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Practical Considerations for Adaptive Trial Design and Implementation

Practical Considerations for Adaptive Trial Design and Implementation Author Weili He
ISBN-10 9781493911004
Release 2014-10-15
Pages 416
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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.



The Evaluation of Surrogate Endpoints

The Evaluation of Surrogate Endpoints Author Tomasz Burzykowski
ISBN-10 9780387270807
Release 2006-03-30
Pages 410
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Covers the latest research on a sensitive and controversial topic in a professional and well researched manner. Provides practical outlook as well as model guidelines and software tools that should be of interest to people who use the software tools described and those who do not. Related title by Co-author Geert Molenbergh has sold more than 3500 copies world wide. Provides dual viewpoints: from scientists in the industry as well as regulatory authorities.



Statistical Monitoring of Clinical Trials

Statistical Monitoring of Clinical Trials Author Michael A. Proschan
ISBN-10 0387449701
Release 2006-12-31
Pages 268
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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.



Oncology Clinical Trials

Oncology Clinical Trials Author William Kevin Kelly, DO
ISBN-10 9780826168733
Release 2018-03-28
Pages 600
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The second edition of Oncology Clinical Trials has been thoroughly revised and updated and now contains the latest designs and methods of conducting and analyzing cancer clinical trials in the era of precision medicine with biologic agents—including trials investigating the safety and efficacy of targeted therapies, immunotherapies, and combination therapies as well as novel radiation therapy modalities. Now divided into six sections this revamped book provides the necessary background and expert guidance from the principles governing oncology clinical trials to the innovative statistical design methods permeating the field; from conducting trials in a safe and effective manner, analyzing and interpreting the data, to a forward-looking assessment and discussion of regulatory issues impacting domestic, international, and global clinical trials. Considered by many as the gold standard reference on oncology clinical trials in the field, the second edition continues to provide examples of real-life flaws and real-world examples for how to successfully design, conduct and analyze quality clinical trials and interpret them. With chapters written by oncologists, researchers, biostatisticians, clinical research administrators, and industry and FDA representatives, this volume provides a comprehensive guide in the design, conduct, monitoring, analysis, and reporting of clinical trials in oncology. NEW TO THIS EDITION: Outlines how to design clinical trials with and without biomarker testing—including genomics-based “basket” trials, and adaptive trials for all phases during treatment and quality-of-life trials Includes new chapters on immunotherapy trials, radiation therapy trials, multi-arm trials, meta-analysis and adaptive design, use of genomics, dose modifications and use of ancillary treatments in investigational studies, establishing surrogate endpoints, practical issues with correlative studies, cost-effectiveness analysis, and more Comprehensively covers all regulatory aspects in the pursuit of global oncology trials Digital access to the ebook included



Statistical Applications for Chemistry Manufacturing and Controls CMC in the Pharmaceutical Industry

Statistical Applications for Chemistry  Manufacturing and Controls  CMC  in the Pharmaceutical Industry Author Richard K. Burdick
ISBN-10 9783319501864
Release 2017-03-14
Pages 379
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This book examines statistical techniques that are critically important to Chemistry, Manufacturing, and Control (CMC) activities. Statistical methods are presented with a focus on applications unique to the CMC in the pharmaceutical industry. The target audience consists of statisticians and other scientists who are responsible for performing statistical analyses within a CMC environment. Basic statistical concepts are addressed in Chapter 2 followed by applications to specific topics related to development and manufacturing. The mathematical level assumes an elementary understanding of statistical methods. The ability to use Excel or statistical packages such as Minitab, JMP, SAS, or R will provide more value to the reader. The motivation for this book came from an American Association of Pharmaceutical Scientists (AAPS) short course on statistical methods applied to CMC applications presented by four of the authors. One of the course participants asked us for a good reference book, and the only book recommended was written over 20 years ago by Chow and Liu (1995). We agreed that a more recent book would serve a need in our industry. Since we began this project, an edited book has been published on the same topic by Zhang (2016). The chapters in Zhang discuss statistical methods for CMC as well as drug discovery and nonclinical development. We believe our book complements Zhang by providing more detailed statistical analyses and examples.



Preventing and Treating Missing Data in Longitudinal Clinical Trials

Preventing and Treating Missing Data in Longitudinal Clinical Trials Author Craig H. Mallinckrodt
ISBN-10 9781107311367
Release 2013-01-28
Pages
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Recent decades have brought advances in statistical theory for missing data, which, combined with advances in computing ability, have allowed implementation of a wide array of analyses. In fact, so many methods are available that it can be difficult to ascertain when to use which method. This book focuses on the prevention and treatment of missing data in longitudinal clinical trials. Based on his extensive experience with missing data, the author offers advice on choosing analysis methods and on ways to prevent missing data through appropriate trial design and conduct. He offers a practical guide to key principles and explains analytic methods for the non-statistician using limited statistical notation and jargon. The book's goal is to present a comprehensive strategy for preventing and treating missing data, and to make available the programs used to conduct the analyses of the example dataset.



