Adaptive Trials: Acceptability, Versatility and Utility
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The Statistical Significance of Randomized Controlled Trial Results Is Frequently Fragile: a Case for a Fragility Index
The statistical significance of randomized controlled trial results is frequently fragile: A case for a Fragility Index Walsh, M., Srinathan, S. K., McAuley, D. F., Mrkobrada, M., Levine, O., Ribic, C., Molnar, A. O., Dattani, N. D., Burke, A., Guyatt, G., Thabane, L., Walter, S. D., Pogue, J., & Devereaux, P. J. (2014). The statistical significance of randomized controlled trial results is frequently fragile: A case for a Fragility Index. Journal of Clinical Epidemiology, 67(6), 622-628. https://doi.org/10.1016/j.jclinepi.2013.10.019 Published in: Journal of Clinical Epidemiology Document Version: Publisher's PDF, also known as Version of record Queen's University Belfast - Research Portal: Link to publication record in Queen's University Belfast Research Portal Publisher rights 2014 The Authors. Published by Elsevier Inc. This is an open access article published under a Creative Commons Attribution-NonCommercial-NoDerivs License (https://creativecommons.org/licenses/by-nc-nd/3.0/), which permits distribution and reproduction for non-commercial purposes, provided the author and source are cited. General rights Copyright for the publications made accessible via the Queen's University Belfast Research Portal is retained by the author(s) and / or other copyright owners and it is a condition of accessing these publications that users recognise and abide by the legal requirements associated with these rights. Take down policy The Research Portal is Queen's institutional repository that provides access to Queen's research output. Every effort has been made to ensure that content in the Research Portal does not infringe any person's rights, or applicable UK laws. -
Evolution of Clinical Trials Throughout History
Evolution of clinical trials throughout history Emma M. Nellhaus1, Todd H. Davies, PhD1 Author Affiliations: 1. Office of Research and Graduate Education, Marshall University Joan C. Edwards School of Medicine, Huntington, West Virginia The authors have no financial disclosures to declare and no conflicts of interest to report. Corresponding Author: Todd H. Davies, PhD Director of Research Development and Translation Marshall University Joan C. Edwards School of Medicine Huntington, West Virginia Email: [email protected] Abstract The history of clinical research accounts for the high ethical, scientific, and regulatory standards represented in current practice. In this review, we aim to describe the advances that grew from failures and provide a comprehensive view of how the current gold standard of clinical practice was born. This discussion of the evolution of clinical trials considers the length of time and efforts that were made in order to designate the primary objective, which is providing improved care for our patients. A gradual, historic progression of scientific methods such as comparison of interventions, randomization, blinding, and placebos in clinical trials demonstrates how these techniques are collectively responsible for a continuous advancement of clinical care. Developments over the years have been ethical as well as clinical. The Belmont Report, which many investigators lack appreciation for due to time constraints, represents the pinnacle of ethical standards and was developed due to significant misconduct. Understanding the history of clinical research may help investigators value the responsibility of conducting human subjects’ research. Keywords Clinical Trials, Clinical Research, History, Belmont Report In modern medicine, the clinical trial is the gold standard and most dominant form of clinical research. -
Why Do You Need a Biostatistician? Antonia Zapf1* , Geraldine Rauch2 and Meinhard Kieser3
Zapf et al. BMC Medical Research Methodology (2020) 20:23 https://doi.org/10.1186/s12874-020-0916-4 DEBATE Open Access Why do you need a biostatistician? Antonia Zapf1* , Geraldine Rauch2 and Meinhard Kieser3 Abstract The quality of medical research importantly depends, among other aspects, on a valid statistical planning of the study, analysis of the data, and reporting of the results, which is usually guaranteed by a biostatistician. However, there are several related professions next to the biostatistician, for example epidemiologists, medical informaticians and bioinformaticians. For medical experts, it is often not clear what the differences between these professions are and how the specific role of a biostatistician can be described. For physicians involved in medical research, this is problematic because false expectations often lead to frustration on both sides. Therefore, the aim of this article is to outline the tasks and responsibilities of biostatisticians in clinical trials as well as in other fields of application in medical research. Keywords: Medical research, Biostatistician, Tasks, Responsibilities Background Biometric Society (IBS) provides a definition of biomet- What is a biostatistician, what does he or she actually do rics as a ‘field of development of statistical and mathem- and what distinguishes him or her from, for example, an atical methods applicable in the biological sciences’ [2]. epidemiologist? If we would ask this our main cooper- In here, we will focus on (human) medicine as area of ation partners like physicians or biologists, they probably application, but the results can be easily transferred to could not give a satisfying answer. This is problematic the other biological sciences like, for example, agricul- because false expectations often lead to frustration on ture or ecology. -
