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Grayling MJ, Wason JMS, Villar SS. Response adaptive intervention allocation in stepped-wedge cluster randomized trials. Stat Med 2022; 41:1081-1099. [PMID: 35064595 PMCID: PMC7612601 DOI: 10.1002/sim.9317] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2021] [Revised: 11/30/2021] [Accepted: 12/22/2021] [Indexed: 11/09/2022]
Abstract
BACKGROUND Stepped-wedge cluster randomized trial (SW-CRT) designs are often used when there is a desire to provide an intervention to all enrolled clusters, because of a belief that it will be effective. However, given there should be equipoise at trial commencement, there has been discussion around whether a pre-trial decision to provide the intervention to all clusters is appropriate. In pharmaceutical drug development, a solution to a similar desire to provide more patients with an effective treatment is to use a response adaptive (RA) design. METHODS We introduce a way in which RA design could be incorporated in an SW-CRT, permitting modification of the intervention allocation during the trial. The proposed framework explicitly permits a balance to be sought between power and patient benefit considerations. A simulation study evaluates the methodology. RESULTS In one scenario, for one particular RA design, the proportion of cluster-periods spent in the intervention condition was observed to increase from 32.2% to 67.9% as the intervention effect was increased. A cost of this was a 6.2% power drop compared to a design that maximized power by fixing the proportion of time in the intervention condition at 45.0%, regardless of the intervention effect. CONCLUSIONS An RA approach may be most applicable to settings for which the intervention has substantial individual or societal benefit considerations, potentially in combination with notable safety concerns. In such a setting, the proposed methodology may routinely provide the desired adaptability of the roll-out speed, with only a small cost to the study's power.
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Affiliation(s)
- Michael J. Grayling
- Population Health Sciences InstituteNewcastle UniversityNewcastle upon TyneUK
| | - James M. S. Wason
- Population Health Sciences InstituteNewcastle UniversityNewcastle upon TyneUK
| | - Sofía S. Villar
- MRC Biostatistics Unit, School of Clinical MedicineUniversity of CambridgeCambridgeUK
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2
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Johnson R, Jackson C, Presanis A, Villar SS, De Angelis D. Quantifying Efficiency Gains of Innovative Designs of Two-Arm Vaccine Trials for COVID-19 Using an Epidemic Simulation Model. Stat Biopharm Res 2022; 14:33-41. [PMID: 35096276 PMCID: PMC7612285 DOI: 10.1080/19466315.2021.1939774] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2020] [Revised: 04/18/2021] [Accepted: 05/25/2021] [Indexed: 12/24/2022]
Abstract
Clinical trials of a vaccine during an epidemic face particular challenges, such as the pressure to identify an effective vaccine quickly to control the epidemic, and the effect that time-space-varying infection incidence has on the power of a trial. We illustrate how the operating characteristics of different trial design elements maybe evaluated using a network epidemic and trial simulation model, based on COVID-19 and individually randomized two-arm trials with a binary outcome. We show that "ring" recruitment strategies, prioritizing participants at an imminent risk of infection, can result in substantial improvement in terms of power in the model we present. In addition, we introduce a novel method to make more efficient use of the data from the earliest cases of infection observed in the trial, whose infection may have been too early to be vaccine-preventable. Finally, we compare several methods of response-adaptive randomization (RAR), discussing their advantages and disadvantages in the context of our model and identifying particular adaptation strategies that preserve power and estimation properties, while slightly reducing the number of infections, given an effective vaccine.
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Affiliation(s)
- Rob Johnson
- Imperial College London, Department of Infectious Disease Epidemiology, London, UK
| | - Chris Jackson
- MRC Biostatistics Unit, University of Cambridge, Cambridge, UK
| | - Anne Presanis
- MRC Biostatistics Unit, University of Cambridge, Cambridge, UK
| | - Sofia S. Villar
- MRC Biostatistics Unit, University of Cambridge, Cambridge, UK
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3
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Madewell ZJ, Dean NE, Berlin JA, Coplan PM, Davis KJ, Struchiner CJ, Halloran ME. Challenges of evaluating and modelling vaccination in emerging infectious diseases. Epidemics 2021; 37:100506. [PMID: 34628108 PMCID: PMC8491997 DOI: 10.1016/j.epidem.2021.100506] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2021] [Revised: 08/25/2021] [Accepted: 10/04/2021] [Indexed: 12/17/2022] Open
Abstract
Outbreaks of emerging pathogens pose unique methodological and practical challenges for the design, implementation, and evaluation of vaccine efficacy trials. Lessons learned from COVID-19 highlight the need for innovative and flexible study design and application to quickly identify promising candidate vaccines. Trial design strategies should be tailored to the dynamics of the specific pathogen, location of the outbreak, and vaccine prototypes, within the regional socioeconomic constraints. Mathematical and statistical models can assist investigators in designing infectious disease clinical trials. We introduce key challenges for planning, evaluating, and modelling vaccine efficacy trials for emerging pathogens.
