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Lee A, Shan D, Castle D, Rajji TK, Ma C. Landscape of Phase II Trials in Alzheimer's Disease. J Alzheimers Dis 2023; 96:745-757. [PMID: 37840500 DOI: 10.3233/jad-230660] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/17/2023]
Abstract
BACKGROUND Drug development in Alzheimer's disease (AD) over the past two decades has had high rates of failure. Novel trial designs, such as adaptive designs, have the potential to improve the efficiency of drug development in AD. OBJECTIVE To evaluate the design characteristics, temporal trends, and differences in design between sponsor types in phase II trials of investigational agents in AD. METHODS Phase I/II, II, and II/III trials for AD with drug or other biological interventions registered from December 1996 to December 2021 in ClinicalTrials.gov were included. Descriptive statistics were used to summarize trial characteristics. Linear, logistic, and multinomial regression models assessed temporal trends and differences between sponsor types in design characteristics. RESULTS Of N = 474 trials identified, randomized parallel group design was the most common design (72%). Only 12 trials (2.5%) used an adaptive design; adaptive features included early stopping rules, model-based dose-finding, adaptive treatment arm selection, and response adaptive randomization. The use of non-randomized parallel-group and open-label single arm designs increased over time. No temporal trend in the use of adaptive design was identified. Trials sponsored by industry only were more likely to use a randomized parallel-group design and have a larger estimated sample size than trials with other sponsor types. CONCLUSION Our systematic review showed that very few phase II trials in AD used an adaptive trial design. Innovation and implementation of novel trial designs in AD trials can accelerate the drug development process.
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Affiliation(s)
- Alina Lee
- Centre for Addiction and Mental Health, Toronto, Ontario, Canada
| | - Di Shan
- Centre for Addiction and Mental Health, Toronto, Ontario, Canada
| | - David Castle
- Department of Psychiatry, University of Tasmania, Tasmania, Australia
- Centre for Mental Health Service Innovation, Statewide Mental Health Service, Tasmania, Australia
| | - Tarek K Rajji
- Centre for Addiction and Mental Health, Toronto, Ontario, Canada
- Toronto Dementia Research Alliance, Toronto, Canada
- Temerty Faculty of Medicine, University of Toronto, Toronto, Canada
| | - Clement Ma
- Centre for Addiction and Mental Health, Toronto, Ontario, Canada
- Division of Biostatistics, Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada
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Afolabi MO, Kelly LE. Non-static framework for understanding adaptive designs: an ethical justification in paediatric trials. JOURNAL OF MEDICAL ETHICS 2022; 48:825-831. [PMID: 34362828 PMCID: PMC9626916 DOI: 10.1136/medethics-2021-107263] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 01/18/2021] [Accepted: 06/25/2021] [Indexed: 06/13/2023]
Abstract
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.
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Affiliation(s)
- Michael Os Afolabi
- Department of Pediatrics and Child Health, Faculty of Health Sciences, University of Manitoba, Winnipeg, Manitoba, Canada
| | - Lauren E Kelly
- Department of Pediatrics and Child Health, Faculty of Health Sciences, University of Manitoba, Winnipeg, Manitoba, Canada
- Children's Hospital Research Institute of Manitoba, Winnipeg, Manitoba, Canada
- George & Fay Yee Centre for Healthcare Innovation, Winnipeg, Manitoba, Canada
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Broglio K, Meurer WJ, Durkalski V, Pauls Q, Connor J, Berry D, Lewis RJ, Johnston KC, Barsan WG. Comparison of Bayesian vs Frequentist Adaptive Trial Design in the Stroke Hyperglycemia Insulin Network Effort Trial. JAMA Netw Open 2022; 5:e2211616. [PMID: 35544137 PMCID: PMC9096598 DOI: 10.1001/jamanetworkopen.2022.11616] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
IMPORTANCE Bayesian adaptive trial design has the potential to create more efficient clinical trials. However, a barrier to the uptake of bayesian adaptive designs for confirmatory trials is limited experience with how they may perform compared with a frequentist design. OBJECTIVE To compare the performance of a bayesian and a frequentist adaptive clinical trial design. DESIGN, SETTING, AND PARTICIPANTS This prospective cohort study compared 2 trial designs for a completed multicenter acute stroke trial conducted within a National Institutes of Health neurologic emergencies clinical trials network, with individual patient-level data, including the timing and order of enrollments and outcome ascertainment, from 1151 patients with acute stroke and hyperglycemia randomized to receive intensive or standard insulin therapy. The implemented frequentist design had group sequential boundaries for efficacy and futility interim analyses at 90 days after randomization for 500, 700, 900, and 1100 patients. The bayesian alternative used predictive probability of trial success to govern early termination for efficacy and futility with a first interim analysis at 500 randomized patients and subsequent interims after every 100 randomizations. MAIN OUTCOMES AND MEASURES The main outcome was the sample size at end of study, which was defined as the sample size at which each of the studies stopped accrual of patients. RESULTS Data were collected from 1151 patients. As conducted, the frequentist design passed the futility boundary after 936 participants were randomized. Using the same sequence and timing of randomization and outcome data, the bayesian alternative crossed the futility boundary approximately 3 months earlier after 800 participants were randomized. CONCLUSIONS AND RELEVANCE Both trial designs stopped for futility before reaching the planned maximum sample size. In both cases, the clinical community and patients would benefit from learning the answer to the trial's primary question earlier. The common feature across the 2 designs was frequent interim analyses to stop early for efficacy or for futility. Differences between how these analyses were implemented between the 2 trials resulted in the differences in early stopping.