U.S. Investments in Medical and Health Research and Development 2013 - 2017 Advocacy Has Helped Bring About Five Years of Much-Needed Growth in U.S
Fall 2018 U.S. Investments in Medical and Health Research and Development 2013 - 2017 Advocacy has helped bring about five years of much-needed growth in U.S. medical and health research investment. More advocacy is critical now to ensure our nation steps up in response to health threats that we can—we must—overcome. More Than Half Favor Doubling Federal Spending on Medical Research Do you favor or oppose doubling federal spending on medical research over the next five years? 19% Not Sure 23% 8% Strongly favor Strongly oppose 16% 35% Somewhat oppose Somewhat favor Source: A Research!America survey of U.S. adults conducted in partnership with Zogby Analytics in January 2018. Research!America 3 Introduction Investment1 in medical and health research and development (R&D) in the U.S. grew by $38.8 billion or 27% from 2013 to 2017. Industry continues to invest more than any other sector, accounting for 67% of total spending in 2017, followed by the federal government at 22%. Federal investments increased from 2016 to 2017, the second year of growth after a dip from 2014 to 2015. Overall, federal investment increased by $6.1 billion or 18.4% from 2013 to 2017, but growth has been uneven across federal health agencies. Investment by other sectors, including academic and research institutions, foundations, state and local governments, and voluntary health associations and professional societies, also increased from 2013 to 2017. Looking ahead, medical and health R&D spending is expected to move in an upward trajectory in 2018 but will continue to fall short relative to the health and economic impact of major health threats. -
Clinical Research Services
Clinical Research Services Conducting efficient, innovative clinical research from initial planning to closeout WHY LEIDOS LIFE SCIENCES? In addition to developing large-scale technology programs for U.S. federal f Leidos has expertise agencies with a focus on health, Leidos provides a broad range of clinical supporting all product services and solutions to researchers, product sponsors, U.S. government development phases agencies, and other biomedical enterprises, hospitals, and health systems. for vaccines, drugs, and Our broad research experience enables us to support programs throughout biotherapeutics the development life cycle: from concept through the exploratory, f Leidos understands the development, pre-clinical, and clinical phases, as well as with product need to control clinical manufacturing and launching. Leidos designs and develops customized project scope, timelines, solutions that support groundbreaking medical research, optimize business and cost while remaining operations, and expedite the discovery of safe and effective medical flexible amidst shifting products. We apply our technical knowledge and experience in selecting research requirements institutions, clinical research organizations, and independent research f Leidos remains vendor- facilities to meet the specific needs of each clinical study. We also manage neutral while fostering and team integration, communication, and contracts throughout the project. managing collaborations Finally, Leidos has a proven track record of ensuring that research involving with -
Adaptive Designs in Clinical Trials: Why Use Them, and How to Run and Report Them Philip Pallmann1* , Alun W
Pallmann et al. BMC Medicine (2018) 16:29 https://doi.org/10.1186/s12916-018-1017-7 CORRESPONDENCE Open Access Adaptive designs in clinical trials: why use them, and how to run and report them Philip Pallmann1* , Alun W. Bedding2, Babak Choodari-Oskooei3, Munyaradzi Dimairo4,LauraFlight5, Lisa V. Hampson1,6, Jane Holmes7, Adrian P. Mander8, Lang’o Odondi7, Matthew R. Sydes3,SofíaS.Villar8, James M. S. Wason8,9, Christopher J. Weir10, Graham M. Wheeler8,11, Christina Yap12 and Thomas Jaki1 Abstract Adaptive designs can make clinical trials more flexible by utilising results accumulating in the trial to modify the trial’s course in accordance with pre-specified rules. Trials with an adaptive design are often more efficient, informative and ethical than trials with a traditional fixed design since they often make better use of resources such as time and money, and might require fewer participants. Adaptive designs can be applied across all phases of clinical research, from early-phase dose escalation to confirmatory trials. The pace of the uptake of adaptive designs in clinical research, however, has remained well behind that of the statistical literature introducing new methods and highlighting their potential advantages. We speculate that one factor contributing to this is that the full range of adaptations available to trial designs, as well as their goals, advantages and limitations, remains unfamiliar to many parts of the clinical community. Additionally, the term adaptive design has been misleadingly used as an all-encompassing label to refer to certain methods that could be deemed controversial or that have been inadequately implemented. We believe that even if the planning and analysis of a trial is undertaken by an expert statistician, it is essential that the investigators understand the implications of using an adaptive design, for example, what the practical challenges are, what can (and cannot) be inferred from the results of such a trial, and how to report and communicate the results. -
