Applying Survival Analysis Techniques to Interim Analysis and Sample Size Reassessment of Clinical Trials with a Dichotomous Endpoint PDF Download
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Author: Alison L. Pedley
Publisher:
ISBN:
Category :
Languages : en
Pages : 210
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Book Description
Abstract: A two-sample Z test of proportions is often performed in randomized clinical trials designed to assess the superiority of an experimental treatment to a control with respect to a long-term dichotomous primary endpoint, such as 1-year mortality. Due to the staggered entry of participants across the trial's recruitment period, only a portion of enrolled participants have complete follow- up data available at the time of an interim analysis. Typically, the interim evaluation of trial hypotheses is performed using the same test statistic as the test statistic planned for the final analysis. However, application of the Z test of proportions at interim analysis results in a potentially substantial reduction to the number of participants that are able to contribute to the analysis. In this dissertation, methodology for the use of the log-rank test, which incorporates data of all enrolled participants regardless of the amount of time each has been followed, in the interim analysis of trials with a dichotomous final primary endpoint is developed and evaluated. Although the overall power and type I error rates of the newly proposed methodology and the standard methodology are comparable under the assumption of proportional hazards and event rates less than 50%, the efficiency of using the log-rank test during the interim analysis was realized in terms of an increased probability of early trial termination for overwhelming efficacy resulting in potential for shorter trials and smaller sized trials. Methodology for using the log-rank test was also developed for and applied to trials incorporating an adaptation for sample size re-estimation at interim based on the conditional power of achieving a significant result by the end of the trial. In the context of sample size re-estimation, the use of the log-rank test not only increased the probability of declaring superiority of the experimental treatment over the control at the time of interim analysis, but increased the overall power. Regardless of whether or not sample size re-estimation is used, greater efficiency is attained when the log-rank test is performed at interim analysis as the differential between the percentages of subjects enrolled and with complete follow-up at interim analysis increases.
Author: Alison L. Pedley
Publisher:
ISBN:
Category :
Languages : en
Pages : 210
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Book Description
Abstract: A two-sample Z test of proportions is often performed in randomized clinical trials designed to assess the superiority of an experimental treatment to a control with respect to a long-term dichotomous primary endpoint, such as 1-year mortality. Due to the staggered entry of participants across the trial's recruitment period, only a portion of enrolled participants have complete follow- up data available at the time of an interim analysis. Typically, the interim evaluation of trial hypotheses is performed using the same test statistic as the test statistic planned for the final analysis. However, application of the Z test of proportions at interim analysis results in a potentially substantial reduction to the number of participants that are able to contribute to the analysis. In this dissertation, methodology for the use of the log-rank test, which incorporates data of all enrolled participants regardless of the amount of time each has been followed, in the interim analysis of trials with a dichotomous final primary endpoint is developed and evaluated. Although the overall power and type I error rates of the newly proposed methodology and the standard methodology are comparable under the assumption of proportional hazards and event rates less than 50%, the efficiency of using the log-rank test during the interim analysis was realized in terms of an increased probability of early trial termination for overwhelming efficacy resulting in potential for shorter trials and smaller sized trials. Methodology for using the log-rank test was also developed for and applied to trials incorporating an adaptation for sample size re-estimation at interim based on the conditional power of achieving a significant result by the end of the trial. In the context of sample size re-estimation, the use of the log-rank test not only increased the probability of declaring superiority of the experimental treatment over the control at the time of interim analysis, but increased the overall power. Regardless of whether or not sample size re-estimation is used, greater efficiency is attained when the log-rank test is performed at interim analysis as the differential between the percentages of subjects enrolled and with complete follow-up at interim analysis increases.
Author: Jianrong Wu
Publisher: CRC Press
ISBN: 0429892942
Category : Mathematics
Languages : en
Pages : 257
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Book Description
Statistical Methods for Survival Trial Design: With Applications to Cancer Clinical Trials Using R provides a thorough presentation of the principles of designing and monitoring cancer clinical trials in which time-to-event is the primary endpoint. Traditional cancer trial designs with time-to-event endpoints are often limited to the exponential model or proportional hazards model. In practice, however, those model assumptions may not be satisfied for long-term survival trials. This book is the first to cover comprehensively the many newly developed methodologies for survival trial design, including trial design under the Weibull survival models; extensions of the sample size calculations under the proportional hazard models; and trial design under mixture cure models, complex survival models, Cox regression models, and competing-risk models. A general sequential procedure based on the sequential conditional probability ratio test is also implemented for survival trial monitoring. All methodologies are presented with sufficient detail for interested researchers or graduate students.
