Statistical Monitoring Of Clinical Trials
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| Author | : Lemuel A. Moyé |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 284 |
| Release | : 2006 |
| Genre | : Health & Fitness |
| ISBN | : 9780387277813 |
Statistical Monitoring of Clinical Trials: Fundamentals for Investigators introduces the investigator and statistician to monitoring procedures in clinical research. Clearly presenting the necessary background with limited use of mathematics, this book increases the knowledge, experience, and intuition of investigations in the use of these important procedures now required by the many clinical research efforts. The author provides motivated clinical investigators the background, correct use, and interpretation of these monitoring procedures at an elementary statistical level. He defines terms commonly used such as group sequential procedures and stochastic curtailment in non-mathematical language and discusses the commonly used procedures of Pocock, O’Brien–Fleming, and Lan–DeMets. He discusses the notions of conditional power, monitoring for safety and futility, and monitoring multiple endpoints in the study. The use of monitoring clinical trials is introduced in the context of the evolution of clinical research and one chapter is devoted to the more recent Bayesian procedures. Dr. Lemuel A. Moyé, M.D., Ph.D. is a physician and a biostatistician at the University of Texas School of Public Health. He is a diplomat of the National Board of Medical Examiners and is currently Professor of Biostatistics at the University of Texas School of Public Health in Houston where he holds a full time faculty position. Dr. Moyé has carried out cardiovascular research for twenty years and continues to be involved in the design, execution and analysis of clinical trials, both reporting to and serving on many Data Monitoring Committees. He has served in several clinical trials sponsored by both the U.S. government and private industry. In addition, Dr. Moyé has served as statistician/epidemiologist for six years on both the Cardiovascular and Renal Drug Advisory Committee to the Food and Drug Administration and the Pharmacy Sciences Advisory Committee to the FDA. He has published over 120 manuscripts in peer-reviewed literature that discuss the design, execution and analysis of clinical research. He authored Statistical Reasoning in Medicine: The Intuitive P-value Primer (Springer, 2000) and Multiple Analysis in Clinical Trials: Fundamentals for Investigators (Springer, 2003).
| Author | : Michael A. Proschan |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 263 |
| Release | : 2006-12-31 |
| Genre | : Medical |
| ISBN | : 0387449701 |
The approach taken in this book is, to studies monitored over time, what the Central Limit Theorem is to studies with only one analysis. Just as the Central Limit Theorem shows that test statistics involving very different types of clinical trial outcomes are asymptotically normal, this book shows that the joint distribution of the test statistics at different analysis times is asymptotically multivariate normal with the correlation structure of Brownian motion ("the B-value") – irrespective of the test statistic. Thus, this book offers statisticians an accessible, incremental approach to understanding Brownian motion as related to clinical trials.
| Author | : Thomas D. Cook |
| Publisher | : CRC Press |
| Total Pages | : 465 |
| Release | : 2007-11-19 |
| Genre | : Mathematics |
| ISBN | : 1584880279 |
Clinical trials have become essential research tools for evaluating the benefits and risks of new interventions for the treatment and prevention of diseases, from cardiovascular disease to cancer to AIDS. Based on the authors’ collective experiences in this field, Introduction to Statistical Methods for Clinical Trials presents various statistical topics relevant to the design, monitoring, and analysis of a clinical trial. After reviewing the history, ethics, protocol, and regulatory issues of clinical trials, the book provides guidelines for formulating primary and secondary questions and translating clinical questions into statistical ones. It examines designs used in clinical trials, presents methods for determining sample size, and introduces constrained randomization procedures. The authors also discuss how various types of data must be collected to answer key questions in a trial. In addition, they explore common analysis methods, describe statistical methods that determine what an emerging trend represents, and present issues that arise in the analysis of data. The book concludes with suggestions for reporting trial results that are consistent with universal guidelines recommended by medical journals. Developed from a course taught at the University of Wisconsin for the past 25 years, this textbook provides a solid understanding of the statistical approaches used in the design, conduct, and analysis of clinical trials.
