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Evidence-Based Diagnosis

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Overview

Evidence-Based Diagnosis is a textbook about diagnostic, screening, and prognostic tests in clinical medicine. The authors' approach is based on many years of experience teaching physicians in a clinical research training program. Although requiring only a minimum of mathematics knowledge, the quantitative discussions in this book are deeper and more rigorous than those in most introductory texts. The book includes numerous worked examples and 60 problems (with answers) based on real clinical situations and journal articles. The book will be helpful and accessible to anyone looking to select, develop, or market medical tests. Topics covered include:
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Editorial Reviews

Doody's Review Service
Reviewer: Martha L Carvour, MD, PhD (University of Iowa College of Public Health)
Description: This book provides a working statistical framework for the assessment and integration of diagnostic tests in the clinical setting. Topics include the interpretation of diagnostic and prognostic data, including information derived from routine clinical tests as well as the medical literature. All topics are presented with the clinician's perspective in mind, using clinically relevant in-text examples and multiple sample problems with each chapter.
Purpose: The authors set out to demystify the statistical principles underlying evidence-based medicine, particularly those related to diagnostic testing, in a format accessible to clinicians. Effective teaching tools and resource materials in this field are widely sought after. This book may offer a useful supplement to an evidence-based medicine curriculum but will be less useful as a reference guide for busy clinicians.
Audience: The authors apply years of experience in both the clinic and classroom to address a broad clinical audience. The book is geared toward residents, fellows, and junior faculty, although students could make use of it early in their evidence-based medicine training. The sample problems may also be useful during preparation for board exams. To many in the clinical arena, this may come across as a clinically relevant but statistically daunting book.
Features: Topics covered range from common terms in evidence-based medicine — sensitivity, specificity, and positive and negative predictive values — to those less thoroughly addressed by some resources in the field, such as measures of reliability, likelihood ratios, and propensity scores. The authors provide many illustrative, clinically relevant examples and sample problems, along with a detailed answer key. On the whole, however, the figures are a bit text-heavy (or data-heavy) for the intended audience.
Assessment: While this book is not intended to review all concepts in a complete evidence-based medicine curriculum, it may serve as a useful supplement for existing curricula or for board exam preparation. The format will appeal most strongly to readers interested in the statistical underpinnings of evidence-based diagnosis. However, sections pertaining to critical appraisal of the clinical literature and interpretation of p-values and confidence intervals may be worthwhile to readers at any stage in their clinical training.
From the Publisher
"The authors apply years of experience in both the clinic and classroom to address a broad clinical audience. The book is geared toward residents, fellows, and junior faculty, although students could make use of it early in their evidence-based medicine training...Topics covered range from common terms in evidence-based medicine — sensitivity, specificity, and positive and negative predictive values — to those less thoroughly addressed by some resources in the field, such as measures of reliability, likelihood ratios, and propensity scores. The authors provide many illustrative, clinically relevant examples and sample problems, along with a detailed answer key...The format will appeal most strongly to readers interested in the statistical underpinnings of evidence-based diagnosis."
Doody's Review Service

"The book has an appealing pedagogical touch and shows that the authors have a long experience as teachers. This is reflected in the selection of applications, case studies and the problems adapted for self-studies, with solutions supplied at the end of the book."
European Journal of Public Health

"This excellent new textbook thoroughly explains all aspects of a reasoned approach to diagnostic decision making… Evidence-Based Diagnosis should now become the definitive text for this corner of the evidence-based medicine library. It teaches the skills necessary to adopt a thoroughly reasoned diagnostic approach, and although aimed at academicians, it is written so that it can and should be used by a broader audience of trainees and clinicians."
Michael J. Steiner, Academic Pediatrics 2010; 10(1):75

"This is a book on diagnostic testing aimed at an audience of clinicians, with those of an academic interest in focus, but it should also be of great value for anyone with an interest of practical applications of evidence-based medicine… The book has an appealing pedagogical touch and shows that the authors have a long experience as teachers... For those with basic knowledge of statistics, this is an excellent follow-up and in-depth continuation into applications on diagnostic tests and treatment effect analysis."
Lennart Bodin, European Journal of Public Health 2009;20(1):120

“ The amazing part is that the authors explain complex concepts with minimal math, to avoid frustrating the novice clinician... For those with a basic level of knowledge, this is an excellent resource to enhance and expand your understanding of diagnostic testing and its applications in trials."
Abhinav Chandra, Academic Emergency Medicine 2010;17(6):e51

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Product Details

  • ISBN-13: 9780521714020
  • Publisher: Cambridge University Press
  • Publication date: 2/16/2009
  • Edition description: New Edition
  • Pages: 312
  • Product dimensions: 6.90 (w) x 9.80 (h) x 0.80 (d)

Meet the Author

Thomas B. Newman, currently Chief of the Division of Clinical Epidemiology and Professor of Epidemiology and Biostatistics and Pediatrics at the University of California, San Francisco, previously served as Associate Director of the UCSF/Stanford Robert Wood Johnson Clinical Scholars Program and Associate Professor in the Department of Laboratory Medicine at UCSF. He is a co-author of Designing Clinical Research and a currently practicing pediatrician.

Michael A. Kohn is Associate Professor of Epidemiology and Biostatistics at the University of California, San Francisco, where he teaches clinical epidemiology and evidence-based medicine. He is also an emergency physician with more than 20 years of clinical experience, currently practising at Mills-Peninsula Medical Center in Burlingame, California.

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Table of Contents

1 Introduction: understanding diagnosis and diagnostic testing 1

2 Reliability and measurement error 10

3 Dichotomous tests 39

4 Multilevel and continuous tests 68

5 Critical appraisal of studies of diagnostic tests 94

6 Screening tests 116

7 Prognostic tests and studies 138

8 Multiple tests and multivariable decision rules 156

9 Quantifying treatment effects using randomized trials 186

10 Alternatives to randomized trials for estimating treatment effects 206

11 Understanding P-values and confidence intervals 220

12 Challenges for evidence-based diagnosis 239

Answers to problems 255

Index 287

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