A fundamental concept of information theory, relative entropy and mutual information, is directly applicable to evaluation of diagnostic test performance. The aim of this study is to demonstrate how basic concepts in information theory apply to the problem of quantifying major depressive disorder diagnostic test performance. In this study, the performances of the Dexamethasone Suppression Test-DST and the Thyroid-Stimulating Hormone Test-TSH, two of the diagnosis tests of Major Depressive Disorder, are evaluated with the method of Information Theory. The amount of information gained by performing a diagnostic test can be quantified by calculating the relative entropy between the posttest and pretest probability distributions. And also demonstrates that diagnostic test performance can be quantified as the average amount of information the test result provides about the disease state. It is aimed that this study will hopefully give various points of view to the researchers who want to make research on this subject by explaining how the tests used for the diagnosis of various diseases are evaluated with this way.

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