EEG Biomarkers for Predicting Response to Antidepressant Therapy

The safety and scientific validity of this study is the responsibility of the study sponsor and investigators. Listing a study does not mean it has been evaluated by the U.S. Federal Government. Read our disclaimer for details. Identifier: NCT00289523
Recruitment Status : Completed
First Posted : February 10, 2006
Last Update Posted : March 7, 2012
Information provided by (Responsible Party):
Medtronic - MITG

February 8, 2006
February 10, 2006
March 7, 2012
January 2006
July 2007   (Final data collection date for primary outcome measure)
1. To confirm prospectively the accuracy of an EEG biomarker as a leading indicator of SSRI antidepressant treatment response; [ Time Frame: 8 weeks ]
2. To identify the optimal positive and negative indicators of response to initial treatment with an SSRI; 3. To determine the preferred clinical intervention to perform following an initial negative treatment response indicator;
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Complete list of historical versions of study NCT00289523 on Archive Site
1. To confirm prospectively the accuracy of an EEG biomarker as a leading indicator of remission; [ Time Frame: 8 weeks ]
2. To explore the relationship between EEG and genetic biomarkers as predictors of treatment response and remission; 3. To determine if certain baseline EEG values or changes early in the course of treatment may predict the emergence of worsening suicidal ideation.
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EEG Biomarkers for Predicting Response to Antidepressant Therapy
Biomarkers for Rapid Identification of Treatment Effectiveness in Major Depression (BRITE-MD), a Prospective, Randomized, Multi-center Study to Determine the Efficacy of Selected EEG and Genotype Biomarkers for Predicting Response to Antidepressant Therapy With Escitalopram, Bupropion XL, or a Combination Treatment Regimen.

The purpose of this study is to evaluate the potential early EEG predictors of an individual's response to treatment with antidepressant medications.


  • Prospectively confirm accuracy of current EEG biomarker algorithm
  • Determine preferred clinical intervention for subjects with negative indicator
  • Identify predictors of worsening suicide ideation

According to recent clinical studies sponsored by the NIH, fewer than half of subjects diagnosed with a major depressive episode respond to the first trial of an antidepressant medication. While the majority of subjects eventually respond to treatment with an antidepressant, failure with the first line medication puts subjects at increased risk for never receiving adequate treatment of their depression.

Several lines of reasoning support the rationale for further investigating EEG as a means of predicting response and resistance to antidepressants. Prior studies suggest that changes in neuronal activity in the anterior cingulate and prefrontal regions are related to depression and that changes in brain response to treatment may also produce alterations that can be detected by recoding frontal EEG activity.

In this protocol, we proposed to identify possible neurophysiologic indicators of treatment outcome in depression, particularly indicators of brain response that appear early (within 7 days) during treatment with antidepressants. We will test whether quantitative EEG (QEEG) biomarkers can be reliably associated with response or non-response to treatment with antidepressant medications, using both monotherapy and combination drug treatments.


Selecting the best treatment for subjects with resistance to an initial antidepressant poses a considerable challenge for clinicians. The most widely prescribed antidepressants usually require 4-6 weeks of therapeutic dosing before a marked clinical improvement in symptoms is observed. Therefore, determining the optimal regimen can take several weeks or months for subjects who are resistant to the first line antidepressant. A tool for predicting eventual clinical response to antidepressants could help inform and accelerate the process of identifying the most efficacious treatment option for a given subject.

Observational Model: Case Control
Time Perspective: Prospective
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Probability Sample
A total of 375 subjects with major depressive disorder (MDD) between the ages of 18 - 75 with no other primary neuropsychiatric illnesses were recruited from the population presenting for ongoing treatment in a primary care clinic, or for depression in a psychiatric clinic at each site.
Major Depressive Disorder
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  • Escitalopram
  • Bupropion XL
  • Combination Therapy
    Escitalopram and Bupropion XL

*   Includes publications given by the data provider as well as publications identified by Identifier (NCT Number) in Medline.
Same as current
July 2007
July 2007   (Final data collection date for primary outcome measure)

Inclusion Criteria:

  • Subject has diagnosis of Major Depressive Disorder

Exclusion Criteria:

  • Subject is suffering from cognitive, bipolar, or psychotic disorder
  • Subject has had a course of ECT within the past six months
  • Subject has any known contraindication for use of any of the study drugs
  • Subject has a known drug dependency or substance abuse within the past six mon ths
  • Subject is currently pregnant or not using a medically acceptable means of birth control
Sexes Eligible for Study: All
21 Years to 75 Years   (Adult, Older Adult)
Contact information is only displayed when the study is recruiting subjects
United States
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Medtronic - MITG
Medtronic - MITG
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Principal Investigator: Andrew F Leuchter, M.D. University of California, Los Angeles-Westwood
Medtronic - MITG
April 2010