Good Statistical Practices for Contemporary Meta-Analysis: Examples Based on a Systematic Review on COVID-19 in Pregnancy
Review Good Statistical Practices for Contemporary Meta-Analysis: Examples Based on a Systematic Review on COVID-19 in Pregnancy Yuxi Zhao and Lifeng Lin * Department of Statistics, Florida State University, Tallahassee, FL 32306, USA; [email protected] * Correspondence: [email protected] Abstract: Systematic reviews and meta-analyses have been increasingly used to pool research find- ings from multiple studies in medical sciences. The reliability of the synthesized evidence depends highly on the methodological quality of a systematic review and meta-analysis. In recent years, several tools have been developed to guide the reporting and evidence appraisal of systematic reviews and meta-analyses, and much statistical effort has been paid to improve their methodological quality. Nevertheless, many contemporary meta-analyses continue to employ conventional statis- tical methods, which may be suboptimal compared with several alternative methods available in the evidence synthesis literature. Based on a recent systematic review on COVID-19 in pregnancy, this article provides an overview of select good practices for performing meta-analyses from sta- tistical perspectives. Specifically, we suggest meta-analysts (1) providing sufficient information of included studies, (2) providing information for reproducibility of meta-analyses, (3) using appro- priate terminologies, (4) double-checking presented results, (5) considering alternative estimators of between-study variance, (6) considering alternative confidence intervals, (7) reporting predic- Citation: Zhao, Y.; Lin, L. Good tion intervals, (8) assessing small-study effects whenever possible, and (9) considering one-stage Statistical Practices for Contemporary methods. We use worked examples to illustrate these good practices. Relevant statistical code Meta-Analysis: Examples Based on a is also provided. -
Short List of Commonly Used Acronyms in Clinical Research
Short List of Commonly Used Acronyms in Clinical Research ACRP Association of Clinical Research Professionals AE Adverse Event ADR Adverse Drug Reaction AMA American Medical Association BAA Business Associate Agreement BIND Biological IND CA Coverage Analysis CAP College of American Pathologists CBCTN Community Based Clinical Trials Network CCRA Certified Clinical Research Associate (ACRP) CCRC Certified Clinical Research Coordinator (ACRP) CCRT Center for Clinical Research & Technology CCRP Certified Clinical Research Professional (SoCRA) CDA Confidential Disclosure Agreement CDC Center for Disease Control CFR Code of Federal Regulations CIRBI Center for IRB Intelligence CITI Collaborative Institutional Training Initiative CLIA Clinical Laboratory Improvement Amendments CME Continuing Medical Education CMS Central Management System COI Conflict of Interest CRA Clinical Research Associate CRC Clinical Research Coordinator CREC Continuing Research Education Credit CRF Case Report Form CRO Clinical Research Organization CTA Clinical Trial Agreement CTSC Clinical & Translational Science Collaborative CV Curriculum Vitae DCF Data Correction Form / Data Clarification Form DEA Drug Enforcement Agency (law enforcement division of FDA) DHHS Department of Health and Human Services DOS Date of Service DSMB or Data and Safety Monitoring Board (Plan or Committee) DSMP/C EAB Ethical Advisory Board (similar to IRB, used by other nations) EDC Electronic Data Capture FDA Food and Drug Administration FDA-482 Notice of Inspection FDA-483 Notice of Adverse -
A Framework to Assess Empirical Reproducibility in Biomedical Research Leslie D
McIntosh et al. BMC Medical Research Methodology (2017) 17:143 DOI 10.1186/s12874-017-0377-6 RESEARCH ARTICLE Open Access Repeat: a framework to assess empirical reproducibility in biomedical research Leslie D. McIntosh1, Anthony Juehne1*, Cynthia R. H. Vitale2, Xiaoyan Liu1, Rosalia Alcoser1, J. Christian Lukas1 and Bradley Evanoff3 Abstract Background: The reproducibility of research is essential to rigorous science, yet significant concerns of the reliability and verifiability of biomedical research have been recently highlighted. Ongoing efforts across several domains of science and policy are working to clarify the fundamental characteristics of reproducibility and to enhance the transparency and accessibility of research. Methods: The aim of the proceeding work is to develop an assessment tool operationalizing key concepts of research transparency in the biomedical domain, specifically for secondary biomedical data research using electronic health record data. The tool (RepeAT) was developed through a multi-phase process that involved coding and extracting recommendations and practices for improving reproducibility from publications and reports across the biomedical and statistical sciences, field testing the instrument, and refining variables. Results: RepeAT includes 119 unique variables grouped into five categories (research design and aim, database and data collection methods, data mining and data cleaning, data analysis, data sharing and documentation). Preliminary results in manually processing 40 scientific manuscripts indicate components of the proposed framework with strong inter-rater reliability, as well as directions for further research and refinement of RepeAT. Conclusions: The use of RepeAT may allow the biomedical community to have a better understanding of the current practices of research transparency and accessibility among principal investigators. -