Author: Gernot Wassmer
Publisher: Springer
ISBN: 3319325620
Category : Medical
Languages : en
Pages : 310
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Book Description
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.
Author: Jianrong Wu
Publisher: CRC Press
ISBN: 1000422488
Category : Mathematics
Languages : en
Pages : 225
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Book Description
Single-Arm Phase II Survival Trial Design provides a comprehensive summary to the most commonly- used methods for single-arm phase II trial design with time-to-event endpoints. Single-arm phase II trials are a key component for successfully developing advanced cancer drugs and treatments, particular for target therapy and immunotherapy in which time-to-event endpoints are often the primary endpoints. Most test statistics for single-arm phase II trial design with time-to-event endpoints are not available in commercial software. Key Features: Covers the most frequently used methods for single-arm phase II trial design with time-to-event endpoints in a comprehensive fashion. Provides new material on phase II immunotherapy trial design and phase II trial design with TTP ratio endpoint. Illustrates trial designs by real clinical trial examples Includes R code for all methods proposed in the book, enabling straightforward sample size calculation.
Author: Christopher Jennison
Publisher: CRC Press
ISBN: 9781584888581
Category : Mathematics
Languages : en
Pages : 416
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Book Description
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.
Author: Geraldine Rauch
Publisher: Springer
ISBN: 3319737708
Category : Medical
Languages : en
Pages : 254
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Book Description
This book addresses the most important aspects of how to plan and evaluate clinical trials with a composite primary endpoint to guarantee a clinically meaningful and valid interpretation of the results. Composite endpoints are often used as primary efficacy variables for clinical trials, particularly in the fields of oncology and cardiology. These endpoints combine several variables of interest within a single composite measure, and as a result, all variables that are of major clinical relevance can be considered in the primary analysis without the need to adjust for multiplicity. Moreover, composite endpoints are intended to increase the size of the expected effects thus making clinical trials more powerful. The book offers practical advice for statisticians and medical experts involved in the planning and analysis of clinical trials. For readers who are mainly interested in the application of the methods, all the approaches are illustrated with real-world clinical trial examples, and the software codes required for fast and easy implementation are provided. The book also discusses all the methods in the context of relevant guidelines related to the topic. To benefit most from the book, readers should be familiar with the principles of clinical trials and basic statistical methods.
Author: Jonathan J. Shuster
Publisher: CRC Press
ISBN: 9780849344879
Category : Medical
Languages : en
Pages : 224
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Book Description
Practical Handbook of Sample Size Guidelines for Clinical Trials is a concise guide and powerful software utility program that provides a valuable, non-technical blueprint for the design and analysis of survival clinical trials. This text and software allow clinical researchers to write more effective protocols or research grant proposals in a fraction of the time it would take them otherwise. Clinical researchers also gain insight into how biostatisticians analyze trial data and discover what "p-values" really tell them. If you are a biostatistician or student, this book and software will be an indispensable tool for study design. Furthermore, no other book provides justification for survival analysis results at such an introductory level. The program increases your flexibility because it allows you to browse through various planning parameter configurations by changing one parameter at a time, circumventing the need to re-enter the set of planning parameters. Practical Handbook of Sample Size Guidelines for Clinical Trials is ideal for biostatisticians, clinical oncologists, epidemiologists, public health specialists, hematologists, and other researchers who need a concise, easy-to-use tool for sample size determination.
Author: Weichung Joe Shih
Publisher: CRC Press
ISBN: 1000462811
Category : Medical
Languages : en
Pages : 320
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Book Description
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: Peter J. Smith
Publisher: CRC Press
ISBN: 1482295709
Category : Mathematics
Languages : en
Pages : 267
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Book Description
Analysis of Failure and Survival Data is an essential textbook for graduate-level students of survival analysis and reliability and a valuable reference for practitioners. It focuses on the many techniques that appear in popular software packages, including plotting product-limit survival curves, hazard plots, and probability plots in the context of censored data. The author integrates S-Plus and Minitab output throughout the text, along with a variety of real data sets so readers can see how the theory and methods are applied. He also incorporates exercises in each chapter that provide valuable problem-solving experience. In addition to all of this, the book also brings to light the most recent linear regression techniques. Most importantly, it includes a definitive account of the Buckley-James method for censored linear regression, found to be the best performing method when a Cox proportional hazards method is not appropriate. Applying the theories of survival analysis and reliability requires more background and experience than students typically receive at the undergraduate level. Mastering the contents of this book will help prepare students to begin performing research in survival analysis and reliability and provide seasoned practitioners with a deeper understanding of the field.
Author: Mark Chang
Publisher: CRC Press
ISBN: 1351214535
Category : Mathematics
Languages : en
Pages : 362
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Book Description
"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.
