Frontal eeg as predictor of treatment outcome in major depressive disorder

Partial and inadequate response to antidepressant treatment have been common in major depressive disorder (MDD). Only 30-40% of the patients who receive adequate pharmacotheray will achieve full remission of symptoms (1).

Non response or partial response to antidepressants is associated with disability, higher relapse and recurrence rates, higher medical costs, and reduce on quality of life (2).

In the absense of biological predictors of treatment autocme in MDD, clinician face a difficult challenge in selecting an antidepressant treatment (3).

Some studies utilizing resting (eyes-closed) EEGs have show elevated theta and alpha activity in depressed patients as compared to healthy controls (4). Ulrich et al, have observed that the responders to tricyclic antidepressants treatment were distinghuised between non responders by difference in the alpha activity (5). Similar results have been observed by Bruder et al, in depressed patients who received fluoxetina (6).

Cock et al, in various studies observed in prefrontal activity, changes in theta-band cordance, a QEEG mesure integrating absolute and relative power of the signal,  have been associated with clinical response to SSRIs antidepressant and venlafaxine (7).
 
In a recent study, Iosifescu et al, found a disminution of prefrontal theta activity, during he first week of treatment associated with antidepressant response to SSRIs and venlafaxine (3).

This results suggesting the possibility of predicting SSRI or SNRI before or early during the antidepresant treatment. Low baseline relative prefrontal theta power was significantly associated with lower final depression scores at the end of treatment (3).

Recent EEG findings are corroborated by studies that use techniques with greater spatial resolution (eg, PET, MEG) in localizing brain regions pertinent to clinical response. As such, EEG measurements increasingly are validated by other physiologic measurements that have the ability to assess deeper brain structures.

Continued progress along these lines may lead to the realized promise of QEEG biomarkers as predictors of antidepressant treatment outcome in routine clinical practice. In the larger context, use of QEEG technology to predict antidepressant response in major depression may mean that more patients will achieve response and remission with less of the trial-and-error approach that currently accompanies antidepressant treatment (8).

1. Rush AJ, Kaemer HC, Sackeim Ha, Fava M, trivedi MH, Frank E, et al. Report of the ACNP Task Force on response and remission in major depressive disorder. Neuropsychopharmacology 2006;31(9):1841-1853

2.  Judd LL, Akiskal HS, Maser JD, Zeller PJ, Endicott J, Coryell W, et al. Major depressive disorder: a prospective of residual subthershold depressive symptoms as predictor of rapid relapse. J Affect Disord. 1998;50:97-108

3. Iosifescu D, Greenwald S, Devlin P, Mischoulon D, Denninger JW, et al. Eur J Neuropsychopharmacol 2009 Nov;19(11):772-777

4. Pollock VE, Schneider LS. Quantitative, waking EEG research in depression. Biol Psychiatry 1990;27(7):757-780

5. Ulrich G, Rendfort E, Zeller G, Frick K. Interrelation between changes in the EEG and psychopathology under pharmacotherapy for endogenous depression. A contribution to the predictor question. Pharmacopsychiatry 1984;17(6):178-183

6. Bruder GE, Stewart JW, tenke CE, McGrath PJ, Leite P, Bhattacharya N, et al. Electroencephalographic and perceptual asymmetry differences between responders and non responders to an SSRI antidepressant. Biol Psychiatry 2001;49(5):416-425

7. Cook I, Leuchter A, Morgan M, Witte E, Stubbeman W,  Siegman B,  Abrams M. Changes in prefrontal activity characterize clinical response in SSRI nonresponders: a pilot study. Paychiatry Res. 2005;39(5):461-466

8. Hunter  AM, Cook IA, Leuchter AF. The promise of the quantitative electroencephalogram as a predictor of antidepressant treatment outcomes in major depressive disorder.   Psychiatr Clin North Am. 2007 Mar;30(1):105-24.