Issues in Group Sequential/ Adaptive Designs
| Author | : Hong Wan |
| Publisher | : |
| Total Pages | : 96 |
| Release | : 2013 |
| Genre | : |
| ISBN | : |
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Issues In Group Sequential Adaptive Designs
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Group Sequential and Confirmatory Adaptive Designs in Clinical Trials
| Author | : Gernot Wassmer |
| Publisher | : Springer |
| Total Pages | : 310 |
| Release | : 2016-07-04 |
| Genre | : Medical |
| ISBN | : 3319325620 |
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This book provides an up-to-date review of the general principles of and techniques for confirmatory adaptive designs. Confirmatory adaptive designs are a generalization of group sequential designs. With these designs, interim analyses are performed in order to stop the trial prematurely under control of the Type I error rate. In adaptive designs, it is also permissible to perform a data-driven change of relevant aspects of the study design at interim stages. This includes, for example, a sample-size reassessment, a treatment-arm selection or a selection of a pre-specified sub-population. Essentially, this adaptive methodology was introduced in the 1990s. Since then, it has become popular and the object of intense discussion and still represents a rapidly growing field of statistical research. This book describes adaptive design methodology at an elementary level, while also considering designing and planning issues as well as methods for analyzing an adaptively planned trial. This includes estimation methods and methods for the determination of an overall p-value. Part I of the book provides the group sequential methods that are necessary for understanding and applying the adaptive design methodology supplied in Parts II and III of the book. The book contains many examples that illustrate use of the methods for practical application. The book is primarily written for applied statisticians from academia and industry who are interested in confirmatory adaptive designs. It is assumed that readers are familiar with the basic principles of descriptive statistics, parameter estimation and statistical testing. This book will also be suitable for an advanced statistical course for applied statisticians or clinicians with a sound statistical background.
Adaptive Design Methods in Clinical Trials
| Author | : Shein-Chung Chow |
| Publisher | : CRC Press |
| Total Pages | : 368 |
| Release | : 2011-12-01 |
| Genre | : Mathematics |
| ISBN | : 1439839883 |
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With new statistical and scientific issues arising in adaptive clinical trial design, including the U.S. FDA's recent draft guidance, a new edition of one of the first books on the topic is needed. Adaptive Design Methods in Clinical Trials, Second Edition reflects recent developments and regulatory positions on the use of adaptive designs in clini
Randomization in Clinical Trials
| Author | : William F. Rosenberger |
| Publisher | : John Wiley & Sons |
| Total Pages | : 284 |
| Release | : 2015-11-23 |
| Genre | : Mathematics |
| ISBN | : 1118742249 |
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Praise for the First Edition “All medical statisticians involved in clinical trials should read this book...” - Controlled Clinical Trials Featuring a unique combination of the applied aspects of randomization in clinical trials with a nonparametric approach to inference, Randomization in Clinical Trials: Theory and Practice, Second Edition is the go-to guide for biostatisticians and pharmaceutical industry statisticians. Randomization in Clinical Trials: Theory and Practice, Second Edition features: Discussions on current philosophies, controversies, and new developments in the increasingly important role of randomization techniques in clinical trials A new chapter on covariate-adaptive randomization, including minimization techniques and inference New developments in restricted randomization and an increased focus on computation of randomization tests as opposed to the asymptotic theory of randomization tests Plenty of problem sets, theoretical exercises, and short computer simulations using SAS® to facilitate classroom teaching, simplify the mathematics, and ease readers’ understanding Randomization in Clinical Trials: Theory and Practice, Second Edition is an excellent reference for researchers as well as applied statisticians and biostatisticians. The Second Edition is also an ideal textbook for upper-undergraduate and graduate-level courses in biostatistics and applied statistics. William F. Rosenberger, PhD, is University Professor and Chairman of the Department of Statistics at George Mason University. He is a Fellow of the American Statistical Association and the Institute of Mathematical Statistics, and author of over 80 refereed journal articles, as well as The Theory of Response-Adaptive Randomization in Clinical Trials, also published by Wiley. John M. Lachin, ScD, is Research Professor in the Department of Epidemiology and Biostatistics as well as in the Department of Statistics at The George Washington University. A Fellow of the American Statistical Association and the Society for Clinical Trials, Dr. Lachin is actively involved in coordinating center activities for clinical trials of diabetes. He is the author of Biostatistical Methods: The Assessment of Relative Risks, Second Edition, also published by Wiley.