Principles and Practice of Clinical Research

Principles and Practice of Clinical Research Author John I. Gallin
ISBN-10 9780128499047
Release 2017-11-17
Pages 824
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Principles and Practice of Clinical Research, Fourth Edition has been thoroughly revised to provide a comprehensive look at both the fundamental principles and expanding practice of clinical research. New to this edition of this highly regarded reference, authors have focused on examples that broadly reflect clinical research on a global scale while including a discussion of international regulations, studies, and implications. In addition to key topics such as bioethics, clinical outcome data, cultural diversity, protocol guidelines, and “omic platforms, this edition contains new chapters devoted to electronic health records and information resources for clinical researchers, as well as the many opportunities associated with big data. Covering a vast number of topics and practical advice for both novice and advanced clinical investigators, this book is a highly relevant and essential resource for all those involved in conducting research. Features input from experts in the field dedicated to translating scientific research from bench to bedside and back Provides expanded coverage of global clinical research Contains hands-on, practical suggestions, illustrations, and examples throughout Includes new chapters on the international regulation of drugs and biologics, the emergence of the important role of comparative effectiveness research and how to identify clinical risks and manage patient safety in a clinical research setting



Clinical Trial Data Analysis Using R and SAS

Clinical Trial Data Analysis Using R and SAS Author Ding-Geng (Din) Chen
ISBN-10 9781351651141
Release 2017-06-01
Pages 378
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Review of the First Edition "The goal of this book, as stated by the authors, is to fill the knowledge gap that exists between developed statistical methods and the applications of these methods. Overall, this book achieves the goal successfully and does a nice job. I would highly recommend it ...The example-based approach is easy to follow and makes the book a very helpful desktop reference for many biostatistics methods." —Journal of Statistical Software Clinical Trial Data Analysis Using R and SAS, Second Edition provides a thorough presentation of biostatistical analyses of clinical trial data with step-by-step implementations using R and SAS. The book’s practical, detailed approach draws on the authors’ 30 years’ experience in biostatistical research and clinical development. The authors develop step-by-step analysis code using appropriate R packages and functions and SAS PROCS, which enables readers to gain an understanding of the analysis methods and R and SAS implementation so that they can use these two popular software packages to analyze their own clinical trial data. What’s New in the Second Edition Adds SAS programs along with the R programs for clinical trial data analysis. Updates all the statistical analysis with updated R packages. Includes correlated data analysis with multivariate analysis of variance. Applies R and SAS to clinical trial data from hypertension, duodenal ulcer, beta blockers, familial andenomatous polyposis, and breast cancer trials. Covers the biostatistical aspects of various clinical trials, including treatment comparisons, time-to-event endpoints, longitudinal clinical trials, and bioequivalence trials.



Analyzing Longitudinal Clinical Trial Data

Analyzing Longitudinal Clinical Trial Data Author Craig Mallinckrodt
ISBN-10 9781351737685
Release 2016-12-12
Pages 336
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Analyzing Longitudinal Clinical Trial Data: A Practical Guide provide practical and easy to implement approaches for bringing the latest theory on analysis of longitudinal clinical trial data into routine practice.?This 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.



Analysing Seasonal Health Data

Analysing Seasonal Health Data Author Adrian G. Barnett
ISBN-10 3642107486
Release 2010-01-08
Pages 164
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Seasonal patterns have been found in a remarkable range of health conditions, including birth defects, respiratory infections and cardiovascular disease. Accurately estimating the size and timing of seasonal peaks in disease incidence is an aid to understanding the causes and possibly to developing interventions. With global warming increasing the intensity of seasonal weather patterns around the world, a review of the methods for estimating seasonal effects on health is timely. This is the first book on statistical methods for seasonal data written for a health audience. It describes methods for a range of outcomes (including continuous, count and binomial data) and demonstrates appropriate techniques for summarising and modelling these data. It has a practical focus and uses interesting examples to motivate and illustrate the methods. The statistical procedures and example data sets are available in an R package called ‘season’.



Small Clinical Trials

Small Clinical Trials Author Institute of Medicine
ISBN-10 0309171148
Release 2001-01-01
Pages 222
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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.



Clinical and Translational Science

Clinical and Translational Science Author David Robertson
ISBN-10 9780128021118
Release 2016-11-25
Pages 808
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Clinical and Translational Science: Principles of Human Research, Second Edition, is the most authoritative and timely resource for the broad range of investigators taking on the challenge of clinical and translational science, a field that is devoted to investigating human health and disease, interventions, and outcomes for the purposes of developing new treatment approaches, devices, and modalities to improve health. This updated second edition has been prepared with an international perspective, beginning with fundamental principles, experimental design, epidemiology, traditional and new biostatistical approaches, and investigative tools. It presents complete instruction and guidance from fundamental principles, approaches, and infrastructure, especially for human genetics and genomics, human pharmacology, research in special populations, the societal context of human research, and the future of human research. The book moves on to discuss legal, social, and ethical issues, and concludes with a discussion of future prospects, providing readers with a comprehensive view of this rapidly developing area of science. Introduces novel physiological and therapeutic strategies for engaging the fastest growing scientific field in both the private sector and academic medicine Brings insights from international leaders into the discipline of clinical and translational science Addresses drug discovery, drug repurposing and development, innovative and improved approaches to go/no-go decisions in drug development, and traditional and innovative clinical trial designs



