Bayesian Biostatistics and Diagnostic Medicine

Bayesian Biostatistics and Diagnostic Medicine

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ISBN 9781584887676
Cat# C7672

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Features

  • Presents various fields where Bayesian statistics is used in diagnostic medicine, from imaging to pathology to surgery
  • Uses WinBUGS® and Minitab® for statistical calculations
  • Provides examples that are based on actual consulting activities
  • Covers unique topics not found in other books, such as agreement among observers and the analysis and design of Phase I and II clinical trials
  • Explores the receive operating characteristic (ROC) curve for determining diagnostic accuracy
  • Discusses previous experimental studies of the Bayesian approach that can be used in the design of future diagnostic studies
  • Summary

    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.

    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

    Editorial 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