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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This well-written textbook is the ideal synopsis for clinicians, researchers, editors, and policy-makers who are engaged in diagnostic and prognostic decision making. The authors provide a concise, precisely referenced, and pragmatic discussion of diagnostic science, including test reliability and accuracy, interval likelihood ratios, and test-treatment thresholds. Problem sets based upon published studies are included with helpful and appropriately detailed answer keys. Readers will undoubtedly reference this textbook repeatedly as new diagnostic and prognostic research emerges in coming years.
2 Reliability and measurement error
3 Dichotomous tests
4 Multilevel and continuous tests
5 Critical appraisal of studies of diagnostic tests
6 Screening tests
7 Prognostic tests and studies
8 Multiple tests and multivariable decision rules