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Fleming TR, Wittes J, Fiuzat M, Bristow MR, Rockhold FW, Connor JT, Saville BR, Claggett B, Cavagna I, Abraham WT, Cook TD, Lindenfeld J, O'Connor C, DeMets DL. Training the Next Generation of Data Monitoring Committee Members: An Initiative of the Heart Failure Collaboratory. JACC. HEART FAILURE 2024:S2213-1779(24)00180-X. [PMID: 38530701 DOI: 10.1016/j.jchf.2024.02.016] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/22/2023] [Revised: 02/14/2024] [Accepted: 02/21/2024] [Indexed: 03/28/2024]
Abstract
Clinical trials are vital for assessing therapeutic interventions. The associated data monitoring committees (DMCs) safeguard patient interests and enhance trial integrity, thus promoting timely, reliable evaluations of those interventions. We face an urgent need to recruit and train new DMC members. The Heart Failure Collaboratory (HFC), a multidisciplinary public-private consortium of academics, trialists, patients, industry representatives, and government agencies, is working to improve the clinical trial ecosystem. The HFC aims to improve clinical trial efficiency and quality by standardizing concepts, and to help meet the demand for experienced individuals on DMCs by creating a standardized approach to training new members. This paper discusses the HFC's training workshop, and an apprenticeship model for new DMC members. It describes opportunities and challenges DMCs face, along with common myths and best practices learned through previous experiences, with an emphasis on data confidentiality and need for quality independent statistical reporting groups.
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Affiliation(s)
- Thomas R Fleming
- Department of Biostatistics, University of Washington, Seattle, Washington, USA
| | | | - Mona Fiuzat
- Division of Cardiology, Duke University, Durham, North Carolina, USA.
| | - Michael R Bristow
- Division of Cardiology, University of Colorado Anschutz Medical Campus, Aurora, Colorado, USA
| | - Frank W Rockhold
- Department of Biostatistics and Bioinformatics, Duke University School of Medicine and Duke Clinical Research Institute, Durham, North Carolina, USA
| | - Jason T Connor
- ConfluenceStat LLC, Cooper City, Florida, USA; University of Central Florida College of Medicine, Orlando, Florida, USA
| | - Benjamin R Saville
- Adaptix Trials, LLC, Austin, Texas, USA; Vanderbilt University Department of Biostatistics (adjoint faculty), Nashville, Tennessee, USA
| | - Brian Claggett
- Division of Cardiovascular Medicine, Brigham and Women's Hospital, Boston, Massachusetts, USA
| | | | - William T Abraham
- Division of Cardiovascular Medicine and the Davis Heart and Lung Research Institute, The Ohio State University College of Medicine/Ohio State University Wexner Medical Center, Columbus, Ohio, USA
| | - Thomas D Cook
- Biostatistics and Medical Informatics, University of Wisconsin, Madison, Wisconsin, USA
| | - JoAnn Lindenfeld
- Division of Cardiovascular Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | | | - David L DeMets
- Department of Biostatistics and Medical Informatics, University of Wisconsin, Madison, Wisconsin, USA
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2
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Sammy A, Baba A, Klassen TP, Moher D, Offringa M. A Decade of Efforts to Add Value to Child Health Research Practices. J Pediatr 2024; 265:113840. [PMID: 38000771 DOI: 10.1016/j.jpeds.2023.113840] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/09/2023] [Revised: 10/25/2023] [Accepted: 11/15/2023] [Indexed: 11/26/2023]
Abstract
OBJECTIVE To identify practices that add value to improve the design, conduct, and reporting of child health research and reduce research waste. STUDY DESIGN In order to categorize the contributions of members of Standards for Research (StaR) in Child Health network, we developed a novel Child Health Improving Research Practices (CHIRP) framework comprised of 5 domains meant to counteract avoidable child health research waste and improve quality: 1) address research questions relevant to children, their families, clinicians, and researchers; 2) apply appropriate research design, conduct and analysis; 3) ensure efficient research oversight and regulation; 4) Provide accessible research protocols and reports; and 5) develop unbiased and usable research reports, including 17 responsible research practice recommendations. All child health research relevant publications by the 48 original StaR standards' authors over the last decade were identified, and main topic areas were categorized using this framework. RESULTS A total of 247 publications were included in the final sample: 100 publications (41%) in domain 1 (3 recommendations), 77 publications (31%) in domain 2 (3), 35 publications (14%) in domain 3 (4), 20 publications (8%) in domain 4 (4), and 15 publications (6%) in domain 5 (3). We identified readily implementable "responsible" research practices to counter child health research waste and improve quality, especially in the areas of patients and families' engagement throughout the research process, developing Core Outcome Sets, and addressing ethics and regulatory oversight issues. CONCLUSION While most of the practices are readily implementable, increased awareness of methodological issues and wider guideline uptake is needed to improve child health research. The CHIRP Framework can be used to guide responsible research practices that add value to child health research.
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Affiliation(s)
- Adrian Sammy
- Child Health Evaluative Sciences, The Hospital for Sick Children Research Institute, Toronto, Ontario, Canada
| | - Ami Baba
- Child Health Evaluative Sciences, The Hospital for Sick Children Research Institute, Toronto, Ontario, Canada
| | - Terry P Klassen
- Department of Pediatrics and Child Health, Children's Hospital Research Institute of Manitoba, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, Manitoba, Canada
| | - David Moher
- Centre for Journalology, Clinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, Ontario, Canada; School of Epidemiology and Public Health, Faculty of Medicine, University of Ottawa, Ottawa, Ontario, Canada
| | - Martin Offringa
- Child Health Evaluative Sciences, The Hospital for Sick Children Research Institute, Toronto, Ontario, Canada; Division of Neonatology, The Hospital for Sick Children, Toronto, Ontario, Canada; Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, Ontario, Canada.
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3
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Zahrieh D, Croghan IT, Inselman JW, Mandrekar SJ. Guidelines for Data and Safety Monitoring in Pragmatic Randomized Clinical Trials Using Case Studies. Mayo Clin Proc 2023; 98:1712-1726. [PMID: 37923529 PMCID: PMC10807861 DOI: 10.1016/j.mayocp.2023.02.019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/18/2022] [Revised: 01/18/2023] [Accepted: 02/23/2023] [Indexed: 11/07/2023]
Abstract
Pragmatic randomized clinical trials (pRCTs) have a unique set of considerations for data and safety monitoring. Because of their unconventional trial designs coupled with collection of multilevel data and implementation outcomes in real-world settings, thoughtful consideration is needed on the presentation of the trial design and accruing data to facilitate review and decision-making by the trial's data and safety monitoring board (DSMB). To our knowledge, there is limited information available in practical guidelines for generalists and medical general practitioners on what to monitor and to report to the DSMB during the conduct of pRCTs and what the DSMB should focus on in its review of reports. This article discusses these matters in the context of 3 case studies focusing on a set of critical data and safety monitoring questions that would be of interest to the generalist conducting pRCTs. In considering these questions, we provide tabular and graphical illustrations of how data can be presented to the DSMB while drawing attention to those areas that the DSMB should focus on in its review of the trial. The strategies and viewpoints discussed herein provide practical guidelines and can serve as a resource for the generalist conducting pRCTs.
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Affiliation(s)
- David Zahrieh
- Department of Data Sciences and Development Strategy, Ultragenyx Pharmaceutical, Novato, CA; Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN.
| | - Ivana T Croghan
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN; Division of General Internal Medicine, Mayo Clinic, Rochester, MN
| | - Jonathan W Inselman
- Robert D. and Patricia E. Kern Center for the Science of Healthcare Delivery, Mayo Clinic, Rochester, MN
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Hamilton F, Arnold D, Lilford R. Bad research is not all bad. Trials 2023; 24:680. [PMID: 37864198 PMCID: PMC10588138 DOI: 10.1186/s13063-023-07706-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2023] [Accepted: 10/04/2023] [Indexed: 10/22/2023] Open
Abstract
In this commentary, we discuss a recent article in Trials that raised concerns about the number of poorly performed randomised trials in the medical literature and discuss the trials literature more widely. Although we all aim for higher methodological standards in trials, we argue that (i) the idea that 'most randomised trials are bad', which the recent article concludes is an overly simplistic representation of the situation, and (ii) the suggestion that an increased focus on methodological review during trial development (e.g. ethical boards performing some assessment of the methodologists on a trial), while well meaning, may have negative unintended consequences. We therefore propose that (a) trials should be assessed on their merits and weaknesses, including an assessment of risk of bias but placing that in a wider context; (b) we should recognise that although the methodological conduct of trials is of utmost importance, interventions that aim to improve this could have unintended consequences-such as bureaucracy-that have an overall negative effect; and (c) we should therefore generate an evidence base for policy interventions to improve conduct of trials rather than applying arbitrary rules.
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Affiliation(s)
- Fergus Hamilton
- Infection Science, Southmead Hospital, North Bristol NHS Trust, Bristol, BS10 5NB, UK.
- MRC Integrative Epidemiology Unit, Oakfield House, University of Bristol, Bristol, BS10 5NB, UK.
| | - David Arnold
- MRC Integrative Epidemiology Unit, Oakfield House, University of Bristol, Bristol, BS10 5NB, UK
- Academic Respiratory Unit, Southmead Hospital, North Bristol NHS Trust, Bristol, BS10 5NB, UK
| | - Richard Lilford
- NIHR ARC West Midlands, Institute of Applied Health Research, College of Medical and Dental Sciences, University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK
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5
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Thakur B, Ayers GD, Atem F, DeClercq JJ, Jain NB. Statistical and Methodological Considerations for Randomized Controlled Trial Design in Physical Medicine and Rehabilitation. Am J Phys Med Rehabil 2023; 102:855-860. [PMID: 36882301 PMCID: PMC10471787 DOI: 10.1097/phm.0000000000002225] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/09/2023]
Abstract
ABSTRACT Well-designed randomized controlled clinical trials assessing treatments in the field of physical medicine and rehabilitation are essential for evidence-based patient care. However, there are challenges unique to clinical trials in physical medicine and rehabilitation due to complex health interventions in this field. We highlight routinely encountered empirical challenges and provide evidence-based recommendations on statistical and methodological approaches for the design and conduct of randomized controlled trials. Some of the issues addressed include challenges with blinding treatment groups in a rehabilitation setting, heterogeneity in treatment therapy, heterogeneity of treatment effects, uniformity in patient-reported outcome measures, and effect on power with varying scales of information. Furthermore, we discuss challenges with estimation of sample size and power, adaption to poor compliance with treatment and missing outcomes, and preferred statistical approaches for longitudinal data analysis. TO CLAIM CME CREDITS Complete the self-assessment activity and evaluation online at http://www.physiatry.org/JournalCME. CME OBJECTIVES Upon completion of this article, the reader should be able to: (1) Appraise the complexities of interventions in physical medicine and rehabilitation and how these challenges impact the conduct of clinical trials; (2) Develop an analytical strategy for poor treatment compliance and missing outcomes that can compromise the causal effect sought in a randomized clinical trial; and (3) Recognize the role of a data and safety monitoring board in a clinical trial. LEVEL Advanced. ACCREDITATION The Association of Academic Physiatrists is accredited by the Accreditation Council for Continuing Medical Education to provide continuing medical education for physicians.The Association of Academic Physiatrists designates this Journal-based CME activity for a maximum of 1.0 AMA PRA Category 1 Credit(s) ™. Physicians should only claim credit commensurate with the extent of their participation in the activity.
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Affiliation(s)
- Bhaskar Thakur
- From the Department of Physical Medicine and Rehabilitation, Family and Community Medicine, and Emergency Medicine, University of Texas Southwestern Medical Center, Dallas, Texas (BT); Center for Quantitative Sciences, Department of Biostatistics, Vanderbilt School of Medicine, Nashville, Tennessee (GDA); Department of Biostatistics and Data Science, University of Texas Health Science Center-Houston, Dallas, Texas (FA); Department of Biostatistics, Vanderbilt School of Medicine, Nashville, Tennessee (JD); Department of Physical Medicine and Rehabilitation, and Orthopedics, University of Texas Southwestern, Dallas, Texas (NBJ); and Department of Physical Medicine and Rehabilitation, Vanderbilt University Medical Center, Nashville, Tennessee (NBJ)
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Farah E, Kenney M, Kica A, Haddad P, Stewart DJ, Bradford JP. Beyond Participation: Evaluating the Role of Patients in Designing Oncology Clinical Trials. Curr Oncol 2023; 30:8310-8327. [PMID: 37754518 PMCID: PMC10527717 DOI: 10.3390/curroncol30090603] [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] [Received: 08/14/2023] [Revised: 09/05/2023] [Accepted: 09/06/2023] [Indexed: 09/28/2023] Open
Abstract
Historically, subject matter experts and healthcare professionals have played a pivotal role in driving oncology clinical trials. Although patients have been key participants, their deliberate and active contribution to the design and decision-making process has been limited. This scoping review aimed to examine the existing literature to scope the extent of active patient engagement in the design of oncology clinical trials and its corresponding influence on trial outcomes. We conducted a systematic search using two databases, namely MEDLINE (Ovid) and EMBASE, to identify relevant studies exploring patient engagement in cancer-related clinical research design. We identified seven studies that met the eligibility criteria. The studies highlighted the benefits of active patient involvement, such as improved recruitment strategies, and the attainment of more patient-centered trial outcomes. The influence of patient involvement varied from tangible developments like patient-friendly resources to indirect impacts like improved patient experiences and potentially higher adherence to trial intervention. The future of clinical trials should prioritize patients' values and perspectives, with regulatory bodies fostering these practices through clear guidelines. As the concept of patient centricity takes root in oncology research, the involvement of patients should evolve beyond mere participation.
