Evidence-Based Diagnosis

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.

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.