Research Article| Volume 27, ISSUE 9, P990-1006, May 01, 1990

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Optimizing REM latency as a diagnostic test for depression using receiver operating characteristic analysis and information theory

  • Eugene Somoza
    Address reprint requests to Eugene Somoza, M.D., Ph.D., Director, Psychiatric Evaluation Center 116A, Veterans Administration Medical Center, 3200 Vine Street, Cincinnati, Ohio 45220, USA.
    Psyciatry Service, Veterans Administration Medical Center, Cincinnati, USA

    Division of Neuroscience, Psychiatry Department, University of Cincinnati Medical Center, Cincinnati, Ohio, USA

    Millcreek Psychiatric Center for Children, Paddock Road, Cincinnati, USA

    Department of Psychiatry, University of Cincinnati Medical Center, Cincinnati, Ohio, USA
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  • Douglas Mossman
    Psyciatry Service, Veterans Administration Medical Center, Cincinnati, USA

    Division of Neuroscience, Psychiatry Department, University of Cincinnati Medical Center, Cincinnati, Ohio, USA

    Millcreek Psychiatric Center for Children, Paddock Road, Cincinnati, USA

    Department of Psychiatry, University of Cincinnati Medical Center, Cincinnati, Ohio, USA
    Search for articles by this author
  • Author Footnotes
    1 The authors thank Mr. Luis Soutullo-Esperson for his excellent work in the production of the computer-generated figures.
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      New diagnostic techniques must be evaluated for their intrinsic accuracy and for their applicability to particular patient groups in specific clinical settings. Using receiver operating characteristics (ROC) analysis and concepts from information theory, we have developed a new mathematical and graphical method that can evaluate, compare, and optimize the performance of diagnostic tests for any value of disorder prevalence. Our analytic method is appropriate to any test that sorts disordered from nondisordered subjects using a continuous or nonbinary diagnostic variable; its characterization of the fundamental properties of such tests thus has important implications for the evaluation and optimization of diagnostic modalities used by clinicians in all medical specialties. We demonstrate our method using published data from five studies that used sleep architecture as a “biological marker” for depression. Our analysis confirms that REM latency is comparable to the dexamethasone suppression test in its ability to discriminate depressed from control subjects. For each of the five studies, we show how optimal REM latency cut-off times may be selected so that diagnostic information yield is maximized, and we compare the ability of each study to detect depressed subjects in populations where the prevalence of affective disorder can be specified.
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