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Diagnostic Decision: Probability Theory in the Use of Diagnostic Tests
An Introduction to Critical Study of the Literature
Abstract
The purpose of this article is to provide an understanding of methods that are useful in formulating advice about when to use diagnostic tests. If the clinician expresses diagnostic uncertainty as the probability of a disease in a patient, Bayes' theorem may be used to predict the effect of doing various tests and their impact on patient management. To use Bayes' theorem wisely, one must be aware of pitfalls in estimating probability and must understand the limitations of most studies of the sensitivity and specificity of diagnostic tests.
Article and Author Information
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▸From the Division of General Internal Medicine, Stanford University School of Medicine, Palo Alto Veterans Administration Medical Center; Palo Alto, California.
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▸The section consultants for Diagnostic Decision papers are John M. Eisenberg, M.D., and Sankey V. Williams, M.D. This paper and the series referred to by Dr. Sox in his first paragraph will be published in a collective reprint, the availability of which will be announced later.—The Editor.
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▸Requests for reprints should be addressed to Harold C. Sox, Jr., M.D.; Palo Alto Veterans Administration Medical Center, 3801 Miranda Avenue; Palo Alto, CA 94304.