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Affiliation(s)
- Eliya Farah
- Life-Saving Therapies Network, 173 Heath Street, Ottawa, ON K1H 8L6, Canada
| | - Matthew Kenney
- Life-Saving Therapies Network, 173 Heath Street, Ottawa, ON K1H 8L6, Canada
| | - Anris Kica
- Life-Saving Therapies Network, 173 Heath Street, Ottawa, ON K1H 8L6, Canada
| | - Paul Haddad
- Life-Saving Therapies Network, 173 Heath Street, Ottawa, ON K1H 8L6, Canada
| | - David J. Stewart
- Department of Medicine, Faculty of Medicine, The Ottawa Hospital, University of Ottawa, 501 Smyth Rd., Ottawa, ON K1H 8L6, Canada;
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Bunning BJ, Hedlin H, Chen JH, Ciolino JD, Ferstad JO, Fox E, Garcia A, Go A, Johari R, Lee J, Maahs DM, Mahaffey KW, Opsahl-Ong K, Perez M, Rochford K, Scheinker D, Spratt H, Turakhia MP, Desai M. The evolving role of data & safety monitoring boards for real-world clinical trials. J Clin Transl Sci 2023; 7:e179. [PMID: 37745930 PMCID: PMC10514684 DOI: 10.1017/cts.2023.582] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2023] [Revised: 06/20/2023] [Accepted: 06/24/2023] [Indexed: 09/26/2023] Open
Abstract
Introduction Clinical trials provide the "gold standard" evidence for advancing the practice of medicine, even as they evolve to integrate real-world data sources. Modern clinical trials are increasingly incorporating real-world data sources - data not intended for research and often collected in free-living contexts. We refer to trials that incorporate real-world data sources as real-world trials. Such trials may have the potential to enhance the generalizability of findings, facilitate pragmatic study designs, and evaluate real-world effectiveness. However, key differences in the design, conduct, and implementation of real-world vs traditional trials have ramifications in data management that can threaten their desired rigor. Methods Three examples of real-world trials that leverage different types of data sources - wearables, medical devices, and electronic health records are described. Key insights applicable to all three trials in their relationship to Data and Safety Monitoring Boards (DSMBs) are derived. Results Insight and recommendations are given on four topic areas: A. Charge of the DSMB; B. Composition of the DSMB; C. Pre-launch Activities; and D. Post-launch Activities. We recommend stronger and additional focus on data integrity. Conclusions Clinical trials can benefit from incorporating real-world data sources, potentially increasing the generalizability of findings and overall trial scale and efficiency. The data, however, present a level of informatic complexity that relies heavily on a robust data science infrastructure. The nature of monitoring the data and safety must evolve to adapt to new trial scenarios to protect the rigor of clinical trials.
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Affiliation(s)
- Bryan J. Bunning
- Quantitative Sciences Unit, Stanford University, Stanford, CA, USA
- Department of Biomedical Data Science, Stanford University, Stanford, CA, USA
| | - Haley Hedlin
- Quantitative Sciences Unit, Stanford University, Stanford, CA, USA
| | - Jonathan H. Chen
- Stanford Center for Biomedical Informatics Research, Stanford University, Stanford, CA, USA
| | - Jody D. Ciolino
- Department of Preventative Medicine – Biostatistics, Northwestern University, Chicago, IL, USA
| | | | - Emily Fox
- Department of Statistics, Stanford University, Stanford, CA, USA
- Kaiser Permanente Northern California Division of Research, Kaiser Permanente, Oakland, CA, USA
| | - Ariadna Garcia
- Quantitative Sciences Unit, Stanford University, Stanford, CA, USA
| | - Alan Go
- Department of Computer Science, Stanford University, Stanford, CA, USA
| | - Ramesh Johari
- Department of Management Science and Engineering, Stanford University, Stanford, CA, USA
| | - Justin Lee
- Quantitative Sciences Unit, Stanford University, Stanford, CA, USA
| | - David M. Maahs
- Department of Pediatrics, Stanford Medicine Children’s Hospital, Stanford, CA, USA
| | - Kenneth W. Mahaffey
- Stanford Center for Clinical Research, Stanford University, Stanford, CA, USA
| | - Krista Opsahl-Ong
- Department of Pediatrics, Stanford Medicine Children’s Hospital, Stanford, CA, USA
| | - Marco Perez
- Department of Medicine, Cardiovascular Medicine, Stanford Medicine, Stanford, CA, USA
| | - Kaylin Rochford
- Department of Management Science and Engineering, Stanford University, Stanford, CA, USA
| | - David Scheinker
- Systems Design and Collaborative Research, Stanford Medicine Children’s Hospital, Stanford, CA, USA
| | - Heidi Spratt
- Department of Preventative Medicine & Community Health, University of Texas Medical Branch, Galveston, TX, USA
| | - Mintu P. Turakhia
- Stanford Center for Clinical Research, Stanford University, Stanford, CA, USA
| | - Manisha Desai
- Quantitative Sciences Unit, Stanford University, Stanford, CA, USA
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DeMets DL, Zarin DA, Rockhold F, Ellenberg SS, Fleming T, Wittes J. Bringing data monitoring committee charters into the sunlight. Clin Trials 2023; 20:447-451. [PMID: 37231737 DOI: 10.1177/17407745231169499] [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: 05/27/2023]
Abstract
Clinical trials investigating novel or high risk interventions, or studying vulnerable participants, often use a data monitoring committee to oversee the progress of the trial. The data monitoring committee serves both an ethical and a scientific function, by protecting the interests of trial participants while ensuring the integrity of the trial results. A data monitoring committee charter, which typically describes the procedures by which data monitoring committees operate, contains details about the data monitoring committee's organizational structure, membership, meeting frequency, sequential monitoring guidelines, and the overall contents of data monitoring committee reports for interim review. These charters, however, are generally not reviewed by outside entities and are rarely publicly available. The result is that a key component of trial oversight remains in the dark. We recommend that ClinicalTrials.gov modify its system to allow uploading of data monitoring committee charters, as is already possible for other important study documents and that clinical trialists take advantage of this opportunity to voluntarily upload the data monitoring committee charter for trials that have one. The resulting cache of publicly available data monitoring committee charters should provide important insights for those interested in a particular trial, as well as for meta-researchers who wish to understand and potentially improve how this important component of trial oversight is actually being applied.
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Affiliation(s)
| | - Deborah A Zarin
- The MRCT Center of Brigham and Women's Hospital and Harvard, Cambridge, MA, USA
| | - Frank Rockhold
- Duke Clinical Research Institute/Duke University, Durham, NC, USA
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Wittes J, Fleming T, DeMets D, Ellenberg S, Gerstein H, Pfeffer M, Rockhold F, Yusuf S, Hennekens C. The Data Monitoring Committee: A Collective or a Collection? Ther Innov Regul Sci 2023; 57:653-655. [PMID: 37069466 DOI: 10.1007/s43441-023-00520-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2023] [Accepted: 03/30/2023] [Indexed: 04/19/2023]
Abstract
In this commentary, we urge that a Data Monitoring Committee (DMC) should operate as a collective, that is, as a unitary whole. In so doing, its recommendations should emerge through a consensus development process, not through a vote of the members. The summary notes of its closed session, that is, its minutes, should report the recommendations of the DMC and, if necessary, the justification for those recommendations; it should not attribute opinions to individual members. Importantly, the proceedings of the DMC meetings should not be electronically recorded.
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Affiliation(s)
| | | | - David DeMets
- University of Wisconsin-Madison, Madison, WI, USA
| | | | - Hertzel Gerstein
- Population Health Research Institute and Department of Medicine, McMaster University and Hamilton Health Sciences, Hamilton, Canada
| | - Marc Pfeffer
- Harvard Medical School and Brigham and Women's Hospital, Boston, MA, USA
| | - Frank Rockhold
- Duke University Medical Center and The Duke Clinical Research Institute, Durham, NC, USA
| | - Salim Yusuf
- Population Health Research Institute, McMaster University and Hamilton Health Sciences, Hamilton, Canada
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10
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Ciolino JD, Kaizer AM, Bonner LB. Guidance on interim analysis methods in clinical trials. J Clin Transl Sci 2023; 7:e124. [PMID: 37313374 PMCID: PMC10260346 DOI: 10.1017/cts.2023.552] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2023] [Revised: 05/08/2023] [Accepted: 05/09/2023] [Indexed: 06/15/2023] Open
Abstract
Interim analyses in clinical trials can take on a multitude of forms. They are often used to guide Data and Safety Monitoring Board (DSMB) recommendations to study teams regarding recruitment targets for large, later-phase clinical trials. As collaborative biostatisticians working and teaching in multiple fields of research and across a broad array of trial phases, we note the large heterogeneity and confusion surrounding interim analyses in clinical trials. Thus, in this paper, we aim to provide a general overview and guidance on interim analyses for a nonstatistical audience. We explain each of the following types of interim analyses: efficacy, futility, safety, and sample size re-estimation, and we provide the reader with reasoning, examples, and implications for each. We emphasize that while the types of interim analyses employed may differ depending on the nature of the study, we would always recommend prespecification of the interim analytic plan to the extent possible with risk mitigation and trial integrity remaining a priority. Finally, we posit that interim analyses should be used as tools to help the DSMB make informed decisions in the context of the overarching study. They should generally not be deemed binding, and they should not be reviewed in isolation.
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Affiliation(s)
- Jody D. Ciolino
- Department of Preventive Medicine (Biostatistics), Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
| | - Alexander M. Kaizer
- Department of Biostatistics & Informatics, Colorado School of Public Health, Aurora, Colorado, USA
| | - Lauren Balmert Bonner
- Department of Preventive Medicine (Biostatistics), Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
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11
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Vandemeulebroecke M, Baillie M, Mirshani A, Lesaffre E. DMC reports in the 21st century: towards better tools for decision-making. Trials 2023; 24:289. [PMID: 37085883 PMCID: PMC10120491 DOI: 10.1186/s13063-023-07290-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2022] [Accepted: 04/03/2023] [Indexed: 04/23/2023] Open
Abstract
Data Monitoring Committees (DMCs) have the important task to protect the safety of current and future patients during the conduct of a clinical study. Unfortunately, their work is often made difficult by voluminous DMC reports that are poorly structured and difficult to digest. In this article, we suggest improved solutions. Starting from a principled approach and building upon previous proposals, we offer concrete and easily understood displays, including related computer code. While leveraging modern tools, the most important is that these displays support the DMC's workflow in answering the relevant questions of interest. We hope that the adoption of these proposals can ease the task of DMCs, and importantly, lead to better decision-making for the benefit of patients.
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Evans SR, Zeng L, Dai W. The Data and Safety Monitoring Board: The Toughest Job in Clinical Trials. NEJM EVIDENCE 2023; 2:EVIDctw2200220. [PMID: 38320039 DOI: 10.1056/evidctw2200220] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/08/2024]
Abstract
The DSMB: The Toughest Job in Clinical TrialsIn this review article, the authors discuss methods that DSMBs can use to compare the absolute and relative risks of benefits and adverse effects between trial interventions and illustrate how the DSMB can use this approach to evaluate the balance of these competing risks. Two approaches are discussed - the win ratio and the DOOR probability on one treatment relative to another.