Group Sequential Methods with Applications to Clinical Trials
| Author | : Christopher Jennison |
| Publisher | : CRC Press |
| Total Pages | : 416 |
| Release | : 1999-09-15 |
| Genre | : Mathematics |
| ISBN | : 9781584888581 |
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Group sequential methods answer the needs of clinical trial monitoring committees who must assess the data available at an interim analysis. These interim results may provide grounds for terminating the study-effectively reducing costs-or may benefit the general patient population by allowing early dissemination of its findings. Group sequential methods provide a means to balance the ethical and financial advantages of stopping a study early against the risk of an incorrect conclusion. Group Sequential Methods with Applications to Clinical Trials describes group sequential stopping rules designed to reduce average study length and control Type I and II error probabilities. The authors present one-sided and two-sided tests, introduce several families of group sequential tests, and explain how to choose the most appropriate test and interim analysis schedule. Their topics include placebo-controlled randomized trials, bio-equivalence testing, crossover and longitudinal studies, and linear and generalized linear models. Research in group sequential analysis has progressed rapidly over the past 20 years. Group Sequential Methods with Applications to Clinical Trials surveys and extends current methods for planning and conducting interim analyses. It provides straightforward descriptions of group sequential hypothesis tests in a form suited for direct application to a wide variety of clinical trials. Medical statisticians engaged in any investigations planned with interim analyses will find this book a useful and important tool.
Sequential Experimentation in Clinical Trials
| Author | : Jay Bartroff |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 250 |
| Release | : 2012-12-12 |
| Genre | : Medical |
| ISBN | : 1461461146 |
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Sequential Experimentation in Clinical Trials: Design and Analysis is developed from decades of work in research groups, statistical pedagogy, and workshop participation. Different parts of the book can be used for short courses on clinical trials, translational medical research, and sequential experimentation. The authors have successfully used the book to teach innovative clinical trial designs and statistical methods for Statistics Ph.D. students at Stanford University. There are additional online supplements for the book that include chapter-specific exercises and information. Sequential Experimentation in Clinical Trials: Design and Analysis covers the much broader subject of sequential experimentation that includes group sequential and adaptive designs of Phase II and III clinical trials, which have attracted much attention in the past three decades. In particular, the broad scope of design and analysis problems in sequential experimentation clearly requires a wide range of statistical methods and models from nonlinear regression analysis, experimental design, dynamic programming, survival analysis, resampling, and likelihood and Bayesian inference. The background material in these building blocks is summarized in Chapter 2 and Chapter 3 and certain sections in Chapter 6 and Chapter 7. Besides group sequential tests and adaptive designs, the book also introduces sequential change-point detection methods in Chapter 5 in connection with pharmacovigilance and public health surveillance. Together with dynamic programming and approximate dynamic programming in Chapter 3, the book therefore covers all basic topics for a graduate course in sequential analysis designs.
