Quantitative EEG (QEEG) as a Predictor of Treatment Outcome in Depression

NCT ID: NCT00157547

Last Updated: 2008-05-28

Basic Information

• Recruitment Status: COMPLETED
• Clinical Phase: PHASE4
• Total Enrollment: 95 participants
• Study Classification: INTERVENTIONAL
• Study Start Date: 2003-04-30
• Study Completion Date: 2006-08-31

Brief 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.

Conditions

Major Depressive Disorder

Keywords

Depression; Quantitative EEG (QEEG); Antidepressants

Study Design

• Allocation Method: NON_RANDOMIZED
• Intervention Model: PARALLEL
• Primary Study Purpose: TREATMENT
• Blinding Strategy: NONE

Interventions

Selective serotonin reuptake inhibitors (SSRI)

Selective serotonin reuptake inhibitors (SSRI)

Intervention Type: DRUG

Other Intervention Names

fluoxetine; sertraline; paroxetine; fluvoxamine; citalopram; escitalopram; venlafaxine

Eligibility Criteria

Inclusion Criteria

1. DSM-IV diagnostic criteria for MDD

2. Written informed consent

3. Men or women aged 18-65

4. A baseline Hamilton-D17 score of > 16 at screen visit

Exclusion Criteria

1. Subjects with suicidal ideation where outpatient treatment is determined unsafe by the study clinician. These patients will be immediately referred to appropriate clinical treatment.

2. Pregnant women or women of childbearing potential who are not using a medically accepted means of contraception (defined as oral contraceptive pill or implant, condom, diaphragm, spermicide, IUD, s/p tubal ligation, partner with vasectomy)

3. Known history of serious or unstable medical illness, including cardiovascular, hepatic, renal, respiratory, endocrine, neurologic or hematological disease

4. History of seizure disorder, brain injury, any history of known neurological disease (multiple sclerosis, degenerative disease such as ALS, Parkinson disease and any movement disorders, etc)

5. History or current diagnosis of the following DSM-IV psychiatric illness: organic mental disorder, schizophrenia, schizoaffective disorder, delusional disorder, psychotic disorders not otherwise specified, bipolar disorder, patients with mood congruent or mood incongruent psychotic features, patients with substance dependence disorders, including alcohol, active within the last 12 months.

6. History of multiple adverse drug reactions

7. Current use of other psychotropic drugs, including current use of benzodiazepines, hypnotics, anticonvulsants. Concomitant use of antihistamine drugs will be allowed.

8. Patients who have failed to respond during the course of their current major depressive episode to at least two adequate antidepressant trials, or have failed more than one adequate trial with an SSRI antidepressant.

9. Electroconvulsive therapy (ECT) within the past 6 months

• Minimum Eligible Age: 18 Years
• Maximum Eligible Age: 65 Years
• Eligible Sex: ALL
• Accepts Healthy Volunteers: No

Sponsors

Medtronic - MITG

INDUSTRY

Sponsor Role: collaborator

Massachusetts General Hospital

OTHER

Sponsor Role: lead

Responsible Party

Massachusetts General Hospital, Boston, MA 02114

Principal Investigators

Dan Iosifescu, MD

Role: PRINCIPAL_INVESTIGATOR

Massachusetts General Hospital

References

Iosifescu DV, Greenwald S, Devlin P, Mischoulon D, Denninger JW, Alpert JE, Fava M. Frontal EEG predictors of treatment outcome in major depressive disorder. Eur Neuropsychopharmacol. 2009 Nov;19(11):772-7. doi: 10.1016/j.euroneuro.2009.06.001. Epub 2009 Jul 1.

Reference Type: DERIVED

PMID: 19574030 (View on PubMed)

Other Identifiers

2002-P-001784

Identifier Type: -

Identifier Source: org_study_id