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Affiliation(s)
- Kristine Broglio
- AstraZeneca US, Gaithersburg, Maryland
- Berry Consultants LLC, Austin, Texas
| | - William J. Meurer
- Berry Consultants LLC, Austin, Texas
- Department of Emergency Medicine, University of Michigan, Ann Arbor
- Department of Neurology, University of Michigan, Ann Arbor
- Stroke Program, University of Michigan, Ann Arbor
| | - Valerie Durkalski
- Department of Public Health Sciences, Medical University of South Carolina, Charleston
| | - Qi Pauls
- Department of Public Health Sciences, Medical University of South Carolina, Charleston
| | - Jason Connor
- ConfluenceStat LLC, Cooper City, Florida
- Department of Medical Education, University of Central Florida College of Medicine, Orlando
| | | | - Roger J. Lewis
- Berry Consultants LLC, Austin, Texas
- Department of Emergency Medicine, Harbor-UCLA Medical Center, Torrance, California
- Department of Emergency Medicine, David Geffen School of Medicine at UCLA, Los Angeles, California
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Varnai P, Davé A, Farla K, Nooijen A, Petrosova L. The Evidence REVEAL Study: Exploring the Use of Real-World Evidence and Complex Clinical Trial Design by the European Pharmaceutical Industry. Clin Pharmacol Ther 2020; 110:1180-1189. [PMID: 33216976 PMCID: PMC8596609 DOI: 10.1002/cpt.2103] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2020] [Accepted: 10/15/2020] [Indexed: 11/22/2022]
Abstract
The rapid evolution of science and technology allows innovative approaches to generate new types of evidence about the effectiveness of medical product development so as to speed up patients’ access to better diagnostics and treatment. Our study explored how two emerging approaches, the use of real‐world evidence (RWE) and complex clinical trial (CCT) design, are currently being used by the pharmaceutical industry to support premarketing authorization of medical product development and reviewed the international landscape for regulatory acceptance of such novel approaches. Combining evidence from a literature review, company survey, and interviews with international regulators and experts, we found that 80% of Europe‐based pharmaceutical companies have used RWE and 50% have used CCTs, in some capacity. Further, we present case examples of how companies are using these approaches and how international regulators are preparing for such developments. To conclude, we provide a set of recommendations for European industry and regulators to consider so that these novel approaches achieve their full potential within the EU regulatory system.
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Dimairo M, Pallmann P, Wason J, Todd S, Jaki T, Julious SA, Mander AP, Weir CJ, Koenig F, Walton MK, Nicholl JP, Coates E, Biggs K, Hamasaki T, Proschan MA, Scott JA, Ando Y, Hind D, Altman DG. The adaptive designs CONSORT extension (ACE) statement: a checklist with explanation and elaboration guideline for reporting randomised trials that use an adaptive design. Trials 2020; 21:528. [PMID: 32546273 PMCID: PMC7298968 DOI: 10.1186/s13063-020-04334-x] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022] Open
Abstract
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. In order to encourage its wide dissemination this article is freely accessible on the BMJ and Trials journal websites."To maximise the benefit to society, you need to not just do research but do it well" Douglas G Altman.
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Affiliation(s)
- Munyaradzi Dimairo
- School of Health and Related Research, University of Sheffield, Sheffield, S1 4DA, UK.
