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Early reduction in prefrontal theta QEEG cordance value predicts response to venlafaxine treatment in patients with resistant depressive disorder

Published online by Cambridge University Press:  16 April 2020

Martin Bares ,
Martin Brunovsky ,
Miloslav Kopecek ,
Tomas Novak ,
Pavla Stopkova ,
Jiri Kozeny ,
Peter Sos ,
Vladimir Krajca  and
Cyril Höschl
Martin Bares*
Affiliation:
Prague Psychiatric Centre, Ustavni 91, 181 03 Prague 8, Bohnice, Czech Republic Department of Psychiatry and Medical Psychology, 3rd Faculty of Medicine, Charles University, Ruska 87, 100 00 Prague 10, Czech Republic
Martin Brunovsky
Affiliation:
Prague Psychiatric Centre, Ustavni 91, 181 03 Prague 8, Bohnice, Czech Republic Department of Psychiatry and Medical Psychology, 3rd Faculty of Medicine, Charles University, Ruska 87, 100 00 Prague 10, Czech Republic
Miloslav Kopecek
Affiliation:
Prague Psychiatric Centre, Ustavni 91, 181 03 Prague 8, Bohnice, Czech Republic Department of Psychiatry and Medical Psychology, 3rd Faculty of Medicine, Charles University, Ruska 87, 100 00 Prague 10, Czech Republic Center of Excellence for Research and Treatment Bipolar Disorder, Department of Psychiatry, University of North Carolina at Chapel Hill, NC, USA
Tomas Novak
Affiliation:
Prague Psychiatric Centre, Ustavni 91, 181 03 Prague 8, Bohnice, Czech Republic Department of Psychiatry and Medical Psychology, 3rd Faculty of Medicine, Charles University, Ruska 87, 100 00 Prague 10, Czech Republic
Pavla Stopkova
Affiliation:
Prague Psychiatric Centre, Ustavni 91, 181 03 Prague 8, Bohnice, Czech Republic Department of Psychiatry and Medical Psychology, 3rd Faculty of Medicine, Charles University, Ruska 87, 100 00 Prague 10, Czech Republic
Jiri Kozeny
Affiliation:
Prague Psychiatric Centre, Ustavni 91, 181 03 Prague 8, Bohnice, Czech Republic Department of Psychiatry and Medical Psychology, 3rd Faculty of Medicine, Charles University, Ruska 87, 100 00 Prague 10, Czech Republic
Peter Sos
Affiliation:
Prague Psychiatric Centre, Ustavni 91, 181 03 Prague 8, Bohnice, Czech Republic Department of Psychiatry and Medical Psychology, 3rd Faculty of Medicine, Charles University, Ruska 87, 100 00 Prague 10, Czech Republic
Vladimir Krajca
Affiliation:
Department of Neurology, Faculty Hospital Na Bulovce, 180 00Prague 8, Czech Republic
Cyril Höschl
Affiliation:
Prague Psychiatric Centre, Ustavni 91, 181 03 Prague 8, Bohnice, Czech Republic Department of Psychiatry and Medical Psychology, 3rd Faculty of Medicine, Charles University, Ruska 87, 100 00 Prague 10, Czech Republic
*
*Corresponding author. Prague Psychiatric Centre, Ustavni 91, 181 03 Prague 8, Bohnice, Czech Republic. Tel.: +420 266 003 330; fax: +420 266 003 337. E-mail address: bares@pcp.lf3.cuni.cz (M. Bares).
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Abstract

Introduction

Previous studies of patients with unipolar depression have shown that early decrease of prefrontal EEG cordance in theta band can predict clinical response to various antidepressants. We have now examined whether decrease of prefrontal quantitative EEG (QEEG) cordance value after 1 week of venlafaxine treatment predicts clinical response to venlafaxine in resistant patients.

Method

We analyzed 25 inpatients who finished 4-week venlafaxine treatment. EEG data were monitored at baseline and after 1 week of treatment. QEEG cordance was computed at three frontal electrodes in theta frequency band. Depressive symptoms and clinical status were assessed using Montgomery–Åsberg Depression Rating Scale (MADRS), Beck Depression Inventory-Short Form (BDI-S) and Clinical Global Impression (CGI).

Results

Eleven of 12 responders (reduction of MADRS ≥50%) and only 5 of 13 non-responders had decreased prefrontal QEEG cordance value after the first week of treatment (p = 0.01). The decrease of prefrontal cordance after week 1 in responders was significant (p = 0.03) and there was no significant change in non-responders. Positive and negative predictive values of cordance reduction for response were 0.7 and 0.9, respectively.

Conclusion

The reduction of prefrontal theta QEEG cordance value after first week of treatment might be helpful in the prediction of response to venlafaxine.

