Overview
- Discusses methods for planning and evaluating clinical trials with a composite primary endpoint
- Offers software codes for the implementation of methods
- Summarizes current medical and methodology guideline documents on composite endpoints
- Includes recommendations and guidance for planning clinical trials with composite endpoints
- Provides numerous examples from clinical trials illustrating the different methods
Part of the book series: Springer Series in Pharmaceutical Statistics (SSPS)
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Table of contents (20 chapters)
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Front Matter
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Part II
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Front Matter
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Keywords
About this book
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.
Authors and Affiliations
About the authors
Since 2017, Prof. Dr. Geraldine Rauch has been a professor of Medical Biometry and Director of the Institute of Biometry and Clinical Epidemiology at the Charité Universitätsmedizin Berlin. Prior to that, she had a professorship at the University Medical Center Hamburg-Eppendorf. From 2009 to 2016, she worked at the Institute of Medical Biometry and Informatics, Heidelberg, where she finished her habilitation thesis in 2015. She studied Mathematics at the University of Bremen, and prepared her PhD thesis at Roche Diagnostics GmbH in Penzberg.
Prof. Dr. Meinhard Kieser studied Mathematics at the University of Heidelberg and received his PhD in Medical Biometry in 1992. After that, he worked for more than 15 years as a biostatistician and Head of Biometrics in the pharmaceutical industry. In 2001, he completed his habilitation thesis. Since 2008, he has been a professor of Medical Biometry and Director of the Institute of Medical Biometry and Informatics at the University of Heidelberg.Svenja Schüler studied Mathematics at the University of Kiel and graduated in 2013. Since then, she has been working as a research fellow at the Institute of Medical Biometry and Informatics at the University of Heidelberg. In her doctorial thesis, funded by the German Research Foundation, she is developing statistical methods for the analysis of composite endpoints.
Bibliographic Information
Book Title: Planning and Analyzing Clinical Trials with Composite Endpoints
Authors: Geraldine Rauch, Svenja Schüler, Meinhard Kieser
Series Title: Springer Series in Pharmaceutical Statistics
DOI: https://doi.org/10.1007/978-3-319-73770-6
Publisher: Springer Cham
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: Springer International Publishing AG, part of Springer Nature 2017
Hardcover ISBN: 978-3-319-73769-0Published: 31 May 2018
Softcover ISBN: 978-3-030-08855-2Published: 09 December 2018
eBook ISBN: 978-3-319-73770-6Published: 22 May 2018
Series ISSN: 2366-8695
Series E-ISSN: 2366-8709
Edition Number: 1
Number of Pages: XVI, 255
Number of Illustrations: 7 b/w illustrations, 2 illustrations in colour
Topics: Statistics for Life Sciences, Medicine, Health Sciences, Biostatistics, Pharmaceutical Sciences/Technology