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Affiliation(s)
- Scott R Evans
- Biostatistics Center, Milken Institute School of Public Health, George Washington University, Rockville, MD
| | - Lijuan Zeng
- Biostatistics Center, Milken Institute School of Public Health, George Washington University, Rockville, MD
| | - Weixiao Dai
- Biostatistics Center, Milken Institute School of Public Health, George Washington University, Rockville, MD
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Neerland BE, Busund R, Haaverstad R, Helbostad JL, Landsverk SA, Martinaityte I, Norum HM, Ræder J, Selbaek G, Simpson MR, Skaar E, Skjærvold NK, Skovlund E, Slooter AJ, Svendsen ØS, Tønnessen T, Wahba A, Zetterberg H, Wyller TB. Alpha-2-adrenergic receptor agonists for the prevention of delirium and cognitive decline after open heart surgery (ALPHA2PREVENT): protocol for a multicentre randomised controlled trial. BMJ Open 2022; 12:e057460. [PMID: 35725264 PMCID: PMC9214392 DOI: 10.1136/bmjopen-2021-057460] [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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/06/2022] Open
Abstract
INTRODUCTION Postoperative delirium is common in older cardiac surgery patients and associated with negative short-term and long-term outcomes. The alpha-2-adrenergic receptor agonist dexmedetomidine shows promise as prophylaxis and treatment for delirium in intensive care units (ICU) and postoperative settings. Clonidine has similar pharmacological properties and can be administered both parenterally and orally. We aim to study whether repurposing of clonidine can represent a novel treatment option for delirium, and the possible effects of dexmedetomidine and clonidine on long-term cognitive trajectories, motor activity patterns and biomarkers of neuronal injury, and whether these effects are associated with frailty status. METHODS AND ANALYSIS This five-centre, double-blind randomised controlled trial will include 900 cardiac surgery patients aged 70+ years. Participants will be randomised 1:1:1 to dexmedetomidine or clonidine or placebo. The study drug will be given as a continuous intravenous infusion from the start of cardiopulmonary bypass, at a rate of 0.4 µg/kg/hour. The infusion rate will be decreased to 0.2 µg/kg/hour postoperatively and be continued until discharge from the ICU or 24 hours postoperatively, whichever happens first.Primary end point is the 7-day cumulative incidence of postoperative delirium (Diagnostic and Statistical Manual of Mental Disorders, fifth edition). Secondary end points include the composite end point of coma, delirium or death, in addition to delirium severity and motor activity patterns, levels of circulating biomarkers of neuronal injury, cognitive function and frailty status 1 and 6 months after surgery. ETHICS AND DISSEMINATION This trial is approved by the Regional Committee for Ethics in Medical Research in Norway (South-East Norway) and by the Norwegian Medicines Agency. Dissemination plans include publication in peer-reviewed medical journals and presentation at scientific meetings. TRIAL REGISTRATION NUMBER NCT05029050.
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Affiliation(s)
| | - Rolf Busund
- Department of Cardiothoracic and Vascular Surgery, University Hospital of North Norway, Tromsø, Norway
- Institute of Clinical Medicine, UiT The Artic University of Norway, Tromsø, Norway
| | - Rune Haaverstad
- Department of Heart Disease, Haukeland University Hospital, Bergen, Norway
- Institute of Clinical Science, University of Bergen, Bergen, Norway
| | - Jorunn L Helbostad
- Department of Neuromedicine and Movement Science, Norwegian University of Science and Technology, Trondheim, Norway
| | | | - Ieva Martinaityte
- Institute of Clinical Medicine, UiT The Artic University of Norway, Tromsø, Norway
- Department of Geriatric Medicine, University Hospital of North Norway, Tromsø, Norway
| | - Hilde Margrethe Norum
- Department of Anaesthesiology, Oslo University Hospital, Oslo, Norway
- Department of Research and Development, Oslo University Hospital, Oslo, Norway
| | - Johan Ræder
- Department of Anaesthesiology, Oslo University Hospital, Oslo, Norway
- Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Geir Selbaek
- Department of Geriatric Medicine, Oslo University Hospital, Oslo, Norway
- Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Norwegian National Advisory Unit on Ageing and Health, Tønsberg, Norway
| | - Melanie R Simpson
- Department of Public Health and Nursing, Norwegian University of Science and Technology, Trondheim, Norway
| | - Elisabeth Skaar
- Department of Heart Disease, Haukeland University Hospital, Bergen, Norway
| | - Nils Kristian Skjærvold
- Department of Circulation and Medical Imaging, Norwegian University of Science and Technology, Trondheim, Norway
- Department of Anesthesia and Intensive Care Medicine, Trondheim University Hospital, Trondheim, Norway
| | - Eva Skovlund
- Department of Public Health and Nursing, Norwegian University of Science and Technology, Trondheim, Norway
| | - Arjen Jc Slooter
- Department of Intensive Care Medicine, University Medical Centre Utrecht, Utrecht, The Netherlands
- Department of Neurology, UZ Brussel and Vrije Universiteit Brussel, Brussel, Brussel, Belgium
| | - Øyvind Sverre Svendsen
- Department of Anesthesia and Intensive Care, Haukeland University Hospital, Bergen, Norway
- Department of Clinical Medicine, University of Bergen, Bergen, Norway
| | - Theis Tønnessen
- Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Department of Cardiothoracic Surgery, Oslo University Hospital, Oslo, Norway
| | - Alexander Wahba
- Department of Circulation and Medical Imaging, Norwegian University of Science and Technology, Trondheim, Norway
- Clinic of Cardiothoracic Surgery, Trondheim University Hospital, Trondheim, Norway
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, University of Gothenburg Sahlgrenska Academy, Goteborg, Sweden
- Department of Neurodegenerative Disease, UCL Institute of Neurology, London, UK
- UK Dementia Research Institute, UCL, London, UK
- Hong Kong Center for Neurodegenerative Diseases, Hong Kong, People's Republic of China
| | - Torgeir Bruun Wyller
- Department of Geriatric Medicine, Oslo University Hospital, Oslo, Norway
- Institute of Clinical Medicine, University of Oslo, Oslo, Norway
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14
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Dilts NA, Harrell FE, Lindsell CJ, Nwosu S, Stewart TG, Shotwell MS, Pulley JM, Edwards TL, Serdoz ES, Benhoff K, Bernard GR. Securely sharing DSMB reports to speed decision making from multiple, concurrent, independent studies of similar treatments in COVID-19. J Clin Transl Sci 2022; 6:e49. [PMID: 35656334 PMCID: PMC9120618 DOI: 10.1017/cts.2022.387] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2021] [Revised: 01/22/2022] [Accepted: 04/05/2022] [Indexed: 11/11/2022] Open
Abstract
Introduction As clinical trials were rapidly initiated in response to the COVID-19 pandemic, Data and Safety Monitoring Boards (DSMBs) faced unique challenges overseeing trials of therapies never tested in a disease not yet characterized. Traditionally, individual DSMBs do not interact or have the benefit of seeing data from other accruing trials for an aggregated analysis to meaningfully interpret safety signals of similar therapeutics. In response, we developed a compliant DSMB Coordination (DSMBc) framework to allow the DSMB from one study investigating the use of SARS-CoV-2 convalescent plasma to treat COVID-19 to review data from similar ongoing studies for the purpose of safety monitoring. Methods The DSMBc process included engagement of DSMB chairs and board members, execution of contractual agreements, secure data acquisition, generation of harmonized reports utilizing statistical graphics, and secure report sharing with DSMB members. Detailed process maps, a secure portal for managing DSMB reports, and templates for data sharing and confidentiality agreements were developed. Results Four trials participated. Data from one trial were successfully harmonized with that of an ongoing trial. Harmonized reports allowing for visualization and drill down into the data were presented to the ongoing trial's DSMB. While DSMB deliberations are confidential, the Chair confirmed successful review of the harmonized report. Conclusion It is feasible to coordinate DSMB reviews of multiple independent studies of a similar therapeutic in similar patient cohorts. The materials presented mitigate challenges to DSMBc and will help expand these initiatives so DSMBs may make more informed decisions with all available information.
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Affiliation(s)
- Natalie A. Dilts
- Vanderbilt Institute for Clinical and Translational Research, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Frank E. Harrell
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, TN, USA
- Executive Committee for the Coordinated Approach for Emergency Studies
| | - Christopher J. Lindsell
- Vanderbilt Institute for Clinical and Translational Research, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, TN, USA
- Executive Committee for the Coordinated Approach for Emergency Studies
| | - Samuel Nwosu
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Thomas G. Stewart
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Matthew S. Shotwell
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Jill M. Pulley
- Vanderbilt Institute for Clinical and Translational Research, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Terri L. Edwards
- Vanderbilt Institute for Clinical and Translational Research, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Emily Sheffer Serdoz
- Vanderbilt Institute for Clinical and Translational Research, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Katelyn Benhoff
- Vanderbilt Institute for Clinical and Translational Research, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Gordon R. Bernard
- Vanderbilt Institute for Clinical and Translational Research, Vanderbilt University Medical Center, Nashville, TN, USA
- Executive Committee for the Coordinated Approach for Emergency Studies
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15
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Baillie M, Moloney C, Mueller CP, Dorn J, Branson J, Ohlssen D. Good Data Science Practice: Moving Towards a Code of Practice for Drug Development. Stat Biopharm Res 2022. [DOI: 10.1080/19466315.2022.2063172] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
Affiliation(s)
- Mark Baillie
- Clinical Development & Analytics, Novartis Pharma AG, Basel, Switzerland
| | - Conor Moloney
- Clinical Development & Analytics, Novartis Pharma AG, Dublin, Ireland
| | | | - Jonas Dorn
- pRED Informatics, Roche, Basel, Switzerland
| | - Janice Branson
- Clinical Development & Analytics, Novartis Pharma AG, Basel, Switzerland
| | - David Ohlssen
- Clinical Development & Analytics, Novartis Pharma AG, East Hannover, New Jersey, USA
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16
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Lohmann AE, Ennis M, Parulekar WR, Chen BE, Tomlinson G, Goodwin PJ. The Futility of Futility Analyses in Adjuvant Trials in Hormone Receptor Positive Breast Cancer. J Natl Cancer Inst 2022; 114:924-929. [PMID: 35377437 PMCID: PMC9275774 DOI: 10.1093/jnci/djac067] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2021] [Revised: 02/11/2022] [Accepted: 03/22/2022] [Indexed: 11/12/2022] Open
Abstract
An interim analysis is commonly used in phase III superiority trials to compare treatment arms, with the goal of terminating exposure of patients to ineffective or unsafe drugs, or to identify highly effective therapies for earlier public disclosure. Traditionally, interim analyses have been designed to identify early evidence of extremely large benefit of the experimental approach, potentially leading to early dissemination of effective treatments. Increasingly, interim analysis has also involved analysis of futility which may lead to early termination of a trial that will not yield additional useful information This presents an important challenge in early-stage hormone receptor positive breast cancer, where recurrence often occurs late, with a steady annual event rate up to 20 years. Early analysis of events may miss late treatment effects that can be observed only with longer follow-up. We discuss approaches to futility analysis in adjuvant clinical trials in hormone receptor positive breast cancer, the role of the Data Safety Monitoring Committee in such analyses, considerations of the potential harms versus benefits of treatment, and the risks of continuing versus early stopping of a trial.
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Affiliation(s)
- Ana Elisa Lohmann
- Department of Medical Oncology, University of Western Ontario, Ontario, Canada
| | | | - Wendy R Parulekar
- Canadian Cancer Trials Group, Queen's University, Kingston, Ontario, Canada
| | - Bingshu E Chen
- Canadian Cancer Trials Group, Queen's University, Kingston, Ontario, Canada
| | - George Tomlinson
- Institute of Health Policy Management and Evaluation, University of Toronto, Ontario, Canada.,Department of Medicine, University Health Network and Mount Sinai Hospital
| | - Pamela J Goodwin
- Institute of Health Policy Management and Evaluation, University of Toronto, Ontario, Canada.,Lunenfeld-Tanenbaum Research Institute, Mount Sinai Hospital, University of Toronto, Ontario, Canada
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17
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Evans SR. Independent Oversight of Clinical Trials through Data and Safety Monitoring Boards. NEJM EVIDENCE 2022; 1:EVIDctw2100005. [PMID: 38319172 DOI: 10.1056/evidctw2100005] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/07/2024]
Abstract
DSMBs: Protecting Patients and Scientific IntegrityDSMBs look after the welfare of patients enrolled in interventional clinical trials. DSMBs monitor for early establishment of efficacy, findings of harm, futility in obtaining a meaningful outcome, or changes in the ecology of care that render moot the question a trial aims to answer. This article opens a series of NEJM Evidence reviews about DSMBs.
