Evidence-Based Diagnosis

Thomas B. Newman · Michael A. Kohn

Feb. 2009 · Cambridge University Press

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Evidence-Based Diagnosis explains 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 needing only a minimum of mathematics, the quantitative discussions in this book are deeper and more rigorous than in most introductory texts. The book includes numerous worked examples and 60 problems (with answers) based on real clinical situations and journal articles. This book is a great choice for anyone looking to select, develop, or apply medical tests. Topics covered include: the diagnostic process; test reliability and accuracy; testing and treatment thresholds; critical appraisal of studies of diagnostic, screening and prognostic tests; test independence and methods of combining tests; quantifying treatment benefits using randomized trials and observational studies; Bayesian interpretation of P values and confidence intervals; challenges for evidence-based diagnosis; likelihood ratios and ROC curves.

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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.