Keywords

VenlafaxineDepressive disorderResistant depressionCordanceQEEGResponse prediction
Type
Original article
Information
European Psychiatry , Volume 23 , Issue 5 , August 2008 , pp. 350 - 355
Copyright
Copyright © Elsevier Masson SAS 2008

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References

American Psychiatric Association Diagnostic and statistical manual of mental disorders 4th ed. 1994 Washington, DC: American Psychiatric Press.Google Scholar
Asada, H.Fukuda, Y.Tsunoda, S.Yamaguchi, M.Tonoike, M.Frontal midline theta rhythms reflect alternative activation of prefrontal cortex and anterior cingulate cortex in humans Neurosci Lett 274 1999 29–32.Google Scholar
Baldomero, E.B.Ubago, J.G.Cercos, C.L.Ruiloba, J.V.Calvo, C.G.Lopez, R.P.Venlafaxine extended release versus conventional antidepressants in the remission of depressive disorders after previous antidepressant failure: ARGOS study Depress Anxiety 22 2005 68–76.Google Scholar
Bares, M.Brunovsky, M.Kopecek, M.Stopkova, P.Novak, T.Kozeny, J. et al Changes in QEEG prefrontal cordance as a predictor of response to antidepressants in patients with treatment resistant depressive disorder: a pilot study J Psychiatr Res 41 2007 319–325.Google Scholar
Beck, A.T.Rial, W.Y.Rickels, K.Short form of depression inventory: cross-validation Psychol Rep 34 1974 1184–1186.Google Scholar
Bruder, G.E.Stewart, J.W.Tenke, C.E.McGrath, P.J.Leite, P.Bhattacharya, N. et al Electroencephalographic and perceptual asymmetry differences between responders and nonresponders to an SSRI antidepressant Biol Psychiatry 49 2001 416–425.Google Scholar
Cohen, J.Statistical power analyses for the behavioral sciences 2nd ed. 1988 Hillsdale, NJ: Lawrence Earlbaum Association.Google Scholar
Cook, I.A.Leuchter, A.F.Morgan, M.Witte, E.Stubbeman, W.F.Abrams, M. et al Early changes in prefrontal activity characterize clinical responders to antidepressants Neuropsychopharmacology 27 2002 120–131.Google Scholar
Cook, I.A.Leuchter, A.F.Morgan, M.L.Stubbeman, W.Siegman, B.Abrams, M.Changes in prefrontal activity characterize clinical response in SSRI nonresponders: a pilot study J Psychiatr Res 39 2005 461–466.Google Scholar
Cook, I.A.Leuchter, A.F.Prefrontal changes and treatment response prediction in depression Semin Clin Neuropsychiatry 6 2001 113–120.Google Scholar
Cook, I.A.O'Hara, R.Uijtdehaage, S.Mandelkern, M.Leuchter, A.F.Assessing the accuracy of topographic EEG mapping for determining local brain function Electroencephalogr Clin Neurophysiol 107 1998 404–414.Google Scholar
Corruble, E.Legrand, J.M.Zvenigorowski, H.Duret, C.Guelfi, J.D.Concordance between self-report and clinician's assessment of depression J Psychiatr Res 33 1999 457–465.Google Scholar
Debonnel, G.Saint-Andre, E.Hebert, C.de Montigny, C.Lavoie, N.Blier, P.Differential physiological effects of a low dose and high doses of venlafaxine in major depression Int J Neuropsychopharmacol 10 2007 51–61.Google Scholar
Drevets, W.C.Functional neuroimaging studies of depression: the anatomy of melancholia Annu Rev Med 49 1998 341–361.Google Scholar
Enns, M.W.Larsen, D.K.Cox, B.J.Discrepancies between self and observer ratings of depression. The relationship to demographic, clinical and personality variables J Affect Disord 60 2000 33–41.Google Scholar
Fava, M.Management of nonresponse and intolerance: switching strategies J Clin Psychiatry 61 Suppl. 2 2000 10–12.Google Scholar
Guy, W.ECDEU assessment manual for psychopharmacology Revised 1976 1976 Rockville, MD: National Institutes of Mental Health.Google Scholar
Hirschfeld, R.M.Montgomery, S.A.Aguglia, E.Amore, M.Delgado, P.L.Gastpar, M. et al Partial response and nonresponse to antidepressant therapy: current approaches and treatment options J Clin Psychiatry 63 2002 826–837.Google Scholar
Hjorth, B.An on-line transformation of EEG scalp potentials into orthogonal source derivations Electroencephalogr Clin Neurophysiol 39 1975 526–530.Google Scholar
Hunter, A.M.Cook, I.A.Leuchter, A.F.The promise of the quantitative electroencephalogram as a predictor of antidepressant treatment outcomes in major depressive disorder Psychiatr Clin North Am 30 2007 105–121.Google Scholar
Knott, V.Mahoney, C.Kennedy, S.Evans, K.Pre-treatment EEG and its relationship to depression severity and paroxetine treatment outcome Pharmacopsychiatry 33 2000 201–205.Google Scholar
Knott, V.J.Telner, J.I.Lapierre, I.D.Browne, M.Horn, E.R.Quantitative EEG in the prediction of antidepressant response to imipramine J Affect Disord 39 1996 175–184.Google Scholar
Kobak, K.A.Greist, J.J.Jefferson, J.W.Katzelnick, D.J.Computer-administered clinical rating scales: a review Psychopharmacology 127 1996 291–301.Google Scholar
Kopecek, M.Bares, M.Brunovský, M.Stopková, P.EEG cordance as a predictor to antidepressants response Psychiatrie 11 2007 78–81 [in Czech].Google Scholar
Leuchter, A.F.Cook, I.A.Lufkin, R.B.Dunkin, J.Newton, T.F.Cummings, J.L. et al Cordance: a new method for assessment of cerebral perfusion and metabolism using quantitative electroencephalography Neuroimage 1 1994 208–219.Google Scholar
Leuchter, A.F.Cook, I.A.