EEG Biomarkers for Predicting Response to Antidepressant Therapy

NCT ID: NCT00289523

Last Updated: 2012-03-07

Basic Information

• Recruitment Status: COMPLETED
• Total Enrollment: 375 participants
• Study Classification: OBSERVATIONAL
• Study Start Date: 2006-01-31
• Study Completion Date: 2007-07-31

Brief Summary

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

Objectives:

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

Detailed Description

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.

Comparison(s):

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.

Conditions

Major Depressive Disorder

Study Design

• Observational Model Type: CASE_CONTROL
• Study Time Perspective: PROSPECTIVE

Study Groups

Escitalopram

No interventions assigned to this group

Bupropion XL

No interventions assigned to this group

Combination Therapy

Escitalopram and Bupropion XL

No interventions assigned to this group

Eligibility Criteria

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

• Minimum Eligible Age: 21 Years
• Maximum Eligible Age: 75 Years
• Eligible Sex: ALL
• Accepts Healthy Volunteers: No

Sponsors

Medtronic - MITG

INDUSTRY

Sponsor Role: lead

Responsible Party

Responsibility Role: SPONSOR

Principal Investigators

Andrew F Leuchter, M.D.

Role: PRINCIPAL_INVESTIGATOR

University of California, Los Angeles-Westwood

Locations

University of California, Los Angeles-Westwood

Los Angeles, California, United States

Cedars-Sinai Medical Center

Los Angeles, California, United States

University of California, San Diego

San Diego, California, United States

University of California, Los Angeles-Harbor

Torrance, California, United States

Northwestern University

Chicago, Illinois, United States

Massachusetts General Hospital

Boston, Massachusetts, United States

University of Pittsburgh

Pittsburgh, Pennsylvania, United States

University of Texas, Southwestern

Dallas, Texas, United States

Baylor University College of Medicine

Houston, Texas, United States

R/D Clinical Research, Inc.

Lake Jackson, Texas, United States

Countries

United States

References

Leuchter AF, Cook IA, Marangell LB, Gilmer WS, Burgoyne KS, Howland RH, Trivedi MH, Zisook S, Jain R, McCracken JT, Fava M, Iosifescu D, Greenwald S. Comparative effectiveness of biomarkers and clinical indicators for predicting outcomes of SSRI treatment in Major Depressive Disorder: results of the BRITE-MD study. Psychiatry Res. 2009 Sep 30;169(2):124-31. doi: 10.1016/j.psychres.2009.06.004. Epub 2009 Aug 27.

Reference Type: RESULT

PMID: 19712979 (View on PubMed)

Leuchter AF, Cook IA, Gilmer WS, Marangell LB, Burgoyne KS, Howland RH, Trivedi MH, Zisook S, Jain R, Fava M, Iosifescu D, Greenwald S. Effectiveness of a quantitative electroencephalographic biomarker for predicting differential response or remission with escitalopram and bupropion in major depressive disorder. Psychiatry Res. 2009 Sep 30;169(2):132-8. doi: 10.1016/j.psychres.2009.04.004. Epub 2009 Aug 26.

Reference Type: RESULT

PMID: 19709754 (View on PubMed)

Cook IA, Hunter AM, Gilmer WS, Iosifescu DV, Zisook S, Burgoyne KS, Howland RH, Trivedi MH, Jain R, Greenwald S, Leuchter AF. Quantitative electroencephalogram biomarkers for predicting likelihood and speed of achieving sustained remission in major depression: a report from the biomarkers for rapid identification of treatment effectiveness in major depression (BRITE-MD) trial. J Clin Psychiatry. 2013 Jan;74(1):51-6. doi: 10.4088/JCP.10m06813.

Reference Type: DERIVED

PMID: 23419226 (View on PubMed)

Other Identifiers

227

Identifier Type: -

Identifier Source: org_study_id