Literature DB >> 15992554

Changes in prefrontal activity characterize clinical response in SSRI nonresponders: a pilot study.

Ian A Cook1, Andrew F Leuchter, Melinda L Morgan, William Stubbeman, Barbara Siegman, Michelle Abrams.   

Abstract

Previous studies in unipolar depression have shown that early decreases in prefrontal values of the QEEG cordance measure identified responders to pharmacotherapy. These studies have all examined individuals who were drug-free prior to the first physiologic assessment, yet in the clinical management of treatment resistant depression (TRD), many patients undergo changes in treatment without a drug-free interval between treatments. Here, we investigated whether cordance decreases were associated with response in Stage I TRD subjects without wash-out between treatment trials. Awake EEGs were recorded from 12 adults with unipolar depression. Subjects were receiving naturalistic treatment, had failed SSRI monotherapy, and were starting a new treatment prescribed by their treating psychiatrists. EEG data were recorded before starting the new treatment and after approximately 1 week. Six of the 12 subjects responded to treatment after 8--10 weeks. Five of the six responders showed an early cordance decreases, compared with two of the six nonresponders (accurate characterization in 75% of the cases). Consistent with previous treatment trials, decreases in prefrontal cordance differentiated responders from nonresponders in this setting as well. These findings suggest that cordance biomarkers may be a useful tool in effectiveness trials that parallel clinical practices in SSRI nonresponders, and may not require a wash-out period between treatments.

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Year:  2005        PMID: 15992554     DOI: 10.1016/j.jpsychires.2004.12.002

Source DB:  PubMed          Journal:  J Psychiatr Res        ISSN: 0022-3956            Impact factor:   4.791


  13 in total

1.  The effectiveness of prefrontal theta cordance and early reduction of depressive symptoms in the prediction of antidepressant treatment outcome in patients with resistant depression: analysis of naturalistic data.

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Review 2.  Progress in Elucidating Biomarkers of Antidepressant Pharmacological Treatment Response: A Systematic Review and Meta-analysis of the Last 15 Years.

Authors:  G Voegeli; M L Cléry-Melin; N Ramoz; P Gorwood
Journal:  Drugs       Date:  2017-12       Impact factor: 9.546

3.  Electroencephalographic Biomarkers for Treatment Response Prediction in Major Depressive Illness: A Meta-Analysis.

Authors:  Alik S Widge; M Taha Bilge; Rebecca Montana; Weilynn Chang; Carolyn I Rodriguez; Thilo Deckersbach; Linda L Carpenter; Ned H Kalin; Charles B Nemeroff
Journal:  Am J Psychiatry       Date:  2018-10-03       Impact factor: 18.112

Review 4.  Biomarkers to predict antidepressant response.

Authors:  Andrew F Leuchter; Ian A Cook; Steven P Hamilton; Katherine L Narr; Arthur Toga; Aimee M Hunter; Kym Faull; Julian Whitelegge; Anne M Andrews; Joseph Loo; Baldwin Way; Stanley F Nelson; Steven Horvath; Barry D Lebowitz
Journal:  Curr Psychiatry Rep       Date:  2010-12       Impact factor: 5.285

5.  Midline and right frontal brain function as a physiologic biomarker of remission in major depression.

Authors:  Ian A Cook; Aimee M Hunter; Michelle Abrams; Barbara Siegman; Andrew F Leuchter
Journal:  Psychiatry Res       Date:  2009-10-22       Impact factor: 3.222

6.  Baseline and treatment-emergent EEG biomarkers of antidepressant medication response do not predict response to repetitive transcranial magnetic stimulation.

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7.  Evaluation of quantitative EEG by classification and regression trees to characterize responders to antidepressant and placebo treatment.

Authors:  M Rabinoff; C M R Kitchen; I A Cook; A F Leuchter
Journal:  Open Med Inform J       Date:  2011-02-11

Review 8.  Predictors, moderators, and mediators (correlates) of treatment outcome in major depressive disorder.

Authors:  George I Papakostas; Maurizio Fava
Journal:  Dialogues Clin Neurosci       Date:  2008       Impact factor: 5.986

Review 9.  Advances in Electrophysiological Research.

Authors:  Chella Kamarajan; Bernice Porjesz
Journal:  Alcohol Res       Date:  2015

Review 10.  Depression and Sleep.

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Journal:  Int J Mol Sci       Date:  2019-01-31       Impact factor: 5.923

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