An Application of Bayes ’ Rule to Diagnostic Test Evaluation

It is often the case that a clinician has diagnostic values such as sensitivity and specificity available for a certain diagnostic test but not the positive or negative predictive values. Because the clinician uses these predictive values to make decisions concerning the well-being of the patient, it is important to be able to compute them from the sensitivity and specificity. This article presents a well-established theorem called Bayes ’ rule for doing this. A brief, intuitive development of Bayes’ rule and the framework for this application is given with a minimum of mathematics and without proofs. Several examples are provided. Key words: contingency table, prevalence rate, prob-ability, sensitivity, specificity. Bayes ’ rule, sometimes called Bayes ’ theorem, i