| | | | - James Wason
- MRC Biostatistics Unit, University of Cambridge, Cambridge, UK
- Institute of Health and Society, Newcastle University, Newcastle, UK
| | - Susan Todd
- Department of Mathematics and Statistics, University of Reading, Reading, UK
| | - Thomas Jaki
- Department of Mathematics and Statistics, Lancaster University, Lancaster, UK
| | - Steven A Julious
- School of Health and Related Research, University of Sheffield, Sheffield, S1 4DA, UK
| | - Adrian P Mander
- Centre for Trials Research, Cardiff University, Cardiff, UK
- MRC Biostatistics Unit, University of Cambridge, Cambridge, UK
| | - Christopher J Weir
- Edinburgh Clinical Trials Unit, Usher Institute, University of Edinburgh, Edinburgh, UK
| | - Franz Koenig
- Centre for Medical Statistics, Informatics, and Intelligent Systems, Medical University of Vienna, Vienna, Austria
| | - Marc K Walton
- Janssen Pharmaceuticals, Titusville, New Jersey, USA
| | - Jon P Nicholl
- School of Health and Related Research, University of Sheffield, Sheffield, S1 4DA, UK
| | - Elizabeth Coates
- School of Health and Related Research, University of Sheffield, Sheffield, S1 4DA, UK
| | - Katie Biggs
- School of Health and Related Research, University of Sheffield, Sheffield, S1 4DA, UK
| | | | - Michael A Proschan
- National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, USA
| | - John A Scott
- Division of Biostatistics in the Center for Biologics Evaluation and Research, Food and Drug Administration, Rockville, USA
| | - Yuki Ando
- Pharmaceuticals and Medical Devices Agency, Tokyo, Japan
| | - Daniel Hind
- School of Health and Related Research, University of Sheffield, Sheffield, S1 4DA, UK
| | - Douglas G Altman
- Centre for Statistics in Medicine, University of Oxford, Oxford, UK
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Dimairo M, Pallmann P, Wason J, Todd S, Jaki T, Julious SA, Mander AP, Weir CJ, Koenig F, Walton MK, Nicholl JP, Coates E, Biggs K, Hamasaki T, Proschan MA, Scott JA, Ando Y, Hind D, Altman DG. 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; 369:m115. [PMID: 32554564 PMCID: PMC7298567 DOI: 10.1136/bmj.m115] [Citation(s) in RCA: 55] [Impact Index Per Article: 13.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 11/19/2019] [Indexed: 12/11/2022]
Abstract
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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Affiliation(s)
- Munyaradzi Dimairo
- School of Health and Related Research, University of Sheffield, Sheffield S1 4DA, UK
| | | | - James Wason
- MRC Biostatistics Unit, University of Cambridge, UK
- Institute of Health and Society, Newcastle University, UK
| | - Susan Todd
- Department of Mathematics and Statistics, University of Reading, UK
| | - Thomas Jaki
- Department of Mathematics and Statistics, Lancaster University, UK
| | - Steven A Julious
- School of Health and Related Research, University of Sheffield, Sheffield S1 4DA, UK
| | - Adrian P Mander
- Centre for Trials Research, Cardiff University, UK
- MRC Biostatistics Unit, University of Cambridge, UK
| | - Christopher J Weir
- Edinburgh Clinical Trials Unit, Usher Institute, University of Edinburgh, UK
| | - Franz Koenig
- Centre for Medical Statistics, Informatics, and Intelligent Systems, Medical University of Vienna, Austria
| | | | - Jon P Nicholl
- School of Health and Related Research, University of Sheffield, Sheffield S1 4DA, UK
| | - Elizabeth Coates
- School of Health and Related Research, University of Sheffield, Sheffield S1 4DA, UK
| | - Katie Biggs
- School of Health and Related Research, University of Sheffield, Sheffield S1 4DA, UK
| | | | - Michael A Proschan
- National Institute of Allergy and Infectious Diseases, National Institutes of Health, USA
| | - John A Scott
- Division of Biostatistics in the Center for Biologics Evaluation and Research, Food and Drug Administration, USA
| | - Yuki Ando
- Pharmaceuticals and Medical Devices Agency, Japan
| | - Daniel Hind
- School of Health and Related Research, University of Sheffield, Sheffield S1 4DA, UK
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Madani Kia T, Marshall JC, Murthy S. Stakeholder perspectives on adaptive clinical trials: a scoping review. Trials 2020; 21:539. [PMID: 32552852 PMCID: PMC7301522 DOI: 10.1186/s13063-020-04466-0] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2019] [Accepted: 05/29/2020] [Indexed: 11/10/2022] Open
Abstract
Background Adaptive clinical trials (ACTs) represent an emerging approach to trial design where accumulating data are used to make decisions about future conduct. Adaptations can include comparisons of multiple dose tiers, response-adaptive randomization, sample size re-estimation, and efficacy/futility stopping rules. The objective of this scoping review is to assess stakeholder attitudes, perspectives, and understanding of adaptive trials. Methods We conducted a review of articles examining stakeholders encompassing the broad medical trial community’s perspectives of adaptive designs (ADs). A computerized search was conducted of four electronic databases with relevant search terms. Following screening of articles, the primary findings of each included article were coded for study design, population studied, purpose, and primary implications. Results Our team retrieved 167 peer-reviewed titles in total from the database search and 5 additional titles through searching web-based search engines for gray literature. Of those 172 titles, 152 were non-duplicate citations. Of these, 119 were not given full-text reviews, as their titles and abstracts indicated that they did not meet the inclusion criteria. Thirty-three articles were carefully examined for relevance, and of those, 18 were chosen to be part of the analysis; the other 15 were excluded, as they were not relevant upon closer inspection. Perceived advantages to ADs included limiting ineffective treatments and efficiency in answering the research question; −perceived barriers included insufficient sample size for secondary outcomes, challenges of consent, potential for bias, risk of type 1 error, cost and time to adaptively design trials, unclear rationales for using Ads, and, most importantly, a lack of education regarding ADs among stakeholders within the clinical trial community. Perceptions among different types of stakeholders varied from sector to sector, with patient perspectives being noticeably absent from the literature. Conclusion There are diverse perceptions regarding ADs among stakeholders. Further training, guidelines, and toolkits on the proper use of ADs are needed at all levels to overcome many of these perceived barriers. While education for principal investigators is important, it is also crucial to educate other groups in the community, such as patients, as well as clinicians and staff involved in their daily implementation.