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Affiliation(s)
- Scott R Evans
- Biostatistics Center, Department of Biostatistics and Bioinformatics, Milken Institute School of Public Health, George Washington University, Rockville, MD
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18
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Factors influencing the statistical planning, design, conduct, analysis and reporting of trials in health care: A systematic review. Contemp Clin Trials Commun 2022; 26:100897. [PMID: 35198793 PMCID: PMC8842005 DOI: 10.1016/j.conctc.2022.100897] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2020] [Revised: 11/24/2021] [Accepted: 01/24/2022] [Indexed: 11/23/2022] Open
Abstract
Background Trials in health care are prospective human research studies designed to test the effectiveness and safety of health care interventions, such as medications, surgeries, medical devices and other treatment or prevention interventions. Statistics is an important and powerful tool in trials. Inappropriately designed trials and/or inappropriate statistical analysis produce unreliable results and a lack of transparency when reported, with limited clinical use. Aim This systematic literature review aimed to identify, describe and synthesise factors contributing to or influencing the statistical planning, design, conduct, analysis and reporting of trials. Methods Information sources were retrieved from the following electronic citation databases: PubMed, Web of Science, PsycINFO, and CINAHL and the grey literature repository: OpenGrey. 90 articles and guidelines were included in this review. A narrative, thematic synthesis identified the key factors influencing the statistical planning, design, conduct, analysis and reporting of trials in health care. Findings and conclusion We identified three analytical themes within which factors are grouped. These are: “what makes a statistician?“, “the need for dynamic statistical involvement and collaboration throughout a trial – it's not just about the numbers”, “and the “accountability of statisticians in ensuring the safety of trial participants and the integrity of trial data”. While important insights emerged about the qualifications, training, roles, and responsibilities of statisticians and their collaboration with other team members in a trial, further empirical research is warranted to elicit the perceptions of trial team members at the centre of statistics in trials.
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19
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Eckstein L, Rid A, Kamuya D, Shah SK. The Essential Role of Data and Safety Monitoring Boards (DSMBs) in Ensuring the Ethics of Global Vaccine Trials to Address Coronavirus Disease 2019 (COVID-19O). Clin Infect Dis 2021; 73:2126-2130. [PMID: 33758912 PMCID: PMC8083612 DOI: 10.1093/cid/ciab239] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2021] [Indexed: 11/13/2022] Open
Abstract
Coronavirus disease 2019 (COVID-19) vaccines are being developed and implemented with unprecedented speed. Accordingly, trials considered ethical at their inception may quickly become concerning. We provide recommendations for Data and Safety Monitoring Boards (DSMBs) on monitoring the ethical acceptability of COVID-19 vaccine trials, focusing on placebo-controlled trials in low- and middle-income countries.
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Affiliation(s)
- Lisa Eckstein
- School of Law, University of Tasmania, Hobart, Australia
| | - Annette Rid
- Clinical Center Department of Bioethics & Division of AIDS, National Institutes of Health, Bethesda, MarylandUSA
| | - Dorcas Kamuya
- Health Systems and Research Ethics (HSRE) Department, Kenya Medical Research Institute (KEMRI)-Wellcome Trust Research Programme, Nairobi, Kenya
| | - Seema K Shah
- Department of Pediatrics, Chicago, IllinoisUSA
- Mary Ann & J. Milburn Smith Child Health Outcomes, Research, and Evaluation (SCHORE) Center; Stanley Manne Children’s Research Institute; Lurie Children’s Hospital, Chicago, IllinoisUSA
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20
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Schöffski P. Importance and role of independent data monitoring committees (IDMCs) in oncology clinical trials. BMJ Open 2021; 11:e047294. [PMID: 34697110 PMCID: PMC8547363 DOI: 10.1136/bmjopen-2020-047294] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/24/2022] Open
Abstract
The role and use of independent data monitoring committees (IDMCs) has evolved over the past decades. The Food and Drug Administration and European Medicines Agency have issued guidelines on the role and functioning of such committees. In general, data monitoring committees are recommended for large, often randomised clinical trials involving life-threatening diseases, studies performed in vulnerable populations or where the experimental intervention can potentially harm the trial participant. Such committees play an important role in trials evaluating treatments with the potential to prolong life or reduce the risk of major adverse health outcomes.Typically, oncology clinical trials fall within these recommendations, as they are often large, randomised, multicentric protocols aiming at improving survival outcomes by exploring the use of study treatments that may be associated with a significant risk of serious, even life-threatening adverse events. IDMCs are required for National Cancer Institute phase III randomised trials, European Organisation for Research and Treatment of Cancer phase II/III trials with formal interim analyses, early-stopping rules or adaptive studies. The primary role of an IDMC of ensuring the safety of study participants and maintaining clinical trial integrity is particularly important in oncology trials, due to the nature of the disease, the potential for treatment toxicity and for instilling confidence that the clinical trial data are reliable. A clear understanding by IDMC members of the natural course of the disease, treatment landscape, importance and relevance of certain adverse events in trial participants, clinical trial methodology in general and stopping rules for oncology trials in particular, is crucial for the functioning of an IDMC.It is recommended that IDMC members should be experienced trialists, have a track record of strong clinical, statistical and/or methodological expertise and the required level of independence, as they play a highly important role in the protection of study participants, and in commercially and strategically important go/no decisions. Ideally, IDMC members should have relevant experience or have some training, mentorship or guidelines.
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Affiliation(s)
- P Schöffski
- Department of General Medical Oncology, University Hospitals Leuven, KU Leuven, Leuven Cancer Institute, Leuven, Belgium
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21
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Abstract
Currently, too many Data Monitoring Committee Reports for interim review of trial progress are quite inadequate for Data Monitoring Committees to make informed decisions about risks and benefits. Immediate serious improvement is necessary for Data Monitoring Committees to meet their ethical, clinical, and scientific responsibility to trial participants, investigators, sponsors, and participating institutions. To achieve this critical goal, all parties involved in the Data Monitoring Committee process including sponsors, investigators, Data Monitoring Committee members, and the independent statistical reporting group need to have a better understanding of the structure, function, and needs of a Data Monitoring Committee and the content of a Data Monitoring Committee Report. Training modules through the Society for Clinical Trials are now available on their website to facilitate this.
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Affiliation(s)
| | - Janet Wittes
- WCG Acquires Statistics Collaborative, Washington, DC, USA
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22
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DeMets DL, Fleming TR, Ellenberg SS. Monitoring clinical trials in infectious diseases. JOURNAL OF ALLERGY AND INFECTIOUS DISEASES 2021; 2:29-32. [PMID: 35005713 PMCID: PMC8740779 DOI: 10.46439/allergy.2.019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 12/02/2022]
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23
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Fischer T. Das Data Monitoring Committee – State of the Art und Perspektiven für die Zukunft. Bundesgesundheitsblatt Gesundheitsforschung Gesundheitsschutz 2020; 63:1511-1518. [PMID: 32897407 PMCID: PMC7477738 DOI: 10.1007/s00103-020-03212-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2020] [Accepted: 08/10/2020] [Indexed: 11/25/2022]
Abstract
Zusammenfassung
Hintergrund
Die klassische randomisierte und kontrollierte klinische Prüfung steht mit komplexen Studiendesigns und Disease-Interception-Konzepten vor neuen Herausforderungen. Dabei können Data Monitoring Committees (Datenüberwachungskomitees [DMCs]) eine zentrale Funktion übernehmen, wenn eine fachgerechte Integration in den methodischen Ablauf der klinischen Prüfungen erfolgt. Vor diesem Hintergrund haben die zuständige Bundesoberbehörde und die zuständige Ethikkommission im impliziten/expliziten Genehmigungsverfahren zu überprüfen, ob eine substanzielle Charta die Arbeitsweise des unabhängigen Gremiums abbildet.
Ziel
Es wurde der Frage nachgegangen, mit welchen Häufigkeiten und Gegebenheiten DMCs in klinischen Prüfungen eingesetzt werden.
Methode
Die Datenbank des Bundesinstituts für Arzneimittel und Medizinprodukte (BfArM) bildet die Grundlage für eine Datenanalyse hinsichtlich Häufigkeiten der Implementierung von Data Monitoring Committees unter verschiedenen Kriterien über einen Beobachtungszeitraum von mehr als 15 Jahren.
Ergebnisse
Bei insgesamt 14.135 klinischen Prüfungen mit Arzneimitteln wurde 4152 DMCs eingesetzt. Das unabhängige Expertengremium wurde überwiegend von kommerziellen Sponsoren in der Phase III der klinischen Entwicklung integriert. Die Ethikkommissionen waren mit unterschiedlichen absoluten Häufigkeiten eingebunden.
Diskussion
Die Sponsoren zeigen eine zunehmende Bereitschaft, DMCs in die methodische Durchführung von klinischen Prüfungen, insbesondere bei neuartigen Studiendesigns, zu integrieren. DMCs können eine wichtige wissenschaftliche Unterstützung sein, um die Implikationen des Coronavirus SARS-CoV‑2 auf klinische Prüfungen zu beurteilen.
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Affiliation(s)
- Thomas Fischer
- Fachgebiet Klinische Prüfung/Klinik, Bundesinstitut für Arzneimittel und Medizinprodukte, Kurt-Georg-Kiesinger-Allee 3, 53175, Bonn, Deutschland.
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24
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Krause PR, Fleming TR, Ellenberg SS, Henao-Restrepo AM. Maintaining confidentiality of emerging results in COVID-19 vaccine trials is essential. Lancet 2020; 396:1611-1613. [PMID: 33125926 PMCID: PMC7834563 DOI: 10.1016/s0140-6736(20)32259-5] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/22/2020] [Accepted: 10/26/2020] [Indexed: 12/23/2022]
Affiliation(s)
- Philip R Krause
- Office of Vaccines Research and Review, Center for Biologics Evaluation and Research, US Food and Drug Administration, Silver Spring, MD, USA
| | - Thomas R Fleming
- University of Washington, Fred Hutchinson Cancer Centre, Seattle, WA, USA
| | - Susan S Ellenberg
- Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
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25
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Liu J, Wang N, Dang HX, Chen BW, Zhang L, Zou C, Zhong CL, Huang JK, Liu Q, Yu YN, Jiang M, Liang WX, Chen QG, Wang YY, Shen CT, Wang Z. Standard Operating Procedures for Chinese Medicine Data Monitoring Committees of Clinical Studies. Chin J Integr Med 2020; 27:483-489. [PMID: 33170939 DOI: 10.1007/s11655-020-3439-2] [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] [Accepted: 09/16/2020] [Indexed: 11/26/2022]
Abstract
Although there is guidance from different regulatory agencies, there are opportunities to bring greater consistency and stronger applicability to address the practical issues of establishing and operating a data monitoring committee (DMC) for clinical studies of Chinese medicine. We names it as a Chinese Medicine Data Monitoring Committee (CMDMC). A panel composed of clinical and statistical experts shared their experience and thoughts on the important aspects of CMDMCs. Subsequently, a community standard on CMDMCs (T/CACM 1323-2019) was issued by the China Association of Chinese Medicine on September 12, 2019. This paper summarizes the key content of this standard to help the sponsors of clinical studies establish and operate CMDMCs, which will further develop the scientific integrity and quality of clinical studies.
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Affiliation(s)
- Jun Liu
- Institute of Basic Research in Clinical Medicine, China Academy of Chinese Medical Sciences, Beijing, 100700, China
| | - Nian Wang
- Institute of Basic Research in Clinical Medicine, China Academy of Chinese Medical Sciences, Beijing, 100700, China
| | - Hai-Xia Dang
- China Academy of Chinese Medical Sciences, Beijing, 100700, China
| | - Bing-Wei Chen
- School of Public Health, Southeast University, Nanjing, 210009, China
| | - Li Zhang
- Dongfang Hospital Affiliated to Beijing University of Chinese Medicine, Beijing, 100078, China
| | - Chong Zou
- Jiangsu Provincial Hospital of Traditional Chinese Medicine (Affiliated Hospital of Nanjing University of Traditional Chinese Medicine), Nanjing, 210029, China
| | - Cheng-Liang Zhong
- First Teaching Hospital of Tianjin University of Traditional Chinese Medicine, Tianjin, 300381, China
| | - Ju-Kai Huang
- Dongfang Hospital Affiliated to Beijing University of Chinese Medicine, Beijing, 100078, China
| | - Qiong Liu
- Institute of Basic Research in Clinical Medicine, China Academy of Chinese Medical Sciences, Beijing, 100700, China
| | - Ya-Nan Yu
- Institute of Basic Research in Clinical Medicine, China Academy of Chinese Medical Sciences, Beijing, 100700, China
| | - Meng Jiang
- Jiangsu Provincial Hospital of Traditional Chinese Medicine (Affiliated Hospital of Nanjing University of Traditional Chinese Medicine), Nanjing, 210029, China
| | - Wei-Xiong Liang
- Guangdong Hospital of Traditional Chinese Medicine, Guangzhou, 510120, China
| | - Qi-Guang Chen
- School of Public Health, Southeast University, Nanjing, 210009, China
| | - Yong-Yan Wang
- Institute of Basic Research in Clinical Medicine, China Academy of Chinese Medical Sciences, Beijing, 100700, China
| | - Chun-Ti Shen
- Changzhou Traditional Chinese Medicine Hospital, Changzhou, Jiangsu Province, 213004, China
| | - Zhong Wang
- Institute of Basic Research in Clinical Medicine, China Academy of Chinese Medical Sciences, Beijing, 100700, China.