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Affiliation(s)
- Zachary J Madewell
- Department of Biostatistics, University of Florida, Gainesville, FL, USA.
| | - Natalie E Dean
- Department of Biostatistics, University of Florida, Gainesville, FL, USA
| | - Jesse A Berlin
- Global Epidemiology, Johnson & Johnson, Titusville, NJ, USA
| | - Paul M Coplan
- Medical Device Epidemiology and Real World Data Sciences, Johnson & Johnson, New Brunswick, NJ, USA; Department of Epidemiology and Biostatistics, Perelman School of Medicine, University of Pennsylvania, PA, USA
| | | | | | - M Elizabeth Halloran
- Fred Hutchinson Cancer Research Center, Seattle, WA, USA; Department of Biostatistics, University of Washington, Seattle, WA, USA
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4
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Smith MJ, Emanuel EJ, Thomé B, Upshur RE. Ethical conditions for accelerating COVID-19 vaccine research. Wellcome Open Res 2020. [DOI: 10.12688/wellcomeopenres.16361.1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Abstract
There is a dire need to produce a safe and effective coronavirus disease 2019 (COVID-19) vaccine as quickly as possible to avert an enormous burden of morbidity and mortality. This need for speed has thus far resulted in significant deviations from standard approaches to vaccine research and regulatory approval. Yet, pandemics do not obviate the need for rigorous scientific evaluation of potential interventions and adherence to universal ethical standards. Consequently, steps taken to accelerate clinical research in the context of the current pandemic require an explicit ethical justification, particularly if we expect public trust in the vaccine. We argue that accelerating COVID-19 vaccine research can be ethically justified, but only if social value, scientific validity, and a favourable risk-benefit ratio can be maintained or enhanced when doing so.
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Lu L, Li F, Wen H, Ge S, Zeng J, Luo W, Wang L, Tang C, Xu N. An evidence mapping and analysis of registered COVID-19 clinical trials in China. BMC Med 2020; 18:167. [PMID: 32493331 PMCID: PMC7268588 DOI: 10.1186/s12916-020-01612-y] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/02/2020] [Accepted: 04/30/2020] [Indexed: 01/10/2023] Open
Abstract
BACKGROUND This article aims to summarize the key characteristics of registered trials of 2019 novel coronavirus (COVID-19), in terms of their spatial and temporal distributions, types of design and interventions, and patient characteristics among others. METHODS A comprehensive search of the registered COVID-19 trials has been performed on platforms including ClinicalTrials.gov, WHO International Clinical Trials Registry Platform (WHO ICTRP), Chinese Clinical Trials Registry (CHiCTR), Australian Clinical Trials Registry, Britain's National Research Register (BNRR), Current Control Trials (CCT), and Glaxo Smith Kline Register. Trials registered at the first 8 weeks of the COVID-19 outbreak are included, without language restrictions. For each study, the registration information, study design, and administrator information are collected and summarized. RESULTS A total of 220 registered trials were evaluated as of February 27, 2020. Hospital-initiated trials were the majority and account for 80% of the sample. Among the trials, pilot studies and phase 4 trials are more common and represent 35% and 19.1% of the sample, respectively. The median sample size of the registered trials is 100, with interquartile range 60-240. Further, 45.9% of the trials mentioned information on a data monitoring committee. 54.5% of the trials did not specify the disease severity among patients they intend to recruit. Four types of interventions are most common in the experimental groups across the registered studies: antiviral drugs, Traditional Chinese Medicine (TCM), biological agents, and hormone drugs. Among them, the TCM and biological agents are frequently used in pilot study and correspond to a variety of primary endpoints. In contrast, trials with antiviral drugs have more targeted primary outcomes such as "COVID-19 nucleic acid test" and "28-day mortality." CONCLUSIONS We provide an evidence mapping and analysis of registered COVID-19 clinical trials in China. In particular, it is critical for ongoing and future studies to refine their research hypothesis and better identify their intervention therapies and the corresponding primary outcomes. It is also imperative for multiple public health divisions and research institutions to work together for integrative clinical data capture and sharing, with a common objective of improving future studies that evaluate COVID-19 interventions.