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Affiliation(s)
- Tina Madani Kia
- BC Children's Hospital Research Institute, 4500 Oak Street, Vancouver, BC, Canada.
| | - John C Marshall
- Li Ka Shing Knowledge Institute, Unity Health Toronto, University of Toronto, Toronto, ON, Canada
| | - Srinivas Murthy
- BC Children's Hospital Research Institute, 4500 Oak Street, Vancouver, BC, Canada
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Flight L, Julious S, Brennan A, Todd S, Hind D. How can health economics be used in the design and analysis of adaptive clinical trials? A qualitative analysis. Trials 2020; 21:252. [PMID: 32143728 PMCID: PMC7060544 DOI: 10.1186/s13063-020-4137-2] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2019] [Accepted: 02/04/2020] [Indexed: 12/04/2022] Open
Abstract
INTRODUCTION Adaptive designs offer a flexible approach, allowing changes to a trial based on examinations of the data as it progresses. Adaptive clinical trials are becoming a popular choice, as the prudent use of finite research budgets and accurate decision-making are priorities for healthcare providers around the world. The methods of health economics, which aim to maximise the health gained for money spent, could be incorporated into the design and analysis of adaptive clinical trials to make them more efficient. We aimed to understand the perspectives of stakeholders in health technology assessments to inform recommendations for the use of health economics in adaptive clinical trials. METHODS A qualitative study explored the attitudes of key stakeholders-including researchers, decision-makers and members of the public-towards the use of health economics in the design and analysis of adaptive clinical trials. Data were collected using interviews and focus groups (29 participants). A framework analysis was used to identify themes in the transcripts. RESULTS It was considered that answering the clinical research question should be the priority in a clinical trial, notwithstanding the importance of cost-effectiveness for decision-making. Concerns raised by participants included handling the volatile nature of cost data at interim analyses; implementing this approach in global trials; resourcing adaptive trials which are designed and adapted based on health economic outcomes; and training stakeholders in these methods so that they can be implemented and appropriately interpreted. CONCLUSION The use of health economics in the design and analysis of adaptive clinical trials has the potential to increase the efficiency of health technology assessments worldwide. Recommendations are made concerning the development of methods allowing the use of health economics in adaptive clinical trials, and suggestions are given to facilitate their implementation in practice.
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Affiliation(s)
- Laura Flight
- School of Health And Related Research, University of Sheffield, Sheffield, UK
| | - Steven Julious
- School of Health And Related Research, University of Sheffield, Sheffield, UK
| | - Alan Brennan
- School of Health And Related Research, University of Sheffield, Sheffield, UK
| | - Susan Todd
- Department of Mathematics and Statistics, University of Reading, Reading, UK
| | - Daniel Hind
- School of Health And Related Research, University of Sheffield, Sheffield, UK
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Abstract
BACKGROUND/AIMS The increasing cost of the drug development process has seen interest in the use of adaptive trial designs grow substantially. Accordingly, much research has been conducted to identify barriers to increasing the use of adaptive designs in practice. Several articles have argued that the availability of user-friendly software will be an important step in making adaptive designs easier to implement. Therefore, we present a review of the current state of software availability for adaptive trial design. METHODS We review articles from 31 journals published in 2013-2017 that relate to methodology for adaptive trials to assess how often code and software for implementing novel adaptive designs is made available at the time of publication. We contrast our findings against these journals' policies on code distribution. We also search popular code repositories, such as Comprehensive R Archive Network and GitHub, to identify further existing user-contributed software for adaptive designs. From this, we are able to direct interested parties toward solutions for their problem of interest. RESULTS Only 30% of included articles made their code available in some form. In many instances, articles published in journals that had mandatory requirements on code provision still did not make code available. There are several areas in which available software is currently limited or saturated. In particular, many packages are available to address group sequential design, but comparatively little code is present in the public domain to determine biomarker-guided adaptive designs. CONCLUSIONS There is much room for improvement in the provision of software alongside adaptive design publications. In addition, while progress has been made, well-established software for various types of trial adaptation remains sparsely available.