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26
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Mütze T, Friede T. Data monitoring committees for clinical trials evaluating treatments of COVID-19. Contemp Clin Trials 2020; 98:106154. [PMID: 32961361 PMCID: PMC7833551 DOI: 10.1016/j.cct.2020.106154] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2020] [Accepted: 09/15/2020] [Indexed: 12/15/2022]
Abstract
The first cases of coronavirus disease 2019 (COVID-19) were reported in December 2019 and the outbreak of SARS-CoV-2 was declared a pandemic in March 2020 by the World Health Organization. This sparked a plethora of investigations into diagnostics and vaccination for SARS-CoV-2, as well as treatments for COVID-19. Since COVID-19 is a severe disease associated with a high mortality, clinical trials in this disease should be monitored by a data monitoring committee (DMC), also known as data safety monitoring board (DSMB). DMCs in this indication face a number of challenges including fast recruitment requiring an unusually high frequency of safety reviews, more frequent use of complex designs and virtually no prior experience with the disease. In this paper, we provide a perspective on the work of DMCs for clinical trials of treatments for COVID-19. More specifically, we discuss organizational aspects of setting up and running DMCs for COVID-19 trials, in particular for trials with more complex designs such as platform trials or adaptive designs. Furthermore, statistical aspects of monitoring clinical trials of treatments for COVID-19 are considered. Some recommendations are made regarding the presentation of the data, stopping rules for safety monitoring and the use of external data. The proposed stopping boundaries are assessed in a simulation study motivated by clinical trials in COVID-19.
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Affiliation(s)
- Tobias Mütze
- Statistical Methodology, Novartis Pharma AG, Basel, Switzerland
| | - Tim Friede
- Department of Medical Statistics, University Medical Center Göttingen, Göttingen, Germany; DZHK (German Center for Cardiovascular Research), partner site Göttingen, Göttingen, Germany.
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27
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Thomas SM, Jung K, Sun H, Psioda MA, Quibrera PM, Strakowski SM. Enhancing clarity of clinical trial safety reports for data monitoring committees. J Biopharm Stat 2020; 30:1147-1161. [PMID: 32897808 DOI: 10.1080/10543406.2020.1815034] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
Abstract
A Data Monitoring Committee (DMC) evaluates patient safety in a clinical trial of an investigational intervention through periodic review of adverse events (AEs) and clinical safety assessments. Our aim was to construct DMC report displays to enhance the DMC safety review through use of graphics and clear identification and adjustment for missing data caused by early discontinuations and ongoing study participation. Suggested displays include a study snapshot graph, enhanced adverse event incidence tables including the incidence density and plotted incidence proportions, line graphs in place of by-patient listings, and trend plots in place of tables for continuous assessments.
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Affiliation(s)
- Sonia M Thomas
- Division of Biostatistics and Epidemiology, RTI International, Research Triangle Park, NC, USA
| | - Kwanhye Jung
- Collaborative Studies Coordinating Center, Department of Biostatistics, University of North Carolina, Chapel Hill, NC, USA
| | - Hengrui Sun
- Division of Biometrics IV, Office of Biostatistics, Center for Drug Evaluation and Research, US Food and Drug Administration, Silver Spring, MD, USA
| | - Matthew A Psioda
- Collaborative Studies Coordinating Center, Department of Biostatistics, University of North Carolina, Chapel Hill, NC, USA
| | - Pedro Miguel Quibrera
- Collaborative Studies Coordinating Center, Department of Biostatistics, University of North Carolina, Chapel Hill, NC, USA
| | - Stephen M Strakowski
- Department of Psychiatry, Dell Medical School, University of Texas, Austin, TX, USA
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DeMets DL, Fleming TR. Achieving effective informed oversight by DMCs in COVID clinical trials. J Clin Epidemiol 2020; 126:167-171. [PMID: 32659363 PMCID: PMC7351066 DOI: 10.1016/j.jclinepi.2020.07.001] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2020] [Revised: 07/02/2020] [Accepted: 07/07/2020] [Indexed: 12/14/2022]
Abstract
Best practices of data monitoring committees (DMCs) in randomized clinical trials are well established. Independent oversight provided by DMCs is particularly important in trials conducted in public health emergencies, such as in HIV/AIDS or coronavirus epidemics. Special considerations are needed to enable DMCs to effectively address novel circumstances they face in such settings. In the COVID-19 pandemic, these include the remarkable speed in which data regarding benefits and risks of interventions are accumulated. DMCs must hold frequent virtual meetings, using state-of-the-art communication software that protects against risk for security breaches. Data capture and DMC reports should be focused on the most informative measures about benefits and risks. Because numerous clinical trials are being concurrently conducted in the COVID-19 setting, often addressing closely related scientific questions, structures for DMC oversight should be efficient and adequately informative. When these concurrently conducted trials are evaluating related regimens in related clinical settings, often individually underpowered for safety and having separate DMCs, processes should be implemented enabling these DMCs to share with each other emerging confidential evidence to better assess risks and benefits. Ideally a single DMC would monitor a portfolio of clinical trials or a trial with multiple arms, such as a platform trial. For 5 decades, DMCs have monitored RCTs for safety and benefit. In 2020, the World Health Organization declared covid-19 disease to be a pandemic. Numerous trials have emerged to evaluate potential therapeutics and vaccines. Covid-19 trials bring new challenges to the DMC process, due to the epidemic speed. Patients are being recruited and outcome data accumulating very rapidly. DMCs oversight very important for extreme emergencies such as coronavirus epidemics.
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Dean NE, Gsell PS, Brookmeyer R, Crawford FW, Donnelly CA, Ellenberg SS, Fleming TR, Halloran ME, Horby P, Jaki T, Krause PR, Longini IM, Mulangu S, Muyembe-Tamfum JJ, Nason MC, Smith PG, Wang R, Henao-Restrepo AM, De Gruttola V. Creating a Framework for Conducting Randomized Clinical Trials during Disease Outbreaks. N Engl J Med 2020; 382:1366-1369. [PMID: 32242365 PMCID: PMC7490833 DOI: 10.1056/nejmsb1905390] [Citation(s) in RCA: 51] [Impact Index Per Article: 12.8] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Affiliation(s)
- Natalie E Dean
- From the Department of Biostatistics, University of Florida, Gainesville (N.E.D., I.M.L.); the World Health Organization, Geneva (P.-S.G., A.M.H.-R.); the Department of Biostatistics, University of California, Los Angeles (R.B.); the Department of Biostatistics, Yale University, New Haven, CT (F.W.C.); the Department of Statistics (C.A.D.) and the Centre for Tropical Medicine and Global Health (P.H.), University of Oxford, Oxford, the Medical Research Council (MRC) Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London (C.A.D.), and the MRC Tropical Epidemiology Group, London School of Hygiene and Tropical Medicine (P.G.S.), London, and the Department of Mathematics and Statistics, Lancaster University, Lancaster (T.J.) - all in the United Kingdom; the Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania, Philadelphia (S.S.E.); the Department of Biostatistics, University of Washington (T.R.F., M.E.H.), and the Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center (M.E.H.) - both in Seattle; the Office of Vaccines Research and Review, Center for Biologics Evaluation and Research, Food and Drug Administration, Silver Spring (P.R.K.), and the Biostatistics Research Branch, National Institute of Allergy and Infectious Diseases, Bethesda (M.C.N.) - both in Maryland; Institut National de Recherche Biomédicale, Kinshasa, Democratic Republic of Congo (S.M., J.-J.M.-T.); and the Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute (R.W.), and the Department of Biostatistics, Harvard T.H. Chan School of Public Health (R.W., V.D.G.) - both in Boston
| | - Pierre-Stéphane Gsell
- From the Department of Biostatistics, University of Florida, Gainesville (N.E.D., I.M.L.); the World Health Organization, Geneva (P.-S.G., A.M.H.-R.); the Department of Biostatistics, University of California, Los Angeles (R.B.); the Department of Biostatistics, Yale University, New Haven, CT (F.W.C.); the Department of Statistics (C.A.D.) and the Centre for Tropical Medicine and Global Health (P.H.), University of Oxford, Oxford, the Medical Research Council (MRC) Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London (C.A.D.), and the MRC Tropical Epidemiology Group, London School of Hygiene and Tropical Medicine (P.G.S.), London, and the Department of Mathematics and Statistics, Lancaster University, Lancaster (T.J.) - all in the United Kingdom; the Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania, Philadelphia (S.S.E.); the Department of Biostatistics, University of Washington (T.R.F., M.E.H.), and the Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center (M.E.H.) - both in Seattle; the Office of Vaccines Research and Review, Center for Biologics Evaluation and Research, Food and Drug Administration, Silver Spring (P.R.K.), and the Biostatistics Research Branch, National Institute of Allergy and Infectious Diseases, Bethesda (M.C.N.) - both in Maryland; Institut National de Recherche Biomédicale, Kinshasa, Democratic Republic of Congo (S.M., J.-J.M.-T.); and the Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute (R.W.), and the Department of Biostatistics, Harvard T.H. Chan School of Public Health (R.W., V.D.G.) - both in Boston
| | - Ron Brookmeyer
- From the Department of Biostatistics, University of Florida, Gainesville (N.E.D., I.M.L.); the World Health Organization, Geneva (P.-S.G., A.M.H.-R.); the Department of Biostatistics, University of California, Los Angeles (R.B.); the Department of Biostatistics, Yale University, New Haven, CT (F.W.C.); the Department of Statistics (C.A.D.) and the Centre for Tropical Medicine and Global Health (P.H.), University of Oxford, Oxford, the Medical Research Council (MRC) Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London (C.A.D.), and the MRC Tropical Epidemiology Group, London School of Hygiene and Tropical Medicine (P.G.S.), London, and the Department of Mathematics and Statistics, Lancaster University, Lancaster (T.J.) - all in the United Kingdom; the Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania, Philadelphia (S.S.E.); the Department of Biostatistics, University of Washington (T.R.F., M.E.H.), and the Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center (M.E.H.) - both in Seattle; the Office of Vaccines Research and Review, Center for Biologics Evaluation and Research, Food and Drug Administration, Silver Spring (P.R.K.), and the Biostatistics Research Branch, National Institute of Allergy and Infectious Diseases, Bethesda (M.C.N.) - both in Maryland; Institut National de Recherche Biomédicale, Kinshasa, Democratic Republic of Congo (S.M., J.-J.M.-T.); and the Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute (R.W.), and the Department of Biostatistics, Harvard T.H. Chan School of Public Health (R.W., V.D.G.) - both in Boston
| | - Forrest W Crawford
- From the Department of Biostatistics, University of Florida, Gainesville (N.E.D., I.M.L.); the World Health Organization, Geneva (P.-S.G., A.M.H.-R.); the Department of Biostatistics, University of California, Los Angeles (R.B.); the Department of Biostatistics, Yale University, New Haven, CT (F.W.C.); the Department of Statistics (C.A.D.) and the Centre for Tropical Medicine and Global Health (P.H.), University of Oxford, Oxford, the Medical Research Council (MRC) Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London (C.A.D.), and the MRC Tropical Epidemiology Group, London School of Hygiene and Tropical Medicine (P.G.S.), London, and the Department of Mathematics and Statistics, Lancaster University, Lancaster (T.J.) - all in the United Kingdom; the Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania, Philadelphia (S.S.E.); the Department of Biostatistics, University of Washington (T.R.F., M.E.H.), and the Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center (M.E.H.) - both in Seattle; the Office of Vaccines Research and Review, Center for Biologics Evaluation and Research, Food and Drug Administration, Silver Spring (P.R.K.), and the Biostatistics Research Branch, National Institute of Allergy and Infectious Diseases, Bethesda (M.C.N.) - both in Maryland; Institut National de Recherche Biomédicale, Kinshasa, Democratic Republic of Congo (S.M., J.-J.M.-T.); and the Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute (R.W.), and the Department of Biostatistics, Harvard T.H. Chan School of Public Health (R.W., V.D.G.) - both in Boston
| | - Christl A Donnelly
- From the Department of Biostatistics, University of Florida, Gainesville (N.E.D., I.M.L.); the World Health Organization, Geneva (P.-S.G., A.M.H.-R.); the Department of Biostatistics, University of California, Los Angeles (R.B.); the Department of Biostatistics, Yale University, New Haven, CT (F.W.C.); the Department of Statistics (C.A.D.) and the Centre for Tropical Medicine and Global Health (P.H.), University of Oxford, Oxford, the Medical Research Council (MRC) Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London (C.A.D.), and the MRC Tropical Epidemiology Group, London School of Hygiene and Tropical Medicine (P.G.S.), London, and the Department of Mathematics and Statistics, Lancaster University, Lancaster (T.J.) - all in the United Kingdom; the Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania, Philadelphia (S.S.E.); the Department of Biostatistics, University of Washington (T.R.F., M.E.H.), and the Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center (M.E.H.) - both in Seattle; the Office of Vaccines Research and Review, Center for Biologics Evaluation and Research, Food and Drug Administration, Silver Spring (P.R.K.), and the Biostatistics Research Branch, National Institute of Allergy and Infectious Diseases, Bethesda (M.C.N.) - both in Maryland; Institut National de Recherche Biomédicale, Kinshasa, Democratic Republic of Congo (S.M., J.-J.M.-T.); and the Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute (R.W.), and the Department of Biostatistics, Harvard T.H. Chan School of Public Health (R.W., V.D.G.) - both in Boston
