Bayesian Precision Medicine

Bayesian Precision Medicine provides modern Bayesian statistical models and methods for identifying treatments tailored to individual patients, with practical examples and applications to oncology trials. It discusses the connection between causal analysis and statistical inference, reviews personalized Bayesian clinical trial designs, and presents adaptive methods for clustering similar patient subgroups. The book is aimed at biostatisticians and medical researchers who want to apply modern Bayesian methods to their clinical trials and data analyses.

Format: Hardback
Length: 318 pages
Publication date: 07 May 2024
Publisher: Taylor & Francis Ltd

Bayesian Precision Medicine presents cutting-edge Bayesian statistical models and methodologies for identifying personalized treatments tailored to individual patients based on their prognostic variables and predictive biomarkers. The book thoroughly explains and illustrates the process of evaluating and comparing treatments through practical examples, followed by a discussion of causal analysis and its relationship to statistical inference. It also showcases a wide array of modern Bayesian clinical trial designs, with applications to various oncology trials. The later chapters delve into Bayesian nonparametric regression analyses of datasets derived from multi-stage chemotherapy for acute leukemia, allogeneic stem cell transplantation, and targeted agents for treating advanced breast cancer.

Key Features:
1. Describes the connection between causal analysis and statistical inference.
2. Reviews 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 applications.
3. Presents adaptive methods for clustering similar patient subgroups to improve efficiency.
4. Describes Bayesian nonparametric regression analyses of real-world datasets from oncology.
5. Provides pointers to software for implementation.

Target Audience:
Bayesian Precision Medicine is primarily aimed at biostatisticians and medical researchers who seek to apply modern Bayesian methods to their own clinical trials and data analyses. It can also be used as a teaching resource for a special topics course on precision medicine, particularly for postgraduate biostatistics students. The book's main goal is to demonstrate how Bayesian thinking can provide a practical scientific basis for tailoring treatments to individual patients.

In conclusion, Bayesian Precision Medicine offers a comprehensive and practical guide to modern Bayesian statistical models and methodologies for personalized treatment identification. It provides a solid foundation for biostatisticians and medical researchers to apply Bayesian thinking in their clinical trials and data analyses, ultimately advancing precision medicine and improving patient outcomes.

Weight: 692g
Dimension: 158 x 243 x 27 (mm)
ISBN-13: 9781032754468