Diagnostic tests are typically evaluated using performance measures, such as sensitivity, specificity, positive and negative predictive values, accuracy, and likelihood ratios. Numerous criteria have been suggested as to the types of diagnostic scenarios for which each of these measures is most important. Reports in the medical literature will often characterize a test by the values of some, but not all, of these performance measures. At times the unreported measures can be of interest in evaluating whether to use a test. A set of formulas is presented which, in many cases, enables one to determine unreported measures from those provided, for example, accuracy from sensitivity, specificity, and positive predictive value. The relationships between the measures of diagnostic test effectiveness and the prevalence of disease are discussed. An application to the diagnosis of acute myocardial infarction with new biochemical markers is used to illustrate these relationships.