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Affiliation(s)
- Michael John Grayling
- MRC Biostatistics Unit, University of Cambridge, Cambridge, UK.,Population Health Sciences Institute, Newcastle University, Newcastle upon Tyne, UK
| | - Graham Mark Wheeler
- Cancer Research UK & UCL Cancer Trials Centre, University College London, London, UK
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Tidwell RSS, Peng SA, Chen M, Liu DD, Yuan Y, Lee JJ. Bayesian clinical trials at The University of Texas MD Anderson Cancer Center: An update. Clin Trials 2019; 16:645-656. [PMID: 31450957 DOI: 10.1177/1740774519871471] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
BACKGROUND/AIMS In our 2009 article, we showed that Bayesian methods had established a foothold in developing therapies in our institutional oncology trials. In this article, we will document what has happened since that time. In addition, we will describe barriers to implementing Bayesian clinical trials, as well as our experience overcoming them. METHODS We reviewed MD Anderson Cancer Center clinical trials submitted to the institutional protocol office for scientific and ethical review between January 2009 and December 2013, the same length time period as the previous article. We tabulated Bayesian methods implemented for design or analyses for each trial and then compared these to our previous findings. RESULTS Overall, we identified 1020 trials and found that 283 (28%) had Bayesian components so we designated them as Bayesian trials. Among MD Anderson-only and multicenter trials, 56% and 14%, respectively, were Bayesian, higher rates than our previous study. Bayesian trials were more common in phase I/II trials (34%) than in phase III/IV (6%) trials. Among Bayesian trials, the most commonly used features were for toxicity monitoring (65%), efficacy monitoring (36%), and dose finding (22%). The majority (86%) of Bayesian trials used non-informative priors. A total of 75 (27%) trials applied Bayesian methods for trial design and primary endpoint analysis. Among this latter group, the most commonly used methods were the Bayesian logistic regression model (N = 22), the continual reassessment method (N = 20), and adaptive randomization (N = 16). Median institutional review board approval time from protocol submission was the same 1.4 months for Bayesian and non-Bayesian trials. Since the previous publication, the Biomarker-Integrated Approaches of Targeted Therapy for Lung Cancer Elimination (BATTLE) trial was the first large-scale decision trial combining multiple treatments in a single trial. Since then, two regimens in breast cancer therapy have been identified and published from the cooperative Investigation of Serial Studies to Predict Your Therapeutic Response with Imaging and Molecular Analysis (I-SPY 2), enhancing cooperation among investigators and drug developers across the nation, as well as advancing information needed for personalized medicine. Many software programs and Shiny applications for Bayesian trial design and calculations are available from our website which has had more than 21,000 downloads worldwide since 2004. CONCLUSION Bayesian trials have the increased flexibility in trial design needed for personalized medicine, resulting in more cooperation among researchers working to fight against cancer. Some disadvantages of Bayesian trials remain, but new methods and software are available to improve their function and incorporation into cancer clinical research.
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Affiliation(s)
- Rebecca S Slack Tidwell
- Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - S Andrew Peng
- Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Minxing Chen
- Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Diane D Liu
- Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Ying Yuan
- Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - J Jack Lee
- Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
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11
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Dimairo M, Coates E, Pallmann P, Todd S, Julious SA, Jaki T, Wason J, Mander AP, Weir CJ, Koenig F, Walton MK, Biggs K, Nicholl J, Hamasaki T, Proschan MA, Scott JA, Ando Y, Hind D, Altman DG. Development process of a consensus-driven CONSORT extension for randomised trials using an adaptive design. BMC Med 2018; 16:210. [PMID: 30442137 PMCID: PMC6238302 DOI: 10.1186/s12916-018-1196-2] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/05/2018] [Accepted: 10/23/2018] [Indexed: 11/12/2022] Open
Abstract
BACKGROUND Adequate reporting of adaptive designs (ADs) maximises their potential benefits in the conduct of clinical trials. Transparent reporting can help address some obstacles and concerns relating to the use of ADs. Currently, there are deficiencies in the reporting of AD trials. To overcome this, we have developed a consensus-driven extension to the CONSORT statement for randomised trials using an AD. This paper describes the processes and methods used to develop this extension rather than detailed explanation of the guideline. METHODS We developed the guideline in seven overlapping stages: 1) Building on prior research to inform the need for a guideline; 2) A scoping literature review to inform future stages; 3) Drafting the first checklist version involving an External Expert Panel; 4) A two-round Delphi process involving international, multidisciplinary, and cross-sector key stakeholders; 5) A consensus meeting to advise which reporting items to retain through voting, and to discuss the structure of what to include in the supporting explanation and elaboration (E&E) document; 6) Refining and finalising the checklist; and 7) Writing-up and dissemination of the E&E document. The CONSORT Executive Group oversaw the entire development process. RESULTS Delphi survey response rates were 94/143 (66%), 114/156 (73%), and 79/143 (55%) in rounds 1, 2, and across both rounds, respectively. Twenty-seven delegates from Europe, the USA, and Asia attended the consensus meeting. The main checklist has seven new and nine modified items and six unchanged items with expanded E&E text to clarify further considerations for ADs. The abstract checklist has one new and one modified item together with an unchanged item with expanded E&E text. The E&E document will describe the scope of the guideline, the definition of an AD, and some types of ADs and trial adaptations and explain each reporting item in detail including case studies. CONCLUSIONS We hope that making the development processes, methods, and all supporting information that aided decision-making transparent will enhance the acceptability and quick uptake of the guideline. This will also help other groups when developing similar CONSORT extensions. The guideline is applicable to all randomised trials with an AD and contains minimum reporting requirements.
