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Adaptive treatment strategies in practice : planning trials and analyzing data for personalized medicine
Title
Adaptive treatment strategies in practice : planning trials and analyzing data for personalized medicine / edited by Michael Kosorok, Erica Moodie.
ISBN
9781611974188
9781611974171
Publication
Philadelphia, Pennsylvania : Society for Industrial and Applied Mathematics (SIAM, 3600 Market Street, Floor 6, Philadelphia, PA 19104), [2015]
Physical Description
1 PDF (xvi, 348 pages).
Local Notes
Access is available to the Yale community.
Notes
Title from title screen, viewed 11/9/2015.
Access and use
Access restricted by licensing agreement.
Summary
Personalized medicine is a medical paradigm that emphasizes systematic use of individual patient information to optimize that patient's health care, particularly in managing chronic conditions and treating cancer. In the statistical literature, sequential decision making is known as an adaptive treatment strategy (ATS) or a dynamic treatment regime (DTR). The field of DTRs emerges at the interface of statistics, machine learning, and biomedical science to provide a data-driven framework for precision medicine. The authors provide a learning-by-seeing approach to the development of ATSs, aimed at a broad audience of health researchers. All estimation procedures used are described in sufficient heuristic and technical detail so that less quantitative readers can understand the broad principles underlying the approaches. At the same time, more quantitative readers can implement these practices. Adaptive Treatment Strategies in Practice: Planning Trials and Analyzing Data for Personalized Medicine provides the most up-to-date summary of the current state of the statistical research in personalized medicine, contains chapters by leaders in the area from both the statistics and computer sciences fields, contains a range of practical advice, introductory and expository materials, and case studies.
Variant and related titles
SIAM ebooks.
Other formats
Print version:
Format
Books / Online
Language
English
Added to Catalog
April 16, 2021
Series
ASA-SIAM statistics and applied probability series
Bibliography
Includes bibliographical references and index.
Contents
Preface
1. Introduction
part I. Design of trials for estimating dynamic treatment regimes
2. DTRs and SMARTs : definitions, designs, and applications
3. Efficient design for clinically relevant intent-to-treat comparisons
4. SMART design, conduct, and analysis in oncology
5. Sample size calculations for clustered SMART designs
part II. Practical challenges in dynamic treatment regime analyses
6. Analysis in the single-stage setting : an overview of estimation approaches for dynamic treatment regimes
7. G-estimation for dynamic treatment regimes in the longitudinal setting
8. Outcome weighted learning methods for optimal dynamic treatment regimes
9. Value search estimators for optimal dynamic treatment regimes
10. Evaluation of longitudinal dynamics with and without marginal structural working models
11. Imputation strategy for SMARTs
12. Clinical trials for personalized dose finding
13. Methods for analyzing DTRs with censored survival data
14. Outcome weighted learning with a reject option
15. Estimation of dynamic treatment regimes for complex outcomes : balancing benefits and risks
16. Practical reinforcement learning in dynamic treatment regimes
17. Reinforcement learning applications in clinical trials.
Publisher's number
SA21 SIAM
Subjects
Also listed under
Society for Industrial and Applied Mathematics, publisher.
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