Frontal EEG predictors of treatment outcome in major depressive disorder

Dan V. Iosifescu, Scott Greenwald, Philip Devlin, David Mischoulon, John W. Denninger, Jonathan E. Alpert, Maurizio Fava

Research output: Contribution to journalArticlepeer-review

128 Scopus citations


Objective: To investigate the role of frontal EEG as predictor of clinical response to SSRIs or venlafaxine in major depressive disorder (MDD). Method: 82 subjects (age 35.9 ± 13.0; 47.6% female) meeting DSM-IV criteria for MDD entered an 8-week prospective treatment with SSRIs or venlafaxine. At baseline and week 1 we recorded serial, 4-channel EEGs (F7-Fpz, F8-Fpz, A1-Fpz, A2-Fpz). We evaluated prospectively the relative theta power as predictor of treatment outcome. We also developed an Antidepressant Treatment Response (ATR) index using EEG parameters assessed at baseline and week 1. Results: 45 subjects (54.9%) responded to treatment (HAM-D-17 reduction ≥ 50%). At baseline, frontal relative theta power (i.e., 4-8 Hz power/2-20 Hz power) was significantly (p = 0.017) lower (21%) in treatment responders than in non-responders (24%). Baseline relative theta power predicted treatment response with 63% accuracy [64% sensitivity, 62% specificity, 66% area under the receiver operator curve (AUROC) (p = 0.014)]. Relative theta power at week 1 predicted treatment response with 60% accuracy [62% sensitivity, 57% specificity, 61% AUROC (p = 0.089)]. ATR predicted response with 70% accuracy [82% sensitivity, 54% specificity, 72% AUROC (p = 0.001)]. Conclusion: Using automated analysis of frontal EEG collected during the first week of antidepressant treatment it may be possible to facilitate prediction of SSRI or venlafaxine efficacy in MDD.

Original languageEnglish (US)
Pages (from-to)772-777
Number of pages6
JournalEuropean Neuropsychopharmacology
Issue number11
StatePublished - Nov 2009
Externally publishedYes


  • Antidepressants
  • Major depressive disorder
  • Quantitative electroencephalography (QEEG)
  • Treatment response

ASJC Scopus subject areas

  • Pharmacology
  • Neurology
  • Clinical Neurology
  • Psychiatry and Mental health
  • Biological Psychiatry
  • Pharmacology (medical)


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