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Affiliation(s)
- Munyaradzi Dimairo
- School of Health and Related Research, University of Sheffield, Regent Court, 30 Regent Street, Sheffield, S1 4DA, UK.
| | - Elizabeth Coates
- School of Health and Related Research, University of Sheffield, Regent Court, 30 Regent Street, Sheffield, S1 4DA, UK
| | | | | | - Steven A Julious
- School of Health and Related Research, University of Sheffield, Regent Court, 30 Regent Street, Sheffield, S1 4DA, UK
| | | | - James Wason
- MRC Biostatistics Unit, University of Cambridge, Cambridge, UK
- Institute of Health and Society, Newcastle University, Newcastle upon Tyne, UK
| | - Adrian P Mander
- MRC Biostatistics Unit, University of Cambridge, Cambridge, UK
| | | | - Franz Koenig
- Centre for Medical Statistics, Informatics, and Intelligent Systems, Medical University of Vienna, Vienna, Austria
| | - Marc K Walton
- Janssen Pharmaceuticals, Titusville, New Jersey, USA
| | - Katie Biggs
- School of Health and Related Research, University of Sheffield, Regent Court, 30 Regent Street, Sheffield, S1 4DA, UK
| | - Jon Nicholl
- School of Health and Related Research, University of Sheffield, Regent Court, 30 Regent Street, Sheffield, S1 4DA, UK
| | | | - Michael A Proschan
- National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, USA
| | - John A Scott
- Division of Biostatistics in the Center for Biologics Evaluation and Research, Food and Drug Administration, White Oak, USA
| | - Yuki Ando
- Pharmaceuticals and Medical Devices Agency, Tokyo, Japan
| | - Daniel Hind
- School of Health and Related Research, University of Sheffield, Regent Court, 30 Regent Street, Sheffield, S1 4DA, UK
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12
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Clinical Trial Design for Investigational Cardio-Regenerative Therapy. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2018. [PMID: 30238373 DOI: 10.1007/978-3-319-97421-7_11] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register]
Abstract
Human trials of cardio-regenerative biologic therapies are being performed worldwide to address a growing, unmet need for durable treatments of cardiovascular disease. A well-constructed clinical trial design for these novel therapies requires careful attention to defining a clear hypothesis, a patient population, and anticipated outcomes. The scope of screening, method of randomization, blinding approach, data monitoring, and statistical analysis plan are the foundational elements that must be addressed in any clinical trial. Although the experience of human trials involving extracellular matrix constructs for cardiovascular disease treatment is limited, numerous lessons have been learned in the field of cell therapy that are translatable across all biologic treatment options. Future progress in this field may include testing combinations of cells, gene-transfer agents, and matrix and identifying treatment responders versus nonresponders.
