Literature DB >> 19712979

Comparative effectiveness of biomarkers and clinical indicators for predicting outcomes of SSRI treatment in Major Depressive Disorder: results of the BRITE-MD study.

Andrew F Leuchter1, Ian A Cook, Lauren B Marangell, William S Gilmer, Karl S Burgoyne, Robert H Howland, Madhukar H Trivedi, Sidney Zisook, Rakesh Jain, James T McCracken, Maurizio Fava, Dan Iosifescu, Scott Greenwald.   

Abstract

Patients with Major Depressive Disorder (MDD) may not respond to antidepressants for 8 weeks or longer. A biomarker that predicted treatment effectiveness after only 1 week could be clinically useful. We examined a frontal quantitative electroencephalographic (QEEG) biomarker, the Antidepressant Treatment Response (ATR) index, as a predictor of response to escitalopram, and compared ATR with other putative predictors. Three hundred seventy-five subjects meeting DSM-IV criteria for MDD had a baseline QEEG study. After 1 week of treatment with escitalopram, 10 mg, a second QEEG was performed, and the ATR was calculated. Subjects then were randomly assigned to continue with escitalopram, 10 mg, or change to alternative treatments. Seventy-three evaluable subjects received escitalopram for a total of 49days. Response and remission rates were 52.1% and 38.4%, respectively. The ATR predicted both response and remission with 74% accuracy. Neither serum drug levels nor 5HTTLPR and 5HT2a genetic polymorphisms were significant predictors. Responders had larger decreases in Hamilton Depression Rating Scale (Ham-D(17)) scores at day 7 (P=0.005), but remitters did not. Clinician prediction based upon global impression of improvement at day 7 did not predict outcome. Logistic regression showed that the ATR and early Ham-D(17) changes were additive predictors of response, but the ATR was the only significant predictor of remission. Future studies should replicate these results prior to clinical use.

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Year:  2009        PMID: 19712979     DOI: 10.1016/j.psychres.2009.06.004

Source DB:  PubMed          Journal:  Psychiatry Res        ISSN: 0165-1781            Impact factor:   3.222


  49 in total

Review 1.  Moving pharmacoepigenetics tools for depression toward clinical use.

Authors:  Laura M Hack; Gabriel R Fries; Harris A Eyre; Chad A Bousman; Ajeet B Singh; Joao Quevedo; Vineeth P John; Bernhard T Baune; Boadie W Dunlop
Journal:  J Affect Disord       Date:  2019-02-06       Impact factor: 4.839

2.  An Electrophysiological Biomarker That May Predict Treatment Response to ECT.

Authors:  Katherine W Scangos; Richard D Weiner; Edward C Coffey; Andrew D Krystal
Journal:  J ECT       Date:  2019-06       Impact factor: 3.635

3.  Prospective testing of a neurophysiologic biomarker for treatment decisions in major depressive disorder: The PRISE-MD trial.

Authors:  Ian A Cook; Aimee M Hunter; Marissa M Caudill; Michelle J Abrams; Andrew F Leuchter
Journal:  J Psychiatr Res       Date:  2020-02-26       Impact factor: 4.791

4.  Physiologic artifacts in resting state oscillations in young children: methodological considerations for noisy data.

Authors:  Kevin McEvoy; Kyle Hasenstab; Damla Senturk; Andrew Sanders; Shafali S Jeste
Journal:  Brain Imaging Behav       Date:  2015-03       Impact factor: 3.978

5.  The antidepressant treatment response index and treatment outcomes in a placebo-controlled trial of fluoxetine.

Authors:  Aimee M Hunter; Ian A Cook; Scott D Greenwald; Melody L Tran; Kate N Miyamoto; Andrew F Leuchter
Journal:  J Clin Neurophysiol       Date:  2011-10       Impact factor: 2.177

6.  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.

Authors:  Martin Bares; Tomas Novak; Miloslav Kopecek; Martin Brunovsky; Pavla Stopkova; Cyril Höschl
Journal:  Eur Arch Psychiatry Clin Neurosci       Date:  2014-05-22       Impact factor: 5.270

Review 7.  Combining Antidepressants in Acute Treatment of Depression: A Meta-Analysis of 38 Studies Including 4511 Patients.

Authors:  Jonathan Henssler; Tom Bschor; Christopher Baethge
Journal:  Can J Psychiatry       Date:  2016-01-01       Impact factor: 4.356

8.  Predicting response to psychiatric surgery: a systematic review of neuroimaging findings.

Authors:  Benjamin Davidson; Hrishikesh Suresh; Maged Goubran; Jennifer S Rabin; Ying Meng; Karim Mithani; Christopher B Pople; Peter Giacobbe; Clement Hamani; Nir Lipsman
Journal:  J Psychiatry Neurosci       Date:  2020-11-01       Impact factor: 6.186

9.  Pretreatment brain states identify likely nonresponse to standard treatments for depression.

Authors:  Callie L McGrath; Mary E Kelley; Boadie W Dunlop; Paul E Holtzheimer; W Edward Craighead; Helen S Mayberg
Journal:  Biol Psychiatry       Date:  2013-12-19       Impact factor: 13.382

Review 10.  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

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