A new index of clinical utility for diagnostic tests.

A new interesting article has been published in Scand J Clin Lab Invest. 2019 Dec; 79(8):560-565. doi: 10.1080/00365513.2019.1677938. Epub 2019 Nov 1. and titled:

A new index of clinical utility for diagnostic tests.

Authors of this article are:

Åsberg A, Mikkelsen G, Odsæter IH.

A summary of the article is shown below:

Clinical utility of a diagnostic test depends on its diagnostic accuracy, the pretest probability of disease and the clinical consequences of the test results. Tools for evaluating clinical utility are scarce. We propose a new clinical utility index (CUI), which is the expected gain in utility (EGU) of the test divided by the EGU of an ideal test, both adjusted for EGU of the optimal clinical action without testing. The index expresses the relative benefit of using the test compared to using an optimal test when making a clinical decision. To illustrate how the index may be used, we estimated CUI for fasting glucose, both as a continuous and as a dichotomous test, at several values of pretest probability of diabetes mellitus and at two levels of cost/benefit-ratio. In the same clinical situations we also estimated CUI for the 2 h glucose tolerance test. Hemoglobin A1c ≥ 48 mmol/mol was used as a reference standard for diabetes mellitus. In this model, fasting glucose was clinically more useful as a continuous test than as a dichotomous one, based on CUIs. At pretest probability above the treatment threshold, fasting glucose as a continuous test was even more useful than the complete glucose tolerance test. These results are not necessarily generalizable; however, they show how the CUI can be used to select the most useful test in certain clinical situations.

Check out the article’s website on Pubmed for more information:

[link-preview url=https://www.ncbi.nlm.nih.gov/pubmed/31675254 forceshot=true]

This article is a good source of information and a good way to become familiar with topics such as: Cost benefit analysis; ROC analysis; error, diagnostic; logistic regression; sensitivity; specificity.


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