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13
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Wallach JD, Ross JS, Naci H. The US Food and Drug Administration’s expedited approval programs: Evidentiary standards, regulatory trade-offs, and potential improvements. Clin Trials 2018; 15:219-229. [DOI: 10.1177/1740774518770648] [Citation(s) in RCA: 31] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
The US Food and Drug Administration has several regulatory programs and pathways to expedite the development and approval of therapeutic agents aimed at treating serious or life-debilitating conditions. A common feature of these programs is the regulatory flexibility, which allows for a customized approval approach that enables market authorization on the basis of less rigorous evidence, in exchange for requiring postmarket evidence generation. An increasing share of therapeutic agents approved by the Food and Drug Administration in recent years are associated with expedited programs. In this article, we provide an overview of the evidentiary standards required by the Food and Drug Administration’s expedited development and review programs, summarize the findings of the recent academic literature demonstrating some of the limitations of these programs, and outline potential opportunities to address these limitations. Recent evidence suggests that therapeutic agents in the Food and Drug Administration’s expedited programs are approved on the basis of fewer and smaller studies that may lack comparator groups and random allocation, and rather than focusing on clinical outcomes for study endpoints, rely instead on surrogate markers of disease. Once on the market, agents receiving expedited approvals are often quickly incorporated into clinical practice, and evidence generated in the postmarket period may not necessarily address the evidentiary limitations at the time of market entry. Furthermore, not all pathways require additional postmarket studies. Evidence suggests that drugs in expedited approval programs are associated with a greater likelihood that the Food and Drug Administration will take a safety action following market entry. There are several opportunities to improve the timeliness, information value, and validity of the pre- and postmarket studies of therapeutic agents receiving expedited approvals. When use of nonrandomized and uncontrolled studies cannot be avoided prior to market entry, randomized trials should be mandatory in the postmarket period, unless there are strong justifications for not carrying out such studies. In the premarket period, validity of the surrogate markers can be improved by more rigorously evaluating their correlation with patient-relevant clinical outcomes. Opportunities to reduce the duration, complexity, and cost of postmarket randomized trials should not compromise their validity and instead incorporate pragmatic “real-world” design elements. Despite recent enthusiasm for widely using real-world evidence, adaptive designs, and pragmatic trials in the regulatory setting, caution is warranted until large-scale empirical evaluations demonstrate their validity compared to more traditional trial designs.
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Affiliation(s)
- Joshua D Wallach
- Collaboration for Research Integrity and Transparency, Yale School of Medicine, New Haven, CT, USA
| | - Joseph S Ross
- Section of General Medicine, Department of Internal Medicine, Yale School of Medicine, New Haven, CT, USA
| | - Huseyin Naci
- LSE Health, Department of Health Policy, London School of Economics and Political Science, London, UK
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14
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Abstract
Adaptive clinical trials are an innovative trial design aimed at reducing resources, decreasing time to completion and number of patients exposed to inferior interventions, and improving the likelihood of detecting treatment effects. The last decade has seen an increasing use of adaptive designs, particularly in drug development. They frequently differ importantly from conventional clinical trials as they allow modifications to key trial design components during the trial, as data is being collected, using preplanned decision rules. Adaptive designs have increased likelihood of complexity and also potential bias, so it is important to understand the common types of adaptive designs. Many clinicians and investigators may be unfamiliar with the design considerations for adaptive designs. Given their complexities, adaptive trials require an understanding of design features and sources of bias. Herein, we introduce some common adaptive design elements and biases and specifically address response adaptive randomization, sample size reassessment, Bayesian methods for adaptive trials, seamless trials, and adaptive enrichment using real examples.
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Affiliation(s)
- Jay Jh Park
- Department of Medicine, University of British Columbia, Vancouver, BC, Canada
| | - Kristian Thorlund
- Department of Health Research Methods, Evidence, and Impact (HEI), McMaster University, Hamilton, ON, Canada.,The Bill and Melinda Gates Foundation, Seattle, WA, USA
| | - Edward J Mills
- Department of Health Research Methods, Evidence, and Impact (HEI), McMaster University, Hamilton, ON, Canada.,The Bill and Melinda Gates Foundation, Seattle, WA, USA
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15
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Pallmann P, Bedding AW, Choodari-Oskooei B, Dimairo M, Flight L, Hampson LV, Holmes J, Mander AP, Odondi L, Sydes MR, Villar SS, Wason JMS, Weir CJ, Wheeler GM, Yap C, Jaki T. Adaptive designs in clinical trials: why use them, and how to run and report them. BMC Med 2018; 16:29. [PMID: 29490655 PMCID: PMC5830330 DOI: 10.1186/s12916-018-1017-7] [Citation(s) in RCA: 349] [Impact Index Per Article: 58.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/10/2017] [Accepted: 01/30/2018] [Indexed: 12/11/2022] Open
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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Affiliation(s)
- Philip Pallmann
- Department of Mathematics & Statistics, Lancaster University, Lancaster, LA1 4YF UK
| | | | - Babak Choodari-Oskooei
- MRC Clinical Trials Unit at UCL, Institute of Clinical Trials and Methodology, University College London, London, UK
| | | | - Laura Flight
- Medical Statistics Group, University of Sheffield, Sheffield, UK
| | - Lisa V. Hampson
- Department of Mathematics & Statistics, Lancaster University, Lancaster, LA1 4YF UK
- Statistical Innovation Group, Advanced Analytics Centre, AstraZeneca, Cambridge, UK
| | - Jane Holmes
- Centre for Statistics in Medicine, University of Oxford, Oxford, UK
| | | | - Lang’o Odondi
- Centre for Statistics in Medicine, University of Oxford, Oxford, UK
| | - Matthew R. Sydes
- MRC Clinical Trials Unit at UCL, Institute of Clinical Trials and Methodology, University College London, London, UK
| | - Sofía S. Villar
- MRC Biostatistics Unit, University of Cambridge, Cambridge, UK
| | - James M. S. Wason
- MRC Biostatistics Unit, University of Cambridge, Cambridge, UK
- Institute of Health and Society, Newcastle University, Newcastle, UK
| | - Christopher J. Weir
- Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, UK
| | - Graham M. Wheeler
- MRC Biostatistics Unit, University of Cambridge, Cambridge, UK
- Cancer Research UK & UCL Cancer Trials Centre, University College London, London, UK
| | - Christina Yap
- Cancer Research UK Clinical Trials Unit, University of Birmingham, Birmingham, UK
| | - Thomas Jaki
- Department of Mathematics & Statistics, Lancaster University, Lancaster, LA1 4YF UK
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16
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Abstract
OBJECTIVES This review investigates characteristics of implemented adaptive design clinical trials and provides examples of regulatory experience with such trials. DESIGN Review 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. RESULTS 142 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. CONCLUSIONS Wider 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.
