportion of deaths under the alternate hypothesis compared with the adaptive designs with no stopping rules. Conclusions: Such Bayesian hybrid adaptive survival trials may be promising alternatives to traditional designs, reducing the duration of survival trials, as well as optimizing the ethical concerns for patients enrolled in the trial.

scholarly journals Adaptive design clinical trials: a review of the literature and ClinicalTrials.gov

BMJ Open ◽  
2018 ◽  
Vol 8 (2) ◽  
pp. e018320 ◽  
Author(s):  
Laura E Bothwell ◽  
Jerry Avorn ◽  
Nazleen F Khan ◽  
Aaron S Kesselheim
Keyword(s):  
Clinical Trials ◽  
Phase I ◽  
Interim Analysis ◽  
Adaptive Design ◽  
Drug Application ◽  
Adaptive Designs ◽  
European Medicines Agency ◽  
Product Approval ◽  
New Drug ◽  
Adaptive Trials

ObjectivesThis review investigates characteristics of implemented adaptive design clinical trials and provides examples of regulatory experience with such trials.DesignReview of adaptive design clinical trials in EMBASE, PubMed, Cochrane Registry of Controlled Clinical Trials, Web of Science and ClinicalTrials.gov. Phase I and seamless Phase I/II trials were excluded. Variables extracted from trials included basic study characteristics, adaptive design features, size and use of independent data monitoring committees (DMCs) and blinded interim analyses. We also examined use of the adaptive trials in new drug submissions to the Food and Drug Administration (FDA) and European Medicines Agency (EMA) and recorded regulators’ experiences with adaptive designs.Results142 studies met inclusion criteria. There has been a recent growth in publicly reported use of adaptive designs among researchers around the world. The most frequently appearing types of adaptations were seamless Phase II/III (57%), group sequential (21%), biomarker adaptive (20%), and adaptive dose-finding designs (16%). About one-third (32%) of trials reported an independent DMC, while 6% reported blinded interim analysis. We found that 9% of adaptive trials were used for FDA product approval consideration, and 12% were used for EMA product approval consideration. International regulators had mixed experiences with adaptive trials. Many product applications with adaptive trials had extensive correspondence between drug sponsors and regulators regarding the adaptive designs, in some cases with regulators requiring revisions or alterations to research designs.ConclusionsWider use of adaptive designs will necessitate new drug application sponsors to engage with regulatory scientists during planning and conduct of the trials. Investigators need to more consistently report protections intended to preserve confidentiality and minimise potential operational bias during interim analysis.

Adaptive designs from a Data Safety Monitoring Board perspective: Some controversies and some case studies

2017 ◽  
Vol 14 (5) ◽  
pp. 462-469 ◽  
Author(s):  
Bruce W Turnbull
Keyword(s):  
Clinical Trials ◽  
Case Studies ◽  
Adaptive Design ◽  
Safety Monitoring ◽  
Data Safety Monitoring Board ◽  
Adaptive Designs ◽  
Data Safety ◽  
Safety Monitoring Board ◽  
Data Safety Monitoring ◽  
Personal Experiences

This article describes vignettes concerning interactions with Data Safety Monitoring Boards during the design and monitoring of some clinical trials with an adaptive design. Most reflect personal experiences by the author.

scholarly journals The Bayesian Design of Adaptive Clinical Trials

2021 ◽  
Vol 18 (2) ◽  
pp. 530
Author(s):  
Alessandra Giovagnoli
Keyword(s):  
Clinical Trials ◽  
Adaptive Design ◽  
Recent Literature ◽  
Adaptive Designs ◽  
Bayesian Design ◽  
High Expectations ◽  
Reading Material ◽  
Adaptive Trials ◽  
Adaptive Clinical Trials ◽  
Interesting Reading

This paper presents a brief overview of the recent literature on adaptive design of clinical trials from a Bayesian perspective for statistically not so sophisticated readers. Adaptive designs are attracting a keen interest in several disciplines, from a theoretical viewpoint and also—potentially—from a practical one, and Bayesian adaptive designs, in particular, have raised high expectations in clinical trials. The main conceptual tools are highlighted here, with a mention of several trial designs proposed in the literature that use these methods, including some of the registered Bayesian adaptive trials to this date. This review aims at complementing the existing ones on this topic, pointing at further interesting reading material.

scholarly journals Non-static framework for understanding adaptive designs: an ethical justification in paediatric trials

2021 ◽  
pp. medethics-2021-107263
Author(s):  
Michael OS Afolabi ◽  
Lauren E Kelly
Keyword(s):  
Clinical Trials ◽  
Cost Effective ◽  
Adaptive Designs ◽  
Research Subjects ◽  
Public And Private ◽  
Age Related ◽  
Public And Private Stakeholders ◽  
Social Scientific ◽  
Trial Efficiency ◽  
Scientific Value

