Modern Adaptive Randomized Clinical Trials

Is adaptive randomization always better than traditional fixed-schedule randomization? Which procedures should be used and under which circumstances? What special considerations are required for adaptive randomized trials?

Author: Oleksandr Sverdlov

Publisher: CRC Press

ISBN: 9781482239898

Category: Mathematics

Page: 533

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Is adaptive randomization always better than traditional fixed-schedule randomization? Which procedures should be used and under which circumstances? What special considerations are required for adaptive randomized trials? What kind of statistical inference should be used to achieve valid and unbiased treatment comparisons following adaptive random

Modern Approaches to Clinical Trials Using SAS Classical Adaptive and Bayesian Methods

Adaptive randomization for clinical trials. Journal of Biopharmaceutical Statistics 22: 719-736. Yi Y & Wang X. (2015). Statistical inference following response-adaptive randomization. In Sverdlov O, ed. Modern Adaptive Randomized ...

Author: Sandeep Menon

Publisher: SAS Institute

ISBN: 9781629600840

Category: Computers

Page: 364

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This book covers domains of modern clinical trial design: classical, group sequential, adaptive, and Bayesian methods applicable to and used in various phases of pharmaceutical development. Written for biostatisticians, pharmacometricians, clinical developers, and statistical programmers involved in the design, analysis, and interpretation of clinical trials, as well as students in graduate and postgraduate programs in statistics or biostatistics, it covers topics including: dose-response and dose-escalation designs; sequential methods to stop trials early for overwhelming efficacy, safety, or futility; Bayesian designs incorporating historical data; adaptive sample size re-estimation and randomization to allocate subjects to effective treatments; population enrichment designs. Methods are illustrated using clinical trials from diverse therapeutic areas, including dermatology, endocrinology, infectious disease, neurology, oncology and rheumatology. --

Innovative Strategies Statistical Solutions and Simulations for Modern Clinical Trials

... Linear Mixed Models for Randomized Controlled Trials Toshiro Tango Clinical Trial Data Analysis Using Rand SAS, ... Modern Adaptive Randomized Clinical Trials: Statistical and Practical Aspects Oleksandr Sverdlov Medical Product ...

Author: Mark Chang

Publisher: CRC Press

ISBN: 9781351214537

Category: Mathematics

Page: 362

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"This is truly an outstanding book. [It] brings together all of the latest research in clinical trials methodology and how it can be applied to drug development.... Chang et al provide applications to industry-supported trials. This will allow statisticians in the industry community to take these methods seriously." Jay Herson, Johns Hopkins University The pharmaceutical industry's approach to drug discovery and development has rapidly transformed in the last decade from the more traditional Research and Development (R & D) approach to a more innovative approach in which strategies are employed to compress and optimize the clinical development plan and associated timelines. However, these strategies are generally being considered on an individual trial basis and not as part of a fully integrated overall development program. Such optimization at the trial level is somewhat near-sighted and does not ensure cost, time, or development efficiency of the overall program. This book seeks to address this imbalance by establishing a statistical framework for overall/global clinical development optimization and providing tactics and techniques to support such optimization, including clinical trial simulations. Provides a statistical framework for achieve global optimization in each phase of the drug development process. Describes specific techniques to support optimization including adaptive designs, precision medicine, survival-endpoints, dose finding and multiple testing. Gives practical approaches to handling missing data in clinical trials using SAS. Looks at key controversial issues from both a clinical and statistical perspective. Presents a generous number of case studies from multiple therapeutic areas that help motivate and illustrate the statistical methods introduced in the book. Puts great emphasis on software implementation of the statistical methods with multiple examples of software code (both SAS and R). It is important for statisticians to possess a deep knowledge of the drug development process beyond statistical considerations. For these reasons, this book incorporates both statistical and "clinical/medical" perspectives.

Randomization Masking and Allocation Concealment

Modern Adaptive Randomized Clinical Trials: Statistical, Operational, and Regulatory Aspects: pp. 83–114. CRC Press, Taylor & Francis Group, 2015. 10. Kuznetsova OM. Brick tunnel randomization and the momentum of the probability mass.

