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Bayesian Precision Medicine

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PublisherChapman and Hall/CRC
ISBN 139781032754468
ISBN 10103275446X
AuthorPeter F. Thall
Book FormatHardcover
LanguageEnglish
Book DescriptionBayesian Precision Medicine presents modern Bayesian statistical models and methods for identifying treatments tailored to individual patients using their prognostic variables and predictive biomarkers. The process of evaluating and comparing treatments is explained and illustrated by practical examples, followed by a discussion of causal analysis and its relationship to statistical inference. A wide array of modern Bayesian clinical trial designs are presented, including applications to many oncology trials. The later chapters describe Bayesian nonparametric regression analyses of datasets arising from multistage chemotherapy for acute leukemia, allogeneic stem cell transplantation, and targeted agents for treating advanced breast cancer.Features:Describes the connection between causal analysis and statistical inferenceReviews modern personalized Bayesian clinical trial designs for dose-finding, treatment screening, basket trials, enrichment, incorporating historical data, and confirmatory treatment comparison, illustrated by real-world applicationsPresents adaptive methods for clustering similar patient subgroups to improve efficiencyDescribes Bayesian nonparametric regression analyses of real-world datasets from oncologyProvides pointers to software for implementationBayesian Precision Medicine is primarily aimed at biostatisticians and medical researchers who desire to apply modern Bayesian methods to their own clinical trials and data analyses. It also might be used to teach a special topics course on precision medicine using a Bayesian approach to postgraduate biostatistics students. The main goal of the book is to show how Bayesian thinking can provide a practical scientific basis for tailoring treatments to individual patients.
About the AuthorPeter F. Thall is a global leader in the development and application of Bayesian methods in medical research, with over 300 publications in professional journals. His research interests include Bayesian statistics, clinical trial design, precision medicine, and dynamic treatment regimes.
Publication Date7 May 2024
Number of Pages318 pages

Bayesian Precision Medicine

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