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Affiliation(s)
- Liming Lu
- Clinical Research and Data Center, South China Research Center for Acupuncture and Moxibustion, Medical College of Acu-Moxi and Rehabilitation, Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Fan Li
- Department of Biostatistics, Yale School of Public Health, New Haven, CT, USA.,Center for Methods in Implementation and Prevention Science, Yale School of Public Health, New Haven, CT, USA
| | - Hao Wen
- Clinical Research and Data Center, South China Research Center for Acupuncture and Moxibustion, Medical College of Acu-Moxi and Rehabilitation, Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Shuqi Ge
- Clinical Research and Data Center, South China Research Center for Acupuncture and Moxibustion, Medical College of Acu-Moxi and Rehabilitation, Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Jingchun Zeng
- Department of Acupuncture, First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Wen Luo
- Clinical Research and Data Center, South China Research Center for Acupuncture and Moxibustion, Medical College of Acu-Moxi and Rehabilitation, Guangzhou University of Chinese Medicine, Guangzhou, China.,School of Medical Information Engineering, Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Lai Wang
- Clinical Research and Data Center, South China Research Center for Acupuncture and Moxibustion, Medical College of Acu-Moxi and Rehabilitation, Guangzhou University of Chinese Medicine, Guangzhou, China.,School of Medical Information Engineering, Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Chunzhi Tang
- Clinical Research and Data Center, South China Research Center for Acupuncture and Moxibustion, Medical College of Acu-Moxi and Rehabilitation, Guangzhou University of Chinese Medicine, Guangzhou, China.
| | - Nenggui Xu
- Clinical Research and Data Center, South China Research Center for Acupuncture and Moxibustion, Medical College of Acu-Moxi and Rehabilitation, Guangzhou University of Chinese Medicine, Guangzhou, China.
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Abstract
The conduct of clinical trials during the West Africa Ebola outbreak in 2014 highlighted many ethical challenges. How these challenges were addressed, what clinical studies were conducted during that outbreak, and the lessons learned for dealing with future outbreaks were the subject of a National Academy of Medicine committee report titled Integrating Clinical Research into Epidemic Response: The Ebola Experience. This report suggested improvements for research during subsequent emerging or re-emerging outbreaks and is summarized in this review. We also discuss the current Ebola outbreak in the Democratic Republic of the Congo and highlight how the dialogue has changed and how successful clinical trials have been implemented. We conclude with a description of productive efforts to include pregnant women and children in therapeutic and vaccine trials during outbreaks that are currently ongoing.
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Affiliation(s)
- Kathryn M Edwards
- Division of Pediatric Infectious Diseases, Vanderbilt University School of Medicine, Nashville, Tennessee 37232, USA;
| | - Sonali Kochhar
- Global Healthcare Consulting, New Delhi 110024, India.,Department of Global Health, University of Washington, Seattle, Washington 98104, USA
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Dean NE, Gsell PS, Brookmeyer R, De Gruttola V, Donnelly CA, Halloran ME, Jasseh M, Nason M, Riveros X, Watson CH, Henao-Restrepo AM, Longini IM. Design of vaccine efficacy trials during public health emergencies. Sci Transl Med 2019; 11:eaat0360. [PMID: 31270270 PMCID: PMC6613811 DOI: 10.1126/scitranslmed.aat0360] [Citation(s) in RCA: 35] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2018] [Accepted: 12/13/2018] [Indexed: 01/05/2023]
Abstract
Public health emergencies, such as an Ebola disease outbreak, provide a complex and challenging environment for the evaluation of candidate vaccines. Here, we outline the need for flexible and responsive vaccine trial designs to be used in public health emergencies, and we summarize recommendations for their use in this setting.
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Affiliation(s)
- Natalie E Dean
- Department of Biostatistics, University of Florida, Gainesville, FL, USA.
| | | | - Ron Brookmeyer
- Department of Biostatistics, University of California, Los Angeles, Los Angeles, CA, USA
| | | | - Christl A Donnelly
- Department of Statistics, University of Oxford, Oxford, UK
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London, UK
| | - M Elizabeth Halloran
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - Momodou Jasseh
- Medical Research Council, The Gambia at London School of Hygiene and Tropical Medicine, Fajara, The Gambia
| | - Martha Nason
- Biostatistics Research Branch, National Institute of Allergy and Infectious Diseases, Rockville, MD, USA
| | | | - Conall H Watson
- Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, UK
| | | | - Ira M Longini
- Department of Biostatistics, University of Florida, Gainesville, FL, USA.
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8
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Abstract
In a Policy Forum, Marc Lipsitch and colleagues discuss trial design issues in infectious disease outbreaks.
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Affiliation(s)
- Rebecca Kahn
- Center for Communicable Disease Dynamics, Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, United States of America
| | - Annette Rid
- Department of Global Health & Social Medicine, King’s College London, London, United Kingdom
| | - Peter G. Smith
- MRC Tropical Epidemiology Group, London School of Hygiene & Tropical Medicine, London, United Kingdom
| | - Nir Eyal
- Department of Global Health and Population, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, United States of America
| | - Marc Lipsitch
- Center for Communicable Disease Dynamics, Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, United States of America
- Department of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, United States of America
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