| Author | : Michael A. Proschan |
| Publisher | : CRC Press |
| Total Pages | : 276 |
| Release | : 2021-11-24 |
| Genre | : Mathematics |
| ISBN | : 1351673106 |
Statistical Thinking in Clinical Trials combines a relatively small number of key statistical principles and several instructive clinical trials to gently guide the reader through the statistical thinking needed in clinical trials. Randomization is the cornerstone of clinical trials and randomization-based inference is the cornerstone of this book. Read this book to learn the elegance and simplicity of re-randomization tests as the basis for statistical inference (the analyze as you randomize principle) and see how re-randomization tests can save a trial that required an unplanned, mid-course design change. Other principles enable the reader to quickly and confidently check calculations without relying on computer programs. The `EZ’ principle says that a single sample size formula can be applied to a multitude of statistical tests. The `O minus E except after V’ principle provides a simple estimator of the log odds ratio that is ideally suited for stratified analysis with a binary outcome. The same principle can be used to estimate the log hazard ratio and facilitate stratified analysis in a survival setting. Learn these and other simple techniques that will make you an invaluable clinical trial statistician.
| Author | : Susan S. Ellenberg |
| Publisher | : John Wiley & Sons |
| Total Pages | : 208 |
| Release | : 2003-01-17 |
| Genre | : Mathematics |
| ISBN | : 0470854154 |
There has been substantial growth in the use of data monitoring committees in recent years, by both government agencies and the pharmaceutical industry. This growth has been brought about by increasing recognition of the value of such committees in safeguarding trial participants as well as protecting trial integrity and the validity of conclusions. This very timely book describes the operation of data monitoring committees, and provides an authoritative guide to their establishment, purpose and responsibilities. * Provides a practical overview of data monitoring in clinical trials. * Describes the purpose, responsibilities and operation of data monitoring committees. * Provides directly applicable advice for those managing and conducting clinical trials, and those serving on data monitoring committees. * Gives insight into clinical data monitoring to those sitting on regulatory and ethical committees. * Discusses issues pertinent to those working in clinical trials in both the US and Europe. The practical guidance provided by this book will be of use to professionals working in and/or managing clinical trials, in academic, government and industry settings, particularly medical statisticians, clinicians, trial co-ordinators, and those working in regulatory affairs and bioethics.
| Author | : David L. DeMets |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 389 |
| Release | : 2006-06-22 |
| Genre | : Medical |
| ISBN | : 0387301070 |
From the authors of "Fundamentals of Clinical Trials" which has sold over 15,000 copies world wide since its publication in 1998. No competition yet as the text does not focus on how to do clinical trials but on very specific situations that can be encountered during the process.
| Author | : Weichung Joe Shih |
| Publisher | : CRC Press |
| Total Pages | : 380 |
| Release | : 2021-10-26 |
| Genre | : Medical |
| ISBN | : 9781003176527 |
Statistical Design, Monitoring, and Analysis of Clinical Trials, Second Edition concentrates on the biostatistics component of clinical trials. This new edition is updated throughout and includes five new chapters. Developed from the authors' courses taught to public health and medical students, residents, and fellows during the past 20 years, the text shows how biostatistics in clinical trials is an integration of many fundamental scientific principles and statistical methods. The book begins with ethical and safety principles, core trial design concepts, the principles and methods of sample size and power calculation, and analysis of covariance and stratified analysis. It then focuses on sequential designs and methods for two-stage Phase II cancer trials to Phase III group sequential trials, covering monitoring safety, futility, and efficacy. The authors also discuss the development of sample size reestimation and adaptive group sequential procedures, phase 2/3 seamless design and trials with predictive biomarkers, exploit multiple testing procedures, and explain the concept of estimand, intercurrent events, and different missing data processes, and describe how to analyze incomplete data by proper multiple imputations. This text reflects the academic research, commercial development, and public health aspects of clinical trials. It gives students and practitioners a multidisciplinary understanding of the concepts and techniques involved in designing, monitoring, and analyzing various types of trials. The book's balanced set of homework assignments and in-class exercises are appropriate for students and researchers in (bio)statistics, epidemiology, medicine, pharmacy, and public health.