Author: Vance Berger

Publisher: CRC Press

ISBN: 9781315305097

Category: Mathematics

Page: 251

View: 650

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Randomization, Masking, and Allocation Concealment is indispensable for any trial researcher who wants to use state of the art randomization methods, and also wants to be able to describe these methods correctly. Far too often the subtle nuances that distinguish proper randomization from flawed randomization are completely ignored in trial reports that state only that randomization was used, with no additional information. Experience has shown that in many cases, the type of randomization that was used was flawed. It is only a matter of time before medical journals and regulatory agencies come to realize that we can no longer rely on (or publish) flawed trials, and that flawed randomization in and of itself disqualifies a trial from being robust or high quality, even if that trial is of high quality otherwise. This book will help to clarify the role randomization plays in ensuring internal validity, and in drawing valid inferences from the data. The various chapters cover a variety of randomization methods, and are not limited to the most common (and most flawed) ones. Readers will come away with a profound understanding of what constitutes a valid randomization procedure, so that they can distinguish the valid from the flawed among not only existing methods but can also methods yet to be developed.

Statistical Remedies for Medical Researchers

Randomized phase II trials: A long-term investment with promising returns.Journal of the National Cancer Institute ... Modern adaptive randomized clinical trials: Statistical and practical aspects. Boca Raton: CRC Press/Taylor and ...

Author: Peter F. Thall

Publisher: Springer Nature

ISBN: 9783030437145

Category: Medical

Page: 291

View: 695

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This book illustrates numerous statistical practices that are commonly used by medical researchers, but which have severe flaws that may not be obvious. For each example, it provides one or more alternative statistical methods that avoid misleading or incorrect inferences being made. The technical level is kept to a minimum to make the book accessible to non-statisticians. At the same time, since many of the examples describe methods used routinely by medical statisticians with formal statistical training, the book appeals to a broad readership in the medical research community.

The Theory of Response Adaptive Randomization in Clinical Trials

1.2 RESPONSE-ADAPTIVE RANDOMIZATION IN A HISTORICAL CONTEXT In this book, the response-adaptive randomization procedures ... in that each subject is assigned a treatment by random chance, the cornerstone of the modern clinical trial.

Author: Feifang Hu

Publisher: John Wiley & Sons

ISBN: 9780470055878

Category: Mathematics

Page: 240

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Presents a firm mathematical basis for the use of response-adaptive randomization procedures in practice The Theory of Response-Adaptive Randomization in Clinical Trials is the result of the authors' ten-year collaboration as well as their collaborations with other researchers in investigating the important questions regarding response-adaptive randomization in a rigorous mathematical framework. Response-adaptive allocation has a long history in biostatistics literature; however, largely due to the disastrous ECMO trial in the early 1980s, there is a general reluctance to use these procedures. This timely book represents a mathematically rigorous subdiscipline of experimental design involving randomization and answers fundamental questions, including: How does response-adaptive randomization affect power? Can standard inferential tests be applied following response-adaptive randomization? What is the effect of delayed response? Which procedure is most appropriate and how can "most appropriate" be quantified? How can heterogeneity of the patient population be incorporated? Can response-adaptive randomization be performed with more than two treatments or with continuous responses? The answers to these questions communicate a thorough understanding of the asymptotic properties of each procedure discussed, including asymptotic normality, consistency, and asymptotic variance of the induced allocation. Topical coverage includes: The relationship between power and response-adaptive randomization The general result for determining asymptotically best procedures Procedures based on urn models Procedures based on sequential estimation Implications for the practice of clinical trials Useful for graduate students in mathematics, statistics, and biostatistics as well as researchers and industrial and academic biostatisticians, this book offers a rigorous treatment of the subject in order to find the optimal procedure to use in practice.

Textbook of Clinical Trials in Oncology

This methodology is used in the STAMPEDE trial [31], which is a flagship example of a MAMS trial in oncology. ... In Modern Adaptive Randomized Clinical Trials: Statistical and Practical Aspects, Sverdlov O, ed., 2015: 389–410.