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Affiliation(s)
- Laura E Bothwell
- Program on Regulation, Therapeutics, and Law (PORTAL), Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - Jerry Avorn
- Program on Regulation, Therapeutics, and Law (PORTAL), Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - Nazleen F Khan
- Program on Regulation, Therapeutics, and Law (PORTAL), Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - Aaron S Kesselheim
- Program on Regulation, Therapeutics, and Law (PORTAL), Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts, USA
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17
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Bayesian methods in clinical trials with applications to medical devices. COMMUNICATIONS FOR STATISTICAL APPLICATIONS AND METHODS 2017. [DOI: 10.29220/csam.2017.24.6.561] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/02/2023]
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18
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Guetterman TC, Fetters MD, Mawocha S, Legocki LJ, Barsan WG, Lewis RJ, Berry DA, Meurer WJ. The life cycles of six multi-center adaptive clinical trials focused on neurological emergencies developed for the Advancing Regulatory Science initiative of the National Institutes of Health and US Food and Drug Administration: Case studies from the Adaptive Designs Accelerating Promising Treatments Into Trials Project. SAGE Open Med 2017; 5:2050312117736228. [PMID: 29085638 PMCID: PMC5648086 DOI: 10.1177/2050312117736228] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2017] [Accepted: 09/18/2017] [Indexed: 11/17/2022] Open
Abstract
OBJECTIVES Clinical trials are complicated, expensive, time-consuming, and frequently do not lead to discoveries that improve the health of patients with disease. Adaptive clinical trials have emerged as a methodology to provide more flexibility in design elements to better answer scientific questions regarding whether new treatments are efficacious. Limited observational data exist that describe the complex process of designing adaptive clinical trials. To address these issues, the Adaptive Designs Accelerating Promising Treatments Into Trials project developed six, tailored, flexible, adaptive, phase-III clinical trials for neurological emergencies, and investigators prospectively monitored and observed the processes. The objective of this work is to describe the adaptive design development process, the final design, and the current status of the adaptive trial designs that were developed. METHODS To observe and reflect upon the trial development process, we employed a rich, mixed methods evaluation that combined quantitative data from visual analog scale to assess attitudes about adaptive trials, along with in-depth qualitative data about the development process gathered from observations. RESULTS The Adaptive Designs Accelerating Promising Treatments Into Trials team developed six adaptive clinical trial designs. Across the six designs, 53 attitude surveys were completed at baseline and after the trial planning process completed. Compared to baseline, the participants believed significantly more strongly that the adaptive designs would be accepted by National Institutes of Health review panels and non-researcher clinicians. In addition, after the trial planning process, the participants more strongly believed that the adaptive design would meet the scientific and medical goals of the studies. CONCLUSION Introducing the adaptive design at early conceptualization proved critical to successful adoption and implementation of that trial. Involving key stakeholders from several scientific domains early in the process appears to be associated with improved attitudes towards adaptive designs over the life cycle of clinical trial development.
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Affiliation(s)
| | - Michael D Fetters
- Department of Family Medicine, University of Michigan, Ann Arbor, MI, USA
| | - Samkeliso Mawocha
- Department of Emergency Medicine, University of Michigan, Ann Arbor, MI, USA
| | - Laurie J Legocki
- Department of Family Medicine, University of Michigan, Ann Arbor, MI, USA
| | - William G Barsan
- Department of Emergency Medicine, University of Michigan, Ann Arbor, MI, USA
| | - Roger J Lewis
- Department of Emergency Medicine, Harbor-UCLA Medical Center, Los Angeles, CA, USA
| | - Donald A Berry
- Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - William J Meurer
- Department of Emergency Medicine, University of Michigan, Ann Arbor, MI, USA
- Department of Neurology, University of Michigan, Ann Arbor, MI, USA
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