| | - Susan S Ellenberg
- From the Department of Biostatistics, University of Florida, Gainesville (N.E.D., I.M.L.); the World Health Organization, Geneva (P.-S.G., A.M.H.-R.); the Department of Biostatistics, University of California, Los Angeles (R.B.); the Department of Biostatistics, Yale University, New Haven, CT (F.W.C.); the Department of Statistics (C.A.D.) and the Centre for Tropical Medicine and Global Health (P.H.), University of Oxford, Oxford, the Medical Research Council (MRC) Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London (C.A.D.), and the MRC Tropical Epidemiology Group, London School of Hygiene and Tropical Medicine (P.G.S.), London, and the Department of Mathematics and Statistics, Lancaster University, Lancaster (T.J.) - all in the United Kingdom; the Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania, Philadelphia (S.S.E.); the Department of Biostatistics, University of Washington (T.R.F., M.E.H.), and the Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center (M.E.H.) - both in Seattle; the Office of Vaccines Research and Review, Center for Biologics Evaluation and Research, Food and Drug Administration, Silver Spring (P.R.K.), and the Biostatistics Research Branch, National Institute of Allergy and Infectious Diseases, Bethesda (M.C.N.) - both in Maryland; Institut National de Recherche Biomédicale, Kinshasa, Democratic Republic of Congo (S.M., J.-J.M.-T.); and the Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute (R.W.), and the Department of Biostatistics, Harvard T.H. Chan School of Public Health (R.W., V.D.G.) - both in Boston
| | - Thomas R Fleming
- From the Department of Biostatistics, University of Florida, Gainesville (N.E.D., I.M.L.); the World Health Organization, Geneva (P.-S.G., A.M.H.-R.); the Department of Biostatistics, University of California, Los Angeles (R.B.); the Department of Biostatistics, Yale University, New Haven, CT (F.W.C.); the Department of Statistics (C.A.D.) and the Centre for Tropical Medicine and Global Health (P.H.), University of Oxford, Oxford, the Medical Research Council (MRC) Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London (C.A.D.), and the MRC Tropical Epidemiology Group, London School of Hygiene and Tropical Medicine (P.G.S.), London, and the Department of Mathematics and Statistics, Lancaster University, Lancaster (T.J.) - all in the United Kingdom; the Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania, Philadelphia (S.S.E.); the Department of Biostatistics, University of Washington (T.R.F., M.E.H.), and the Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center (M.E.H.) - both in Seattle; the Office of Vaccines Research and Review, Center for Biologics Evaluation and Research, Food and Drug Administration, Silver Spring (P.R.K.), and the Biostatistics Research Branch, National Institute of Allergy and Infectious Diseases, Bethesda (M.C.N.) - both in Maryland; Institut National de Recherche Biomédicale, Kinshasa, Democratic Republic of Congo (S.M., J.-J.M.-T.); and the Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute (R.W.), and the Department of Biostatistics, Harvard T.H. Chan School of Public Health (R.W., V.D.G.) - both in Boston
| | - M Elizabeth Halloran
- From the Department of Biostatistics, University of Florida, Gainesville (N.E.D., I.M.L.); the World Health Organization, Geneva (P.-S.G., A.M.H.-R.); the Department of Biostatistics, University of California, Los Angeles (R.B.); the Department of Biostatistics, Yale University, New Haven, CT (F.W.C.); the Department of Statistics (C.A.D.) and the Centre for Tropical Medicine and Global Health (P.H.), University of Oxford, Oxford, the Medical Research Council (MRC) Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London (C.A.D.), and the MRC Tropical Epidemiology Group, London School of Hygiene and Tropical Medicine (P.G.S.), London, and the Department of Mathematics and Statistics, Lancaster University, Lancaster (T.J.) - all in the United Kingdom; the Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania, Philadelphia (S.S.E.); the Department of Biostatistics, University of Washington (T.R.F., M.E.H.), and the Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center (M.E.H.) - both in Seattle; the Office of Vaccines Research and Review, Center for Biologics Evaluation and Research, Food and Drug Administration, Silver Spring (P.R.K.), and the Biostatistics Research Branch, National Institute of Allergy and Infectious Diseases, Bethesda (M.C.N.) - both in Maryland; Institut National de Recherche Biomédicale, Kinshasa, Democratic Republic of Congo (S.M., J.-J.M.-T.); and the Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute (R.W.), and the Department of Biostatistics, Harvard T.H. Chan School of Public Health (R.W., V.D.G.) - both in Boston
| | - Peter Horby
- From the Department of Biostatistics, University of Florida, Gainesville (N.E.D., I.M.L.); the World Health Organization, Geneva (P.-S.G., A.M.H.-R.); the Department of Biostatistics, University of California, Los Angeles (R.B.); the Department of Biostatistics, Yale University, New Haven, CT (F.W.C.); the Department of Statistics (C.A.D.) and the Centre for Tropical Medicine and Global Health (P.H.), University of Oxford, Oxford, the Medical Research Council (MRC) Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London (C.A.D.), and the MRC Tropical Epidemiology Group, London School of Hygiene and Tropical Medicine (P.G.S.), London, and the Department of Mathematics and Statistics, Lancaster University, Lancaster (T.J.) - all in the United Kingdom; the Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania, Philadelphia (S.S.E.); the Department of Biostatistics, University of Washington (T.R.F., M.E.H.), and the Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center (M.E.H.) - both in Seattle; the Office of Vaccines Research and Review, Center for Biologics Evaluation and Research, Food and Drug Administration, Silver Spring (P.R.K.), and the Biostatistics Research Branch, National Institute of Allergy and Infectious Diseases, Bethesda (M.C.N.) - both in Maryland; Institut National de Recherche Biomédicale, Kinshasa, Democratic Republic of Congo (S.M., J.-J.M.-T.); and the Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute (R.W.), and the Department of Biostatistics, Harvard T.H. Chan School of Public Health (R.W., V.D.G.) - both in Boston
| | - Thomas Jaki
- From the Department of Biostatistics, University of Florida, Gainesville (N.E.D., I.M.L.); the World Health Organization, Geneva (P.-S.G., A.M.H.-R.); the Department of Biostatistics, University of California, Los Angeles (R.B.); the Department of Biostatistics, Yale University, New Haven, CT (F.W.C.); the Department of Statistics (C.A.D.) and the Centre for Tropical Medicine and Global Health (P.H.), University of Oxford, Oxford, the Medical Research Council (MRC) Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London (C.A.D.), and the MRC Tropical Epidemiology Group, London School of Hygiene and Tropical Medicine (P.G.S.), London, and the Department of Mathematics and Statistics, Lancaster University, Lancaster (T.J.) - all in the United Kingdom; the Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania, Philadelphia (S.S.E.); the Department of Biostatistics, University of Washington (T.R.F., M.E.H.), and the Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center (M.E.H.) - both in Seattle; the Office of Vaccines Research and Review, Center for Biologics Evaluation and Research, Food and Drug Administration, Silver Spring (P.R.K.), and the Biostatistics Research Branch, National Institute of Allergy and Infectious Diseases, Bethesda (M.C.N.) - both in Maryland; Institut National de Recherche Biomédicale, Kinshasa, Democratic Republic of Congo (S.M., J.-J.M.-T.); and the Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute (R.W.), and the Department of Biostatistics, Harvard T.H. Chan School of Public Health (R.W., V.D.G.) - both in Boston
| | - Philip R Krause
- From the Department of Biostatistics, University of Florida, Gainesville (N.E.D., I.M.L.); the World Health Organization, Geneva (P.-S.G., A.M.H.-R.); the Department of Biostatistics, University of California, Los Angeles (R.B.); the Department of Biostatistics, Yale University, New Haven, CT (F.W.C.); the Department of Statistics (C.A.D.) and the Centre for Tropical Medicine and Global Health (P.H.), University of Oxford, Oxford, the Medical Research Council (MRC) Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London (C.A.D.), and the MRC Tropical Epidemiology Group, London School of Hygiene and Tropical Medicine (P.G.S.), London, and the Department of Mathematics and Statistics, Lancaster University, Lancaster (T.J.) - all in the United Kingdom; the Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania, Philadelphia (S.S.E.); the Department of Biostatistics, University of Washington (T.R.F., M.E.H.), and the Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center (M.E.H.) - both in Seattle; the Office of Vaccines Research and Review, Center for Biologics Evaluation and Research, Food and Drug Administration, Silver Spring (P.R.K.), and the Biostatistics Research Branch, National Institute of Allergy and Infectious Diseases, Bethesda (M.C.N.) - both in Maryland; Institut National de Recherche Biomédicale, Kinshasa, Democratic Republic of Congo (S.M., J.-J.M.-T.); and the Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute (R.W.), and the Department of Biostatistics, Harvard T.H. Chan School of Public Health (R.W., V.D.G.) - both in Boston
| | - Ira M Longini
- From the Department of Biostatistics, University of Florida, Gainesville (N.E.D., I.M.L.); the World Health Organization, Geneva (P.-S.G., A.M.H.-R.); the Department of Biostatistics, University of California, Los Angeles (R.B.); the Department of Biostatistics, Yale University, New Haven, CT (F.W.C.); the Department of Statistics (C.A.D.) and the Centre for Tropical Medicine and Global Health (P.H.), University of Oxford, Oxford, the Medical Research Council (MRC) Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London (C.A.D.), and the MRC Tropical Epidemiology Group, London School of Hygiene and Tropical Medicine (P.G.S.), London, and the Department of Mathematics and Statistics, Lancaster University, Lancaster (T.J.) - all in the United Kingdom; the Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania, Philadelphia (S.S.E.); the Department of Biostatistics, University of Washington (T.R.F., M.E.H.), and the Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center (M.E.H.) - both in Seattle; the Office of Vaccines Research and Review, Center for Biologics Evaluation and Research, Food and Drug Administration, Silver Spring (P.R.K.), and the Biostatistics Research Branch, National Institute of Allergy and Infectious Diseases, Bethesda (M.C.N.) - both in Maryland; Institut National de Recherche Biomédicale, Kinshasa, Democratic Republic of Congo (S.M., J.-J.M.-T.); and the Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute (R.W.), and the Department of Biostatistics, Harvard T.H. Chan School of Public Health (R.W., V.D.G.) - both in Boston
| | - Sabue Mulangu
- From the Department of Biostatistics, University of Florida, Gainesville (N.E.D., I.M.L.); the World Health Organization, Geneva (P.-S.G., A.M.H.-R.); the Department of Biostatistics, University of California, Los Angeles (R.B.); the Department of Biostatistics, Yale University, New Haven, CT (F.W.C.); the Department of Statistics (C.A.D.) and the Centre for Tropical Medicine and Global Health (P.H.), University of Oxford, Oxford, the Medical Research Council (MRC) Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London (C.A.D.), and the MRC Tropical Epidemiology Group, London School of Hygiene and Tropical Medicine (P.G.S.), London, and the Department of Mathematics and Statistics, Lancaster University, Lancaster (T.J.) - all in the United Kingdom; the Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania, Philadelphia (S.S.E.); the Department of Biostatistics, University of Washington (T.R.F., M.E.H.), and the Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center (M.E.H.) - both in Seattle; the Office of Vaccines Research and Review, Center for Biologics Evaluation and Research, Food and Drug Administration, Silver Spring (P.R.K.), and the Biostatistics Research Branch, National Institute of Allergy and Infectious Diseases, Bethesda (M.C.N.) - both in Maryland; Institut National de Recherche Biomédicale, Kinshasa, Democratic Republic of Congo (S.M., J.-J.M.-T.); and the Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute (R.W.), and the Department of Biostatistics, Harvard T.H. Chan School of Public Health (R.W., V.D.G.) - both in Boston
| | - Jean-Jacques Muyembe-Tamfum
- From the Department of Biostatistics, University of Florida, Gainesville (N.E.D., I.M.L.); the World Health Organization, Geneva (P.-S.G., A.M.H.-R.); the Department of Biostatistics, University of California, Los Angeles (R.B.); the Department of Biostatistics, Yale University, New Haven, CT (F.W.C.); the Department of Statistics (C.A.D.) and the Centre for Tropical Medicine and Global Health (P.H.), University of Oxford, Oxford, the Medical Research Council (MRC) Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London (C.A.D.), and the MRC Tropical Epidemiology Group, London School of Hygiene and Tropical Medicine (P.G.S.), London, and the Department of Mathematics and Statistics, Lancaster University, Lancaster (T.J.) - all in the United Kingdom; the Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania, Philadelphia (S.S.E.); the Department of Biostatistics, University of Washington (T.R.F., M.E.H.), and the Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center (M.E.H.) - both in Seattle; the Office of Vaccines Research and Review, Center for Biologics Evaluation and Research, Food and Drug Administration, Silver Spring (P.R.K.), and the Biostatistics Research Branch, National Institute of Allergy and Infectious Diseases, Bethesda (M.C.N.) - both in Maryland; Institut National de Recherche Biomédicale, Kinshasa, Democratic Republic of Congo (S.M., J.-J.M.-T.); and the Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute (R.W.), and the Department of Biostatistics, Harvard T.H. Chan School of Public Health (R.W., V.D.G.) - both in Boston