A Framework for Simplification of Clinical Trials in Regulated Medical Devices
A Framework for Simplification of Clinical Trials in Regulated Medical Devices Medical Device Innovation Consortium (MDIC) Clinical Trial Innovation and Reformation (CTIR) Committee Rick Kuntz, MD, MSc, Medtronic – CTIR Chair Karim Benali, MD, MSc, Abiomed Willian D. Voorhees, III, PhD, Med Institute Susan Alpert, MD, PhD Wes Cetnarowski, MD, B Braun Chip Hance, Creganna Medical Stephanie Christopher, MDIC Bill Murray, MDIC Dan Schwartz, MDIC September 2016 www.mdic.org MDIC Framework for Simplification of Clinical Trials in Regulated Medical Devices The Medical Device Innovation Consortium (MDIC) is the first-ever public-private partnership created with the sole objective of advancing the regulatory science around the development and assessment of medical devices. Members of MDIC share a vision of providing U.S. citizens with timely access to high-quality, safe, and effective medical devices without unnecessary delay. Background on the MDIC CTIR Committee The MDIC Clinical Trial Innovation & Reform Steering Committee (CTIR Committee) was established to address issues of growing inefficiencies in the clinical trial ecosystem for the medical device industry. MDIC aims to improve the medical device clinical trial enterprise, driving a coordinated effort to fundamentally change how medical research is conducted. Clinical Trial Simplification is one of the projects the CTIR initiated to achieve their goal. The MDIC CTIR Committee comprises leaders from the medical device industry, Food & Drug Association (FDA), National Institutes of Health (NIH), patient groups, and academia. Problem Statement Presently, medical device companies following the FDA Pre-Market Approval (PMA) pathway employ increasingly complex clinical trial structures that are inefficient and burden the clinical research and regulatory evaluation processes. -
Medical Statistics PDF File 9
M249 Practical modern statistics Medical statistics About this module M249 Practical modern statistics uses the software packages IBM SPSS Statistics (SPSS Inc.) and WinBUGS, and other software. This software is provided as part of the module, and its use is covered in the Introduction to statistical modelling and in the four computer books associated with Books 1 to 4. This publication forms part of an Open University module. Details of this and other Open University modules can be obtained from the Student Registration and Enquiry Service, The Open University, PO Box 197, Milton Keynes MK7 6BJ, United Kingdom (tel. +44 (0)845 300 60 90; email [email protected]). Alternatively, you may visit the Open University website at www.open.ac.uk where you can learn more about the wide range of modules and packs offered at all levels by The Open University. To purchase a selection of Open University materials visit www.ouw.co.uk, or contact Open University Worldwide, Walton Hall, Milton Keynes MK7 6AA, United Kingdom for a brochure (tel. +44 (0)1908 858779; fax +44 (0)1908 858787; email [email protected]). Note to reader Mathematical/statistical content at the Open University is usually provided to students in printed books, with PDFs of the same online. This format ensures that mathematical notation is presented accurately and clearly. The PDF of this extract thus shows the content exactly as it would be seen by an Open University student. Please note that the PDF may contain references to other parts of the module and/or to software or audio-visual components of the module. -
Some Aspects of Meningococcal Virulence: a Report to the Medical
SOME ASPECTS OF MENINGOCOCCAL VIRULENCE A REPORT TO THE MEDICAL RESEARCH COUNCIL ON WORK CARRIED OUT AT THE UNIVERSITY OF CAMBRIDGE FIELD LABORATORIES BY E. G. D. MUREAY. CONTENTS. PAGE I. Introduction 175 II. Conditions influencing the determination of the minimal lethal dose . 177 (a) Viability and purity of culture ....... 178 (b) The health of the experimental animal 178 (c) The general influence of the nutrient medium . .178 (d) The correct measurement of the dose of living cocci . 180 (e) The strict correlation of dose to body weight of animal . 180 (/) The influence of sub-culture and age - 181 (g) Summary 183 III. The graduation of doses and the selection of the minimal lethal dose . 183 IV. The variation in virulence of freshly isolated strains .... 185 V. The fate of meningococci injected intraperitoneally into mice . 186 VI. Interference with the activity of the leucocytes and the peritoneal folds 190 VII. The raising of the virulence of the meningococcus by animal passage m. 194 VIII. The raising of the virulence of the meningococcus in vitro . 196 IX. The influence of desiccation, on virulence ...... 202 X. Discussion ........... 203 XI. Conclusions 206 XII. References 207 I. INTRODUCTION. "VIRULENCE" is an ill-defined term and its use frequently gives rise to dis- putes, which remain unresolved because the disputants have no common basis other than that the term applies to organisms which cause disease. Thus it is imperative that the writer clearly defines the meaning of the term virulence as used in this paper, that the issue may not be confused by the reader approaching the subject from a different point of view.