Author: Susan Halabi

Publisher: CRC Press

ISBN: 9781351620970

Category: Medical

Page: 626

View: 324

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There is an increasing need for educational resources for statisticians and investigators. Reflecting this, the goal of this book is to provide readers with a sound foundation in the statistical design, conduct, and analysis of clinical trials. Furthermore, it is intended as a guide for statisticians and investigators with minimal clinical trial experience who are interested in pursuing a career in this area. The advancement in genetic and molecular technologies have revolutionized drug development. In recent years, clinical trials have become increasingly sophisticated as they incorporate genomic studies, and efficient designs (such as basket and umbrella trials) have permeated the field. This book offers the requisite background and expert guidance for the innovative statistical design and analysis of clinical trials in oncology. Key Features: Cutting-edge topics with appropriate technical background Built around case studies which give the work a "hands-on" approach Real examples of flaws in previously reported clinical trials and how to avoid them Access to statistical code on the book’s website Chapters written by internationally recognized statisticians from academia and pharmaceutical companies Carefully edited to ensure consistency in style, level, and approach Topics covered include innovating phase I and II designs, trials in immune-oncology and rare diseases, among many others

Multiregional Clinical Trials for Simultaneous Global New Drug Development

... Tasks, Methods and Tools Marc Lavielle Modeling to Inform Infectious Disease Control Niels G. Becker Modern Adaptive Randomized Clinical Trials: Statistical and Practical Aspects Oleksandr Sverdlov Monte Carlo Simulation for the ...

Author: Joshua Chen

Publisher: CRC Press

ISBN: 9781498701488

Category: Mathematics

Page: 375

View: 102

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In a global clinical development strategy, multiregional clinical trials (MRCTs) are vital in the development of innovative medicines. Multiregional Clinical Trials for Simultaneous Global New Drug Development presents a comprehensive overview on the current status of conducting MRCTs in clinical development. International experts from academia, in

Analyzing Longitudinal Clinical Trial Data

... New Clinical Trialists Scott Evans and Naitee Ting Generalized Linear Models: A Bayesian Perspective Dipak K. Dey, ... to Inform Infectious Disease Control Niels G. Becker Modern Adaptive Randomized Clinical Trials: Statistical and ...

Author: Craig Mallinckrodt

Publisher: CRC Press

ISBN: 9781351737692

Category: Mathematics

Page: 302

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Analyzing Longitudinal Clinical Trial Data: A Practical Guide provides practical and easy to implement approaches for bringing the latest theory on analysis of longitudinal clinical trial data into routine practice.The book, with its example-oriented approach that includes numerous SAS and R code fragments, is an essential resource for statisticians and graduate students specializing in medical research. The authors provide clear descriptions of the relevant statistical theory and illustrate practical considerations for modeling longitudinal data. Topics covered include choice of endpoint and statistical test; modeling means and the correlations between repeated measurements; accounting for covariates; modeling categorical data; model verification; methods for incomplete (missing) data that includes the latest developments in sensitivity analyses, along with approaches for and issues in choosing estimands; and means for preventing missing data. Each chapter stands alone in its coverage of a topic. The concluding chapters provide detailed advice on how to integrate these independent topics into an over-arching study development process and statistical analysis plan.

Bayesian Designs for Phase I II Clinical Trials

Published Titles Frailty Models in Survival Analysis Andreas Wienke Fundamental Concepts for New Clinical Trialists ... Outcomes in Clinical Research Chul Ahn, Moonseong Heo, and Song Zhang Modern Adaptive Randomized Clinical Trials: ...

Author: Ying Yuan

Publisher: CRC Press

ISBN: 9781498709569

Category: Mathematics

Page: 310

View: 247

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Reliably optimizing a new treatment in humans is a critical first step in clinical evaluation since choosing a suboptimal dose or schedule may lead to failure in later trials. At the same time, if promising preclinical results do not translate into a real treatment advance, it is important to determine this quickly and terminate the clinical evaluation process to avoid wasting resources. Bayesian Designs for Phase I–II Clinical Trials describes how phase I–II designs can serve as a bridge or protective barrier between preclinical studies and large confirmatory clinical trials. It illustrates many of the severe drawbacks with conventional methods used for early-phase clinical trials and presents numerous Bayesian designs for human clinical trials of new experimental treatment regimes. Written by research leaders from the University of Texas MD Anderson Cancer Center, this book shows how Bayesian designs for early-phase clinical trials can explore, refine, and optimize new experimental treatments. It emphasizes the importance of basing decisions on both efficacy and toxicity.