Evidence-Based Diagnosis: An Introduction to Clinical Epidemiology / Edition 2

by Thomas B. Newman, Michael A. Kohn

Overview

Medicine is becoming increasingly reliant on diagnostic, prognostic and screening tests for the successful treatment of patients. With new tests being developed all the time, a more informed understanding of the benefits and drawbacks of these tests is crucial. Providing readers with the tools needed to evaluate and interpret these tests, numerous real-world examples demonstrate the practical application and relevance of the material. The mathematics involved are rigorously explained using simple and informative language. Topics covered include the diagnostic process, reliability and accuracy of tests, and quantifying treatment benefits using randomized trials, amongst others. Engaging illustrations act as visual representations of the concepts discussed in the book, complementing the textual explanation. Based on decades of experience teaching in a clinical research training program, this fully updated second edition is an essential guide for anyone looking to select, develop or market medical tests.

Product Details

ISBN-13:	9781108436717
Publisher:	Cambridge University Press
Publication date:	06/25/2020
Edition description:	2nd Revised ed.
Pages:	405
Product dimensions:	6.14(w) x 9.25(h) x 0.63(d)

About the Author

Thomas B. Newman is the Professor Emeritus of Epidemiology & Biostatistics and Pediatrics at the University of California San Francisco, USA.

Michael A. Kohn is a Professor of Epidemiology & Biostatistics at the University of California San Francisco, USA.

Table of Contents

1. Introduction: Understanding Diagnosis and Evidence-Based Diagnosis; 2. Dichotomous Tests; 3. Multilevel and Continuous Tests; 4. Critical Appraisal of Studies of Diagnostic Test Accuracy; 5. Reliability and Measurement Error; 6. Risk Predictions; 7. Multiple Tests and Multivariable Decision Rules; 8. Quantifying Treatment Effects Using Randomized Trials; 9. Alternatives to Randomized Trials for Estimating Treatment Effects; 10. Screening Tests; 11. Understanding P-Values and Confidence Intervals; 12. Challenges for Evidence-Based Diagnosis; Problems and Answers; Index