Adaptive Group Sequential Designs with Control of the Population-wise Error Rate
| Author | : Charlie Hillner |
| Publisher | : |
| Total Pages | : 0 |
| Release | : 2021 |
| Genre | : |
| ISBN | : |
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The aim of individualized medicine is to provide each patient with a therapy tailored to his or her genetic profile. This is particularly important in diseases where the efficacy of a treatment depends on various individual-specific factors. Especially in rarer diseases or in highly stratified patient populations, proof of superiority of a new therapy may now prove difficult to achieve, as the necessary test power cannot be reached due to too small sample sizes. A good example is the field of pediatric oncology, where individualization of therapies plays an increasingly important role, but the underlying study populations are so limited that proof of superiority of therapy and stratification strategies is hardly possible under classical statistical principles. The aim of this work is to combine the flexibility of adaptive designs for clinical trials with the new requirements and dynamic development in individualized medicine. For this purpose, situations are considered in which the superiority of potentially different treatments is to be investigated in different, not necessarily disjoint subgroups of an overall population. In particular, these subgroups may thus be overlapping or nested. Since a multiplicity problem arises from testing several hypotheses on partly the same data material, but the family-wise error rate (FWER) often used here is too conservative, a new, less conservative multiple type I error criterion tailored to the particular subgroup structures is used in this work. This error criterion, termed the population-wise error rate (PWER), will be used as the basis for developing new multiple, sequential, and adaptive trial designs for testing individualized therapies. Specifically, single-stage test designs with PWER control were first developed and compared with corresponding FWER-controlling designs using various special cases. Next, group sequential designs controlling for PWER were constructed, here adapting various methods from the classical theory of group sequential designs. Last, adaptive designs with PWER-control were conceived and tested in numerical examples and simulations.
Adaptive Design Theory and Implementation Using SAS and R
| Author | : Mark Chang |
| Publisher | : CRC Press |
| Total Pages | : 689 |
| Release | : 2014-12-01 |
| Genre | : Mathematics |
| ISBN | : 1482256606 |
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Get Up to Speed on Many Types of Adaptive DesignsSince the publication of the first edition, there have been remarkable advances in the methodology and application of adaptive trials. Incorporating many of these new developments, Adaptive Design Theory and Implementation Using SAS and R, Second Edition offers a detailed framework to understand the
Practical Considerations for Adaptive Trial Design and Implementation
| Author | : Weili He |
| Publisher | : Springer |
| Total Pages | : 420 |
| Release | : 2014-10-15 |
| Genre | : Medical |
| ISBN | : 1493911007 |
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This edited volume is a definitive text on adaptive clinical trial designs from creation and customization to utilization. As this book covers the full spectrum of topics involved in the adaptive designs arena, it will serve as a valuable reference for researchers working in industry, government and academia. The target audience is anyone involved in the planning and execution of clinical trials, in particular, statisticians, clinicians, pharmacometricians, clinical operation specialists, drug supply managers, and infrastructure providers. In spite of the increased efficiency of adaptive trials in saving costs and time, ultimately getting drugs to patients sooner, their adoption in clinical development is still relatively low. One of the chief reasons is the higher complexity of adaptive design trials as compared to traditional trials. Barriers to the use of clinical trials with adaptive features include the concerns about the integrity of study design and conduct, the risk of regulatory non-acceptance, the need for an advanced infrastructure for complex randomization and clinical supply scenarios, change management for process and behavior modifications, extensive resource requirements for the planning and design of adaptive trials and the potential to relegate key decision makings to outside entities. There have been limited publications that address these practical considerations and recommend best practices and solutions. This book fills this publication gap, providing guidance on practical considerations for adaptive trial design and implementation. The book comprises three parts: Part I focuses on practical considerations from a design perspective, whereas Part II delineates practical considerations related to the implementation of adaptive trials. Putting it all together, Part III presents four illustrative case studies ranging from description and discussion of specific adaptive trial design considerations to the logistic and regulatory issues faced in trial implementation. Bringing together the expertise of leading key opinion leaders from pharmaceutical industry, academia, and regulatory agencies, this book provides a balanced and comprehensive coverage of practical considerations for adaptive trial design and implementation.
Small Clinical Trials
| Author | : Institute of Medicine |
| Publisher | : National Academies Press |
| Total Pages | : 221 |
| Release | : 2001-01-01 |
| Genre | : Medical |
| ISBN | : 0309171148 |
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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.
