Book description
Get the tools you need to use SAS® in clinical trial design! Unique and multifaceted, Modern Approaches to Clinical Trials Using SAS: Classical, Adaptive, and Bayesian Methods, edited by Sandeep M. Menon and Richard C. Zink, thoroughly covers several domains of modern clinical trial design: classical, group sequential, adaptive, and Bayesian methods that are applicable to and widely 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, the book touches on a wide variety of topics, including dose-response and dose-escalation designs; sequential methods to stop trials early for overwhelming efficacy, safety, or futility; Bayesian designs that incorporate historical data; adaptive sample size re-estimation; adaptive randomization to allocate subjects to more effective treatments; and population enrichment designs. Methods are illustrated using clinical trials from diverse therapeutic areas, including dermatology, endocrinology, infectious disease, neurology, oncology, and rheumatology. Individual chapters are authored by renowned contributors, experts, and key opinion leaders from the pharmaceutical/medical device industry or academia. Numerous real-world examples and sample SAS code enable users to readily apply novel clinical trial design and analysis methodologies in practice.Table of contents
- Title Page
- Copyright
- Foreword
- About This Book
- About the Author
- Acknowledgments
-
Chapter 1: Overview of Clinical Trials in Support of Drug Development
- 1.1 Introduction
- 1.2 Evolution of Clinical Trials and the Emergence of Guidance Documents
- 1.3 Emergence of Group Sequential Designs in the 70s and 80s
- 1.4 Emergence of Adaptive Designs in the 90s
- 1.5 Widespread Research on Adaptive Designs Since the Turn of the 21st Century
- 1.6 Opportunities and Challenges in Designing, Conducting, and Analyzing Adaptive Trials
- 1.7 The Future of Adaptive Trials in Clinical Drug Development
- References
- Authors
- Chapter 2: Designing and Monitoring Group Sequential Clinical Trials
- Chapter 3: Sample Size Re-estimation
- Chapter 4: Bayesian Survival Meta-Experimental Design Using Historical Data
- Chapter 5: Continual Reassessment Methods
- Chapter 6: Classical Dose-Response Study
- Chapter 7: Implementing the MCP-Mod Procedure for Dose-Response Testing and Estimation
- Chapter 8: Bayesian Dose Response
- Chapter 9: Overview of Adaptive Randomization
-
Chapter 10: Optimal Response-Adaptive Randomization Designs in Binary Outcome Clinical
Trials
- 10.1 Introduction
- 10.2 Optimal Allocation
- 10.3 Response-Adaptive Randomization for Implementing Optimal Allocation
- 10.4 Simulation of Optimal Response-Adaptive Randomization Procedures
- 10.5 Power and Sample Size for Response-Adaptive Randomization
- 10.6 Additional Considerations
- 10.7 Examples
- 10.8 Summary
- References
- Authors
- Chapter 11: Population Enrichment Designs
- Index
- Additional Resources
Product information
- Title: Modern Approaches to Clinical Trials Using SAS: Classical, Adaptive, and Bayesian Methods
- Author(s):
- Release date: December 2015
- Publisher(s): SAS Institute
- ISBN: 9781629600826
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