Bayesian Biostatistics and Diagnostic Medicine: 1st Edition (Hardback) book cover

Bayesian Biostatistics and Diagnostic Medicine

1st Edition

By Lyle D. Broemeling

Chapman and Hall/CRC

216 pages | 26 B/W Illus.

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Hardback: 9781584887676
pub: 2007-07-12
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Description

There are numerous advantages to using Bayesian methods in diagnostic medicine, which is why they are employed more and more today in clinical studies. Exploring Bayesian statistics at an introductory level, Bayesian Biostatistics and Diagnostic Medicine illustrates how to apply these methods to solve important problems in medicine and biology.

After focusing on the wide range of areas where diagnostic medicine is used, the book introduces Bayesian statistics and the estimation of accuracy by sensitivity, specificity, and positive and negative predictive values for ordinal and continuous diagnostic measurements. The author then discusses patient covariate information and the statistical methods for estimating the agreement among observers. The book also explains the protocol review process for cancer clinical trials, how tumor responses are categorized, how to use WHO and RECIST criteria, and how Bayesian sequential methods are employed to monitor trials and estimate sample sizes.

With many tables and figures, this book enables readers to conduct a Bayesian analysis for a large variety of interesting and practical biomedical problems.

Reviews

It is interesting to read this book on Bayesian biostatistics and diagnostic medicine. … this book has several unique features. … an excellent introductory textbook on Bayesian methods and their application in diagnostic medicine. Non-experienced statisticians may also find that the systematic overview of the classification and purposes of the three phases in clinical trials and the basic Bayesian theory are useful references and would benefit from the program codes, particularly WinBUGS codes. …

Pharmaceutical Statistics, 2011, 10

…the inclusion of plenty of real examples plus details of the necessary BUGS code was a very positive attribute. Some of the data sets are available for the reader to analyse and this would further enhance understanding. Overall, it is certainly a useful read or reference book for a practicing statistician with a good baseline theoretical knowledge who would like to expand their interest in this specific field of application.

—A. Wade, University College London, Journal of the Royal Statistical Society, Series A, 2010

This book is quite a good one for a statistician that is (or training to be) a statistical consultant to a cancer center department of diagnostic imaging … . If you are such a person, this book should be in your library.

—David Booth, Technometrics, August 2010

Drawing on his collaborative experiences with medical researchers and his long-standing interests in Bayesian methods, the author of this book shows how the Bayesian approach can be used to advantage when medical diagnosis is based on data with uncertainty. … a general strength of the book is careful discussion of study designs and protocols, which is a bonus relative to many biostatistical books written from a more narrow theory and methods perspective. … A real strength is the strong integration between models and concepts on the one hand, and real studies on the other hand. The inclusion of WinBUGS code is also a plus. … this book is highly recommended for anyone whose interests touch on the statistical side of diagnostic medicine.

Biometrics, March 2009

Table of Contents

INTRODUCTION

Introduction

Statistical Methods in Diagnostic Medicine

Preview of Book

Datasets for Book

Software

References

DIAGNOSTIC MEDICINE

Introduction

Imaging Modalities

Activities in Diagnostic Medicine

Accuracy and Agreement

Developmental Trials for Imaging

Protocol Review and Clinical Trials

The Literature

References

OTHER DIAGNOSTIC PROCEDURES

Introduction

Sentinel Lymph Node Biopsy for Melanoma

Tumor Depth for Diagnosis of Metastatic Melanoma

A Biopsy of Non-Small Cell Lung Cancer

Coronary Artery Disease

BAYESIAN STATISTICS

Introduction

Bayes Theorem

Prior Information

Posterior Information

Inference

Sample Size

Computing

Exercises

References

BAYESIAN METHODS FOR DIAGNOSTIC ACCURACY

Introduction

Study Design

Bayesian Methods for Diagnostic Accuracy: Binary and Ordinal Data

Bayesian Methods for Test Accuracy: Quantitative Variables

Clustered Data

Comparing Accuracy between Modalities

Sample Size Determination

Exercises

References

REGRESSION AND TEST ACCURACY

Introduction

The Audiology Study

The ROC Curve and Patient Covariates

Exercises

References

AGREEMENT

Introduction

Agreement for Discrete Ratings

Agreement for a Continuous Response

Combining Reader Information

Exercises

References

DIAGNOSTIC IMAGING AND CLINICAL TRIALS

Introduction

Clinical Trials

The Protocol

Guidelines for Tumor Response

Bayesian Sequential Stopping Rules

Software for Clinical Trials

Examples

Exercises

References

OTHER TOPICS

Introduction

Imperfect Diagnostic Test Procedures

Test Accuracy and Survival Analysis

ROC Curves with a Non-Binary Gold Standard

Periodic Screening in Cancer

Decision Theory and Diagnostic Accuracy

Exercises

References

Subject Categories

BISAC Subject Codes/Headings:
MAT029000
MATHEMATICS / Probability & Statistics / General
MED080000
MEDICAL / Radiology & Nuclear Medicine