| | - Martha C Nason
- From the Department of Biostatistics, University of Florida, Gainesville (N.E.D., I.M.L.); the World Health Organization, Geneva (P.-S.G., A.M.H.-R.); the Department of Biostatistics, University of California, Los Angeles (R.B.); the Department of Biostatistics, Yale University, New Haven, CT (F.W.C.); the Department of Statistics (C.A.D.) and the Centre for Tropical Medicine and Global Health (P.H.), University of Oxford, Oxford, the Medical Research Council (MRC) Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London (C.A.D.), and the MRC Tropical Epidemiology Group, London School of Hygiene and Tropical Medicine (P.G.S.), London, and the Department of Mathematics and Statistics, Lancaster University, Lancaster (T.J.) - all in the United Kingdom; the Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania, Philadelphia (S.S.E.); the Department of Biostatistics, University of Washington (T.R.F., M.E.H.), and the Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center (M.E.H.) - both in Seattle; the Office of Vaccines Research and Review, Center for Biologics Evaluation and Research, Food and Drug Administration, Silver Spring (P.R.K.), and the Biostatistics Research Branch, National Institute of Allergy and Infectious Diseases, Bethesda (M.C.N.) - both in Maryland; Institut National de Recherche Biomédicale, Kinshasa, Democratic Republic of Congo (S.M., J.-J.M.-T.); and the Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute (R.W.), and the Department of Biostatistics, Harvard T.H. Chan School of Public Health (R.W., V.D.G.) - both in Boston
| | - Peter G Smith
- From the Department of Biostatistics, University of Florida, Gainesville (N.E.D., I.M.L.); the World Health Organization, Geneva (P.-S.G., A.M.H.-R.); the Department of Biostatistics, University of California, Los Angeles (R.B.); the Department of Biostatistics, Yale University, New Haven, CT (F.W.C.); the Department of Statistics (C.A.D.) and the Centre for Tropical Medicine and Global Health (P.H.), University of Oxford, Oxford, the Medical Research Council (MRC) Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London (C.A.D.), and the MRC Tropical Epidemiology Group, London School of Hygiene and Tropical Medicine (P.G.S.), London, and the Department of Mathematics and Statistics, Lancaster University, Lancaster (T.J.) - all in the United Kingdom; the Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania, Philadelphia (S.S.E.); the Department of Biostatistics, University of Washington (T.R.F., M.E.H.), and the Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center (M.E.H.) - both in Seattle; the Office of Vaccines Research and Review, Center for Biologics Evaluation and Research, Food and Drug Administration, Silver Spring (P.R.K.), and the Biostatistics Research Branch, National Institute of Allergy and Infectious Diseases, Bethesda (M.C.N.) - both in Maryland; Institut National de Recherche Biomédicale, Kinshasa, Democratic Republic of Congo (S.M., J.-J.M.-T.); and the Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute (R.W.), and the Department of Biostatistics, Harvard T.H. Chan School of Public Health (R.W., V.D.G.) - both in Boston
| | - Rui Wang
- From the Department of Biostatistics, University of Florida, Gainesville (N.E.D., I.M.L.); the World Health Organization, Geneva (P.-S.G., A.M.H.-R.); the Department of Biostatistics, University of California, Los Angeles (R.B.); the Department of Biostatistics, Yale University, New Haven, CT (F.W.C.); the Department of Statistics (C.A.D.) and the Centre for Tropical Medicine and Global Health (P.H.), University of Oxford, Oxford, the Medical Research Council (MRC) Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London (C.A.D.), and the MRC Tropical Epidemiology Group, London School of Hygiene and Tropical Medicine (P.G.S.), London, and the Department of Mathematics and Statistics, Lancaster University, Lancaster (T.J.) - all in the United Kingdom; the Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania, Philadelphia (S.S.E.); the Department of Biostatistics, University of Washington (T.R.F., M.E.H.), and the Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center (M.E.H.) - both in Seattle; the Office of Vaccines Research and Review, Center for Biologics Evaluation and Research, Food and Drug Administration, Silver Spring (P.R.K.), and the Biostatistics Research Branch, National Institute of Allergy and Infectious Diseases, Bethesda (M.C.N.) - both in Maryland; Institut National de Recherche Biomédicale, Kinshasa, Democratic Republic of Congo (S.M., J.-J.M.-T.); and the Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute (R.W.), and the Department of Biostatistics, Harvard T.H. Chan School of Public Health (R.W., V.D.G.) - both in Boston
| | - Ana M Henao-Restrepo
- From the Department of Biostatistics, University of Florida, Gainesville (N.E.D., I.M.L.); the World Health Organization, Geneva (P.-S.G., A.M.H.-R.); the Department of Biostatistics, University of California, Los Angeles (R.B.); the Department of Biostatistics, Yale University, New Haven, CT (F.W.C.); the Department of Statistics (C.A.D.) and the Centre for Tropical Medicine and Global Health (P.H.), University of Oxford, Oxford, the Medical Research Council (MRC) Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London (C.A.D.), and the MRC Tropical Epidemiology Group, London School of Hygiene and Tropical Medicine (P.G.S.), London, and the Department of Mathematics and Statistics, Lancaster University, Lancaster (T.J.) - all in the United Kingdom; the Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania, Philadelphia (S.S.E.); the Department of Biostatistics, University of Washington (T.R.F., M.E.H.), and the Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center (M.E.H.) - both in Seattle; the Office of Vaccines Research and Review, Center for Biologics Evaluation and Research, Food and Drug Administration, Silver Spring (P.R.K.), and the Biostatistics Research Branch, National Institute of Allergy and Infectious Diseases, Bethesda (M.C.N.) - both in Maryland; Institut National de Recherche Biomédicale, Kinshasa, Democratic Republic of Congo (S.M., J.-J.M.-T.); and the Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute (R.W.), and the Department of Biostatistics, Harvard T.H. Chan School of Public Health (R.W., V.D.G.) - both in Boston
| | - Victor De Gruttola
- From the Department of Biostatistics, University of Florida, Gainesville (N.E.D., I.M.L.); the World Health Organization, Geneva (P.-S.G., A.M.H.-R.); the Department of Biostatistics, University of California, Los Angeles (R.B.); the Department of Biostatistics, Yale University, New Haven, CT (F.W.C.); the Department of Statistics (C.A.D.) and the Centre for Tropical Medicine and Global Health (P.H.), University of Oxford, Oxford, the Medical Research Council (MRC) Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London (C.A.D.), and the MRC Tropical Epidemiology Group, London School of Hygiene and Tropical Medicine (P.G.S.), London, and the Department of Mathematics and Statistics, Lancaster University, Lancaster (T.J.) - all in the United Kingdom; the Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania, Philadelphia (S.S.E.); the Department of Biostatistics, University of Washington (T.R.F., M.E.H.), and the Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center (M.E.H.) - both in Seattle; the Office of Vaccines Research and Review, Center for Biologics Evaluation and Research, Food and Drug Administration, Silver Spring (P.R.K.), and the Biostatistics Research Branch, National Institute of Allergy and Infectious Diseases, Bethesda (M.C.N.) - both in Maryland; Institut National de Recherche Biomédicale, Kinshasa, Democratic Republic of Congo (S.M., J.-J.M.-T.); and the Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute (R.W.), and the Department of Biostatistics, Harvard T.H. Chan School of Public Health (R.W., V.D.G.) - both in Boston
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The role of data and safety monitoring boards in implementation trials: When are they justified? J Clin Transl Sci 2020; 4:229-232. [PMID: 32695494 PMCID: PMC7348012 DOI: 10.1017/cts.2020.19] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022] Open
Abstract
The National Institutes of Health requires data and safety monitoring boards (DSMBs) for all phase III clinical trials. The National Heart, Lung and Blood Institute requires DSMBs for all clinical trials involving more than one site and those involving cooperative agreements and contracts. These policies have resulted in the establishment of DSMBs for many implementation trials, with little consideration regarding the appropriateness of DSMBs and/or key adaptations needed by DSMBs to monitor data quality and participant safety. In this perspective, we review the unique features of implementation trials and reflect on key questions regarding the justification for DSMBs and their potential role and monitoring targets within implementation trials.
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Evans SR, Bigelow R, Chuang-Stein C, Ellenberg SS, Gallo P, He W, Jiang Q, Rockhold F. Presenting Risks and Benefits: Helping the Data Monitoring Committee Do Its Job. Ann Intern Med 2020; 172:119-125. [PMID: 31739312 DOI: 10.7326/m19-1491] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open
Abstract
Data monitoring committees (DMCs), or data and safety monitoring boards, protect clinical trial participants by conducting benefit-risk assessments during the course of a clinical trial. These evaluations may be improved by broader access to data and more effective analyses and presentation. Data monitoring committees should have access to all data, including efficacy data, at each interim review. The DMC reports should include graphical presentations that summarize benefits and harms in efficient ways. Benefit-risk assessments should include summaries that are consistent with the intention-to-treat principle and have a pragmatic focus. This article provides examples of graphical summaries that integrate benefits and harms, and proposes that such summaries become standard in DMC reports.
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Affiliation(s)
- Scott R Evans
- George Washington University, Rockville, Maryland (S.R.E.)
| | - Robert Bigelow
- Duke Clinical Research Institute, Durham, North Carolina (R.B.)
| | | | | | - Paul Gallo
- Novartis Pharmaceuticals, East Hanover, New Jersey (P.G.)
| | - Weili He
- AbbVie, North Chicago, Illinois (W.H.)
| | - Qi Jiang
- Seattle Genetics, Bothell, Washington (Q.J.)
| | - Frank Rockhold
- Duke University Medical Center, Durham, North Carolina (F.R.)
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Data Safety Monitoring Boards. Clin Trials 2020. [DOI: 10.1007/978-3-030-35488-6_11] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
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Lane JA, Gamble C, Cragg WJ, Tembo D, Sydes MR. A third trial oversight committee: Functions, benefits and issues. Clin Trials 2019; 17:106-112. [PMID: 31665920 PMCID: PMC7433693 DOI: 10.1177/1740774519881619] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/03/2022]
Abstract
Background/aims: Clinical trial oversight is central to the safety of participants and production of robust data. The United Kingdom Medical Research Council originally set out an oversight structure comprising three committees in 1998. The first committee, led by the trial team, is hands-on with trial conduct/operations (‘Trial Management Group’) and essential. The second committee (Data Monitoring Committee), usually completely independent of the trial, reviews accumulating trial evidence and is used by most later phase trials. The Independent Data Monitoring Committee makes recommendations to the third oversight committee. The third committee, (‘Trial Steering Committee’), facilitates in-depth interactions of independent and non-independent trial members and gives broader oversight (blinded to comparative analysis). We investigated the roles and functioning of the third oversight committee with multiple research methods. We reflect upon these findings to standardise the committee’s remit and operation and to potentially increase its usage. Methods: We utilised findings from our recent published suite of research on the third oversight committee to inform guideline revision. In brief, we conducted a survey of 38 United Kingdom–registered Clinical Trials Units, reviewed a cohort of 264 published trials, observed 8 third oversight committee meetings and interviewed 52 trialists. We convened an expert panel to discuss third oversight committees. Subsequently, we interviewed nine patient/lay third committee members and eight committee Chairs. Results: In the survey, most Clinical Trials Units required a third committee for all their trials (27/38, 71%) with independent members (ranging from 1 to 6). In the survey and interviews, the independence of the third committee was valued to make unbiased consideration of Independent Data Monitoring Committee recommendations and to advise on trial progress, protocol changes and recruitment issues in conjunction with the trial leadership. The third committee also advised funders and sponsors about trial continuation and represented patients and the public by including lay members. Of the cohort of 264 published trials, 144 reported a ‘steering’ committee (55%), but the independence of these members was not described so these may have been internal Trial Management Groups. Around two thirds of papers (60%) reported having an Independent Data Monitoring Committee and 26.9% neither a steering nor an Independent Data Monitoring Committee. However, before revising the third committee charter (Terms of Reference), greater standardisation is needed around defining member independence, composition, primacy of decision-making, interactions with other committees and the lifespan. Conclusion: A third oversight committee has benefits for trial oversight and conduct, and a revised charter will facilitate greater standardisation and wider adoption.
