Quantitative EEG (QEEG) as a Predictor of Treatment Outcome in Depression
Condition: Major Depressive Disorder
MeSH terms: Depressive Disorder; Depression; Depressive Disorder, Major
Study type: Interventional
Phase: Phase 4

Summary: 
      The purpose of the study is to try to see if antidepressant medications cause changes in QEEG
      measurements in the brain. QEEG is a mathematical analysis of electrical currents in the
      brain using electrodes placed on the scalp. Previous studies have shown that mood improvement
      (clinical response) caused by antidepressant medications was preceded by changes in QEEG
      measurements in the brain.
    

Detailed description: 
      Despite the availability of effective clinical treatments for major depressive disorder
      (MDD), 30-40% of subjects with MDD still fail to respond significantly to antidepressant
      treatment (Fava and Davidson, 1996). In the absence of biological predictors of treatment
      outcome in MDD, clinicians face a difficult dilemma in selecting an antidepressant treatment.

      Currently we have only preliminary knowledge on the mechanisms and the biological correlates
      of treatment response in MDD (Mayberg et al, 1997 and 1999). Functional neuroimaging studies
      have demonstrated decreased metabolism and glucose consumption in specific limbic and
      paralimbic brain areas which are related to affective regulation. Quantitative EEG (QEEG)
      studies in subjects with MDD have revealed other functional brain abnormalities, such as
      decreased power in the EEG theta wave band. Studies with auditory evoked potentials have
      shown P300 latency in subjects with MDD. Moreover, some quantitative EEG parameters (e.g.,
      cordance), appear to predict clinical response to antidepressants.

      The principal aim of this study is to identify, by measuring QEEG, predictors and correlates
      of treatment response in a group of patients with MDD. We will also carry out exploratory
      analyses to identify correlations between QEEG metrics and multiple clinical parameters of
      depressed subjects: gender, age, chronicity of depression, age of onset, comorbid anxiety,
      atypical and melancholic depressive subtypes.

      Our understanding of the relationship between treatment outcome in MDD and EEG measurements
      promises to provide clinically useful information for selecting antidepressant treatments; it
      can also provide important information useful in the early testing of new compounds with
      putative antidepressant efficacy. Furthermore, the knowledge gained and techniques used may
      help shed light on the pathophysiology of major depression and perhaps other neuropsychiatric
      disorders associated with depressed mood.
    

Intervention name(s): Selective serotonin reuptake inhibitors (SSRI)
Intervention type(s): Drug
Intervention description(s): Selective serotonin reuptake inhibitors (SSRI)
Other intervention name(s): fluoxetine; sertraline; paroxetine; fluvoxamine; citalopram; escitalopram; venlafaxine
Intervention MeSH terms: Fluvoxamine; Citalopram; Fluoxetine; Paroxetine; Venlafaxine Hydrochloride; Sertraline; Escitalopram; Selective Serotonin Reuptake Inhibitors; Serotonin
Allocation: Non-Randomized
Intervention model: Parallel Assignment
Masking: None (Open Label)
Primary purpose: Treatment
Keywords: Depression; Quantitative EEG (QEEG); Antidepressants