Many drugs used in paediatric medicine are off-label. There is a rising call for the use of adaptive clinical trial designs (ADs) in responding to the need for safe and effective drugs given their potential to offer efficiency and cost-effective benefits compared with traditional clinical trials. ADs have a strong appeal in paediatric clinical trials given the small number of available participants, limited understanding of age-related variability and the desire to limit exposure to futile or unsafe interventions. Although the ethical value of adaptive trials has increasingly come under scrutiny, there is a paucity of literature on the ethical dilemmas that may be associated with paediatric adaptive designs (PADs). This paper highlights some of these ethical concerns around safety, scientific/social value and caregiver/guardian comprehension of the trial design. Against this background, the paper develops a non-static conceptual lens for understanding PADs. It shows that ADs are epistemically open and reduce some of the knowledge-associated uncertainties inherent in clinical trials as well as fast-track the time to draw conclusions about the value of evaluated drugs/treatments. On this note, the authors argue that PADs are ethically justifiable given they (1) have multiple layers of safety, exposing enrolled children to lesser potential risks, (2) create social/scientific value generally and for paediatric populations in particular, (3) specifically foster the flourishing of paediatric populations and (4) can significantly improve paediatric trial efficiency when properly designed and implemented. However, because PADs are relatively new and their regulatory, ethical and logistical characteristics are yet to be clarified in some jurisdictions, the cooperation of various public and private stakeholders is required to ensure that the interests of children, their caregivers and parents/guardians are best served while exposing paediatric research subjects to the most minimal of risks when they are enrolled in paediatric trials that use ADs.

scholarly journals An evidence base to optimise methods for involving patient and public contributors in clinical trials: a mixed-methods study

2015 ◽  
Vol 3 (39) ◽  
pp. 1-142 ◽  
Author(s):  
Carrol Gamble ◽  
Louise Dudley ◽  
Alison Allam ◽  
Philip Bell ◽  
Deborah Buck ◽  
...  
Keyword(s):  
Clinical Trials ◽  
Mixed Methods ◽  
Public Involvement ◽  
Research Collaboration ◽  
Research Programme ◽  
Evidence Base ◽  
Research Community ◽  
Future Research ◽  
Randomised Trials ◽  
Managerial Roles

BackgroundIn comparison with other study designs, randomised trials are regarded as particularly likely to benefit from patient and public involvement (PPI). Using mixed-methods research we investigated PPI from the perspectives of researchers and PPI contributors.MethodsRandomised trials in receipt of funding from the Health Technology Assessment (HTA) programme between 2006 and 2010 were identified. Funding applications and board and referee comments were obtained and data relevant to PPI extracted. Chief investigators (CIs), PPI contributors and UK Clinical Research Collaboration Registered Clinical Trials Units (RCTUs) were surveyed. Interviews were conducted with researchers and PPI contributors.ResultsA total of 111 trials were included. Text relevant to PPI was identified in half of the trials for which the first-stage applications were available, but only one-quarter described PPI within their development. In the second stage of the application, the majority provided some text relevant to PPI, with over half having PPI in their development. Fewer than half of referees commented on PPI, and funding boards rarely provided comments in relation to PPI. Seventy-three per cent (81 of 111) of CIs responded to the survey and 98% (79 of 81) included PPI at some stage in their trial. CIs considered high impact from PPI contributors to occur more frequently in trial setup, with low or no impact being more common during trial conduct, analysis and dissemination. Only one-third of CIs provided PPI contributor contact details but all contributors contacted completed the survey. The majority of contributors felt engaged and valued by the research team. Interviews were conducted with researchers and/or PPI contributors for 28 trials identifying two main influences on perception of PPI impact: whether or not CIs expressed personal goals and plans for PPI; and the quality of their relationship with the PPI contributors. The importance of early engagement was identified, with opportunity for input thereafter limited. Three PPI roles were identified: oversight, managerial and responsive. Oversight roles, as required by funders, were associated with low impact in comparison with responsive or managerial roles. Most researchers could see some value in PPI training for researchers, although those that had received such training themselves expressed concerns about its purpose and evidence base. Training for PPI contributors was considered unnecessary, with conversational approaches preferred, although this did not appear to provide an opportunity for role negotiation. The RCTU survey response rate was 85% (39 of 46). The majority (37 of 39) reported PPI within trials co-ordinated by their unit. Trial characteristics were used by half to determine the approach to PPI. Two-thirds reported recent developments or changes in implementing plans for PPI (21 of 33). Support to PPI contributors was commonly offered through members of staff at the unit.ConclusionsPPI is occurring in the majority of trials funded by the HTA programme, but uncertainty remains about how it is assessed and valued. Early involvement, building a relationship between researchers and contributors, responsive or managerial roles, and having defined goals for PPI were associated with impact. Efficiency could be gained by utilising the RCTU network to identify and tackle challenges, and develop a risk-based approach utilising trial characteristics. Recommendations are made to trial funders and the research community. Given the difficulties for some informants in recalling PPI contributions, future research using a prospective approach would be valuable. Ethnographic research that combines observation and multi-informant interviews is likely to be informative in identifying impact. The research community needs to give further consideration to processes for selecting PPI contributors and models of implementing PPI.FundingThe National Institute for Health Research Health Services and Delivery Research programme and INVOLVE.

Bayesian optimal response-adaptive design for binary responses using stopping rule

2016 ◽  
Vol 27 (3) ◽  
pp. 891-904 ◽  
Author(s):  
Fumiyasu Komaki ◽  
Atanu Biswas
Keyword(s):  
Clinical Trials ◽  
Adaptive Design ◽  
Real Data ◽  
Adaptive Designs ◽  
Phase Iii ◽  
Data Set ◽  
Binary Responses ◽  
Phase Iii Clinical Trials ◽  
Number Of Patients ◽  
Response Adaptive Designs

Response-adaptive designs are used in phase III clinical trials to allocate a larger number of patients to the better treatment arm. Optimal designs are explored in the recent years in the context of response-adaptive designs, in the frequentist view point only. In the present paper, we propose some response-adaptive designs for two treatments based on Bayesian prediction for phase III clinical trials. Some properties are studied and numerically compared with some existing competitors. A real data set is used to illustrate the applicability of the proposed methodology where we redesign the experiment using parameters derived from the data set.

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