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Affiliation(s)
- J Athene Lane
- Bristol Randomised Trials Collaboration, Bristol Trials Centre, Bristol University, Bristol, UK.,MRC ConDucT-II Hub for Trials Methodology Research, Bristol Medical School, Bristol University, Bristol, UK
| | - Carrol Gamble
- Liverpool Clinical Trials Centre, University of Liverpool, Liverpool, UK.,MRC North West Hub for Trials Methodology Research, University of Liverpool, Liverpool, UK
| | - William J Cragg
- MRC Clinical Trials Unit at UCL, University College London (UCL), London, UK.,MRC London Hub for Trials Methodology Research, London, UK.,Clinical Trials Research Unit, Leeds Institute of Clinical Trials Research, University of Leeds, Leeds, UK
| | - Doreen Tembo
- National Institute for Health Research, Evaluation, Trials and Studies Coordinating Centre, Southampton, UK
| | - Matthew R Sydes
- MRC Clinical Trials Unit at UCL, University College London (UCL), London, UK.,MRC London Hub for Trials Methodology Research, London, UK
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Ensuring trial conduct is consistent with trial design: assumption is the enemy of quality. Trials 2019; 20:416. [PMID: 31291974 PMCID: PMC6617665 DOI: 10.1186/s13063-019-3516-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2018] [Accepted: 06/11/2019] [Indexed: 01/23/2023] Open
Abstract
‘Assumptions are made and most assumptions are wrong’ (Albert Einstein) Clinical trial conduct must be consistent with trial design, yet conducting the trial according to plan remains a major challenge. We discuss the importance of optimal co-applicant team formation in trial leadership, appropriate delegation of tasks and staff supervision arrangements. Finally, we discuss five standard documents which we believe require particular attention. With appropriate engagement by or with co-applicants during the preparation of these five standard documents, we believe many of the pitfalls trials commonly experience can be avoided. The risks inherent in failing to identify and address mistaken assumptions during the preparation of these documents are discussed and recommendations for best practice suggested.
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Tannock LR, Barton-Baxter M, Stoops WW. Creation of an institutional semi-independent data monitoring committee. Clin Trials 2019; 16:523-530. [PMID: 31257918 DOI: 10.1177/1740774519859876] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
BACKGROUND A major goal of the National Institutes of Health's Clinical and Translational Science Award program is to facilitate clinical research and enhance the transition of basic to clinical research. As such, a number of Clinical and Translational Science Award centers have developed services to facilitate the conduct of clinical research, including support with fulfilling regulatory requirements. METHODS The University of Kentucky sought to establish an institutional semi-independent monitoring committee to provide oversight for clinical research studies per National Institutes of Health requirements and recommendations. Our semi-independent monitoring committee was initiated in 2010. RESULTS Since the inception of our semi-independent monitoring committee we have restructured its operations and protocols to improve efficiency. This article discusses our experiences with semi-independent monitoring committee creation and growth. CONCLUSION This article summarizes our experience in creating and maturing an institutional data monitoring committee.
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Affiliation(s)
- Lisa R Tannock
- Department of Internal Medicine, University of Kentucky, Lexington, KY, USA.,Barnstable Brown Diabetes Center, University of Kentucky, Lexington, KY, USA.,Center for Clinical and Translational Science, University of Kentucky, Lexington, KY, USA
| | - Marietta Barton-Baxter
- Center for Clinical and Translational Science, University of Kentucky, Lexington, KY, USA
| | - William W Stoops
- Center for Clinical and Translational Science, University of Kentucky, Lexington, KY, USA.,Department of Behavioral Science, University of Kentucky, Lexington, KY, USA
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Bhattacharyya A, Gallo P, Crisp A, LaVange L, Molenberghs G, Pétavy F, Seltzer J. The changing landscape of data monitoring committees-Perspectives from regulators, members, and sponsors. Biom J 2018; 61:1232-1241. [PMID: 30589102 DOI: 10.1002/bimj.201700307] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2017] [Revised: 11/30/2018] [Accepted: 12/02/2018] [Indexed: 11/06/2022]
Abstract
Data Monitoring Committees (DMCs) are an integral part of clinical drug development. Their use has evolved along with changing study designs and regulatory expectations, which has associated statistical and ethical implications. Although there is guidance from the different regulatory agencies, there are opportunities to bring more consistency to address practical issues of establishing and operating a DMC. Challenging issues include defining the scope of DMC decisions, the regulatory requirements and expectations, the perceived independence of DMCs, the specific focus primarily on safety, etc. Wider use of adaptive clinical trial designs in recent years introduce additional challenges in terms of trial governance and the complexity of DMC activities. A panel comprised of clinical and statistical experts from across academia, industry, and regulatory agencies shared their experience and thoughts on the importance of these aspects and offered perspectives on the future of the DMCs. This paper documents the thinking from the panel session at the CEN-ISBS conference held in Vienna, Austria, 2017.
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Affiliation(s)
| | - Paul Gallo
- Novartis, One Health Plaza, East Hanover, NJ, USA
| | | | - Lisa LaVange
- University of North Carolina, Department of Biostatistics, CB# 8030, Chapel Hill, NC, USA
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Davis B, Kerr D, Maguire M, Sanders C, Snapinn S, Wittes J. University of Pennsylvania 10th annual conference on statistical issues in clinical trials: Current issues regarding data and safety monitoring committees in clinical trials (morning panel session). Clin Trials 2018; 15:335-351. [DOI: 10.1177/1740774518780434] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
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Abstract
With the initiation in the late 1960s of the data and safety monitoring board or equivalently the data monitoring committee in randomized clinical trials came the need for interim statistical reports for these committees to review for study conduct and early evidence of harm or overwhelming evidence of benefit, perhaps leading to early trial termination. Initially, the statistical team was part of the data coordinating center for the trial. Later, starting in the early 1990s in many industry-sponsored trials, this statistical unit was separated organizationally from the team that collected and managed the data. This unit, often referred to as the statistical data analysis center, prepares reports for the data monitoring committee, which cover study conduct, data quality and completeness, primary and secondary outcomes, and safety measures by study arm in an unblinded fashion. The role of the statistical data analysis center is critical to any well-functioning data monitoring committee. With the proliferation of data monitoring committees has grown the need for many more well-trained and experienced statistical data analysis centers. In my experience, some such units perform their tasks extremely well but many do not. There is a tremendous need and opportunity to provide training for statistical data analysis centers, and what sponsors and data monitoring committees should expect from statistical data analysis centers.
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Affiliation(s)
- David DeMets
- Department of Biostatistics & Medical Informatics, University of Wisconsin-Madison, Madison, WI, USA
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Abstract
Maintaining confidentiality of emerging data and ensuring the independence of Data Monitoring Committees are best practices of considerable importance to the ability of these committees to achieve their mission of safeguarding the interests of study participants and enhancing the integrity and credibility of clinical trials. Even with the wide recognition of these principles, there are circumstances where confidentiality issues remain challenging, controversial or inconsistently addressed. First, consider settings where a clinical trial's interim data could provide the evidence regulatory authorities require for decisions about marketing approval, yet where such a trial would be continued post-approval to provide more definitive evidence about principal safety and/or efficacy outcomes. In such settings, data informative about the longer term objectives of the trial should remain confidential until pre-specified criteria for trial completion have been met. Second, for those other than Data Monitoring Committee members, access to safety and efficacy outcomes during trial conduct, even when presented as data pooled across treatment arms, should be on a limited "need to know" basis relating to the ability to carry out ethical or scientific responsibilities in the conduct of the trial. Third, Data Monitoring Committee members should have access to unblinded efficacy and safety data throughout the trial to enable timely and informed judgments about risks and benefits. Fourth, it should be recognized that a mediator potentially could be useful in rare settings where the Data Monitoring Committee would have serious ethical or scientific concerns about the sponsor's dissemination or lack of dissemination of information. Data Monitoring Committee Contract Agreements, Indemnification Agreements and Charters should be developed in a manner to protect Data Monitoring Committee members and their independence, in order to enhance the Data Monitoring Committee's ability to effectively address their mission.
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Affiliation(s)
- Thomas R Fleming
- 1 Department of Biostatistics, University of Washington, Seattle, WA, USA
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Neaton JD, Grund B, Wentworth D. How to construct an optimal interim report: What the data monitoring committee does and doesn’t need to know. Clin Trials 2018; 15:359-365. [PMID: 29552920 DOI: 10.1177/1740774518764449] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
Background: Data monitoring committees for randomized clinical trials have the responsibility of safeguarding interests of trial participants. To do so, the data monitoring committee must receive reports on safety and efficacy to assess risk/benefit and on trial conduct to ensure that the study can achieve its goals. This article outlines the key components of reports to the data monitoring committee and the important role of the unblinded statistician in preparing those reports. Methods: Most data monitoring committee meetings include open and closed sessions. For each session, there is a report of interim results. The open session is attended by the sponsor and lead investigators, including the statistician(s) responsible for the trial design. These investigators are blinded to the interim treatment comparisons. The closed session is attended by the data monitoring committee members and by the statistician(s) who prepared the closed report. These individuals are unblinded to interim treatment comparisons and therefore are not involved in study design changes. The optimal content of data monitoring committee reports and qualifications of the unblinded statistician(s) are discussed. Reports: Open reports should include responses to data monitoring committee recommendations, a synopsis of the protocol, a review of the protocol history and amendments, and information on enrollment, baseline characteristics, completeness of follow-up, and data quality. The open report is also a vehicle through which the sponsor and investigators should inform the data monitoring committee of relevant external information. Data in the open report are pooled over the treatment groups. The open report should not include data summaries by treatment group. The closed report should include a written summary with references to key tables and figures and methods used to prepare them. Tables and figures should summarize baseline characteristics, follow-up completeness, treatment adherence, and major safety and efficacy outcomes by treatment group. Text summaries should accompany the tables and figures. The data monitoring committee monitoring history (e.g. treatment differences at previous meetings) should be summarized. The unblinded statistician preparing the closed report should be familiar with the protocol and data collection plan and be capable of customizing the report to the current stage of the trial. This includes anticipating questions that may arise during the data monitoring committee review and pro-actively including data summaries to address these questions. Conclusions: There is considerable variation in the quality of open and closed data monitoring committee reports. Open and closed data monitoring committee reports should be concise, up to date, and informative. To achieve this, unblinded statisticians responsible for preparing closed data monitoring committee reports should be familiar with the statistical methods, the trial protocol, and the data collection plan. They should be capable of anticipating questions from the data monitoring committee and responding to requests for additional analyses.
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Affiliation(s)
- James D Neaton
- Division of Biostatistics, School of Public Health, University of Minnesota, Minneapolis, MN, USA
| | - Birgit Grund
- School of Statistics, University of Minnesota, Minneapolis, MN, USA
| | - Deborah Wentworth
- Division of Biostatistics, School of Public Health, University of Minnesota, Minneapolis, MN, USA
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Buhr KA, Downs M, Rhorer J, Bechhofer R, Wittes J. Reports to Independent Data Monitoring Committees: An Appeal for Clarity, Completeness, and Comprehensibility. Ther Innov Regul Sci 2017; 52:459-468. [PMID: 29714543 DOI: 10.1177/2168479017739268] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Abstract
BACKGROUND Organizations presenting reports to independent data monitoring committees (IDMCs) should present data in a way that facilitates the ability of the IDMC to make informed judgments about the trial. METHODS This paper reviews reports to IDMCs and suggests approaches an independent statistical reporting group (ISRG) might take to prepare clear, complete, and comprehensible reports. RESULTS Sensible reporting by an ISRG and informed decision making by an IDMC require a productive partnership between the quantitative and clinical disciplines involved in a clinical trial. IDMC reports differ in structure and purpose from clinical study reports that summarize data at the end of a trial. The ISRG must have intellectual independence, recognizing that although the sponsor may be paying the bills, the ISRG is responsible to the IDMC. Ideally, it should have access to all data from the trial and should be capable of responding to requests from the IDMC without the sponsor's specific permission. The ISRG and sponsor must understand the differences between clean data at the end of the trial and data collected during the trial. To perform its role most effectively, the ISRG must collaborate with sponsor and IDMC clinicians to become conversant with the disease area, the product's mechanism of action, and the clinical relevance of important outcome measures. CONCLUSIONS An IDMC is best served by an independent ISRG that will prepare clear, complete, and comprehensible reports. Given the complexities of interim data and IDMC requirements, the ISRG must be an active and informed participant in the monitoring process.
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Affiliation(s)
- Kevin A Buhr
- 1 Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, WI, USA
| | - Matthew Downs
- 2 Statistics Collaborative, Inc, Washington, DC, USA
| | | | - Robin Bechhofer
- 1 Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, WI, USA
| | - Janet Wittes
- 2 Statistics Collaborative, Inc, Washington, DC, USA
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