Information about the performance of diagnostic tests is typically presented in the form of measures of test accuracy such as sensitivity and specificity. These measures may be difficult to translate directly into decisions about patient treatment, for which information presented in the form of probabilities of disease after a positive or a negative test result may be more useful. These probabilities depend on the prevalence of the disease, which is likely to vary between populations. This article aims to clarify the relationship between pre-test (prevalence) and post-test probabilities of disease, and presents two free, online, interactive tools to illustrate this relationship. These tools allow probabilities of disease to be compared to decision thresholds above and below which different treatment decisions may be indicated. They are intended to help those involved in communicating information about diagnostic test performance and are likely to be of benefit when teaching these concepts. A substantive example is presented using C-reactive protein as a diagnostic marker for bacterial infection in the older adult population. The tools may also be useful for manufacturers of clinical tests in planning product development, for authors of test evaluation studies to improve reporting, and for users of test evaluations to facilitate interpretation and application of the results
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