Statistical Inference on Residual Life

Statistical Inference on Residual Life Author Jong-Hyeon Jeong
ISBN-10 9781493900053
Release 2014-01-20
Pages 201
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This is a monograph on the concept of residual life, which is an alternative summary measure of time-to-event data, or survival data. The mean residual life has been used for many years under the name of life expectancy, so it is a natural concept for summarizing survival or reliability data. It is also more interpretable than the popular hazard function, especially for communications between patients and physicians regarding the efficacy of a new drug in the medical field. This book reviews existing statistical methods to infer the residual life distribution. The review and comparison includes existing inference methods for mean and median, or quantile, residual life analysis through medical data examples. The concept of the residual life is also extended to competing risks analysis. The targeted audience includes biostatisticians, graduate students, and PhD (bio)statisticians. Knowledge in survival analysis at an introductory graduate level is advisable prior to reading this book.



Clinical Prediction Models

Clinical Prediction Models Author Ewout W. Steyerberg
ISBN-10 0387772448
Release 2008-12-16
Pages 500
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Prediction models are important in various fields, including medicine, physics, meteorology, and finance. Prediction models will become more relevant in the medical field with the increase in knowledge on potential predictors of outcome, e.g. from genetics. Also, the number of applications will increase, e.g. with targeted early detection of disease, and individualized approaches to diagnostic testing and treatment. The current era of evidence-based medicine asks for an individualized approach to medical decision-making. Evidence-based medicine has a central place for meta-analysis to summarize results from randomized controlled trials; similarly prediction models may summarize the effects of predictors to provide individu- ized predictions of a diagnostic or prognostic outcome. Why Read This Book? My motivation for working on this book stems primarily from the fact that the development and applications of prediction models are often suboptimal in medical publications. With this book I hope to contribute to better understanding of relevant issues and give practical advice on better modelling strategies than are nowadays widely used. Issues include: (a) Better predictive modelling is sometimes easily possible; e.g. a large data set with high quality data is available, but all continuous predictors are dich- omized, which is known to have several disadvantages.



Statistical Methods for Dynamic Treatment Regimes

Statistical Methods for Dynamic Treatment Regimes Author Bibhas Chakraborty
ISBN-10 9781461474289
Release 2013-07-23
Pages 204
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Statistical Methods for Dynamic Treatment Regimes shares state of the art of statistical methods developed to address questions of estimation and inference for dynamic treatment regimes, a branch of personalized medicine. This volume demonstrates these methods with their conceptual underpinnings and illustration through analysis of real and simulated data. These methods are immediately applicable to the practice of personalized medicine, which is a medical paradigm that emphasizes the systematic use of individual patient information to optimize patient health care. This is the first single source to provide an overview of methodology and results gathered from journals, proceedings, and technical reports with the goal of orienting researchers to the field. The first chapter establishes context for the statistical reader in the landscape of personalized medicine. Readers need only have familiarity with elementary calculus, linear algebra, and basic large-sample theory to use this text. Throughout the text, authors direct readers to available code or packages in different statistical languages to facilitate implementation. In cases where code does not already exist, the authors provide analytic approaches in sufficient detail that any researcher with knowledge of statistical programming could implement the methods from scratch. This will be an important volume for a wide range of researchers, including statisticians, epidemiologists, medical researchers, and machine learning researchers interested in medical applications. Advanced graduate students in statistics and biostatistics will also find material in Statistical Methods for Dynamic Treatment Regimes to be a critical part of their studies.



Monitoring Bathing Waters

Monitoring Bathing Waters Author Jamie Bartram
ISBN-10 9780203478264
Release 2002-09-26
Pages 352
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This book, which has been prepared by an international group of experts, provides comprehensive guidance for the design, planning and implementation of assessments and monitoring programmes for water bodies used for recreation. It addresses the wide range of hazards which may be encountered and emphasizes the importance of linking monitoring programmes to effective and feasible management actions to protect human health. It also provides details of sampling and analytical methods. This book will be an invaluable source of information for anyone concerned with monitoring and assessing recreational waters, including field staff. It will also be useful for national and regional government departments concerned with tourism and recreation, and for students and special interest groups.



Design and Analysis of Clinical Trials

Design and Analysis of Clinical Trials Author Shein-Chung Chow
ISBN-10 9780471473299
Release 2008-12-04
Pages 752
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Design and Analysis of Clinical Trials has been writing in one form or another for most of life. You can find so many inspiration from Design and Analysis of Clinical Trials also informative, and entertaining. Click DOWNLOAD or Read Online button to get full Design and Analysis of Clinical Trials book for free.