| Author | : Jay Herson |
| Publisher | : CRC Press |
| Total Pages | : 266 |
| Release | : 2016-12-19 |
| Genre | : Mathematics |
| ISBN | : 1498784127 |
Praise for the first edition: "Given the author’s years of experience as a statistician and as a founder of the first DMC in pharmaceutical industry trials, I highly recommend this book—not only for experts because of its cogent and organized presentation, but more importantly for young investigators who are seeking information about the logistical and philosophical aspects of a DMC." -S. T. Ounpraseuth, The American Statistician In the first edition of this well-regarded book, the author provided a groundbreaking and definitive guide to best practices in pharmaceutical industry data monitoring committees (DMCs). Maintaining all the material from the first edition and adding substantial new material, Data and Safety Monitoring Committees in Clinical Trials, Second Edition is ideal for training professionals to serve on their first DMC as well as for experienced clinical and biostatistical DMC members, sponsor and regulatory agency staff. The second edition guides the reader through newly emerging DMC responsibilities brought about by regulations emphasizing risk vs benefit and the emergence of risk-based monitoring. It also provides the reader with many new statistical methods, clinical trial designs and clinical terminology that have emerged since the first edition. The references have been updated and the very popular end-of-chapter Q&A section has been supplemented with many new experiences since the first edition. New to the Second Edition: Presents statistical methods, tables, listings and graphs appropriate for safety review, efficacy analysis and risk vs benefit analysis, SPERT and PRISMA initiatives. Newly added interim analysis for efficacy and futility section. DMC responsibilities in SUSARs (Serious Unexpected Serious Adverse Reactions), basket trials, umbrella trials, dynamic treatment strategies /SMART trials, pragmatic trials, biosimilar trials, companion diagnostics, etc. DMC responsibilities for data quality and fraud detection (Fraud Recovery Plan) Use of patient reported outcomes of safety Use of meta analysis and data outside the trial New ideas for training and compensation of DMC members Jay Herson is Senior Associate, Biostatistics, Johns Hopkins Bloomberg School of Public Health where he teaches courses on clinical trials and drug development based on his many years experience in clinical trials in academia and the pharmaceutical industry.
| Author | : Institute of Medicine |
| Publisher | : National Academies Press |
| Total Pages | : 221 |
| Release | : 2001-01-01 |
| Genre | : Medical |
| ISBN | : 0309171148 |
Clinical trials are used to elucidate the most appropriate preventive, diagnostic, or treatment options for individuals with a given medical condition. Perhaps the most essential feature of a clinical trial is that it aims to use results based on a limited sample of research participants to see if the intervention is safe and effective or if it is comparable to a comparison treatment. Sample size is a crucial component of any clinical trial. A trial with a small number of research participants is more prone to variability and carries a considerable risk of failing to demonstrate the effectiveness of a given intervention when one really is present. This may occur in phase I (safety and pharmacologic profiles), II (pilot efficacy evaluation), and III (extensive assessment of safety and efficacy) trials. Although phase I and II studies may have smaller sample sizes, they usually have adequate statistical power, which is the committee's definition of a "large" trial. Sometimes a trial with eight participants may have adequate statistical power, statistical power being the probability of rejecting the null hypothesis when the hypothesis is false. Small Clinical Trials assesses the current methodologies and the appropriate situations for the conduct of clinical trials with small sample sizes. This report assesses the published literature on various strategies such as (1) meta-analysis to combine disparate information from several studies including Bayesian techniques as in the confidence profile method and (2) other alternatives such as assessing therapeutic results in a single treated population (e.g., astronauts) by sequentially measuring whether the intervention is falling above or below a preestablished probability outcome range and meeting predesigned specifications as opposed to incremental improvement.
| Author | : Institute of Medicine |
| Publisher | : National Academies Press |
| Total Pages | : 236 |
| Release | : 2015-04-20 |
| Genre | : Medical |
| ISBN | : 0309316324 |
Data sharing can accelerate new discoveries by avoiding duplicative trials, stimulating new ideas for research, and enabling the maximal scientific knowledge and benefits to be gained from the efforts of clinical trial participants and investigators. At the same time, sharing clinical trial data presents risks, burdens, and challenges. These include the need to protect the privacy and honor the consent of clinical trial participants; safeguard the legitimate economic interests of sponsors; and guard against invalid secondary analyses, which could undermine trust in clinical trials or otherwise harm public health. Sharing Clinical Trial Data presents activities and strategies for the responsible sharing of clinical trial data. With the goal of increasing scientific knowledge to lead to better therapies for patients, this book identifies guiding principles and makes recommendations to maximize the benefits and minimize risks. This report offers guidance on the types of clinical trial data available at different points in the process, the points in the process at which each type of data should be shared, methods for sharing data, what groups should have access to data, and future knowledge and infrastructure needs. Responsible sharing of clinical trial data will allow other investigators to replicate published findings and carry out additional analyses, strengthen the evidence base for regulatory and clinical decisions, and increase the scientific knowledge gained from investments by the funders of clinical trials. The recommendations of Sharing Clinical Trial Data will be useful both now and well into the future as improved sharing of data leads to a stronger evidence base for treatment. This book will be of interest to stakeholders across the spectrum of research-from funders, to researchers, to journals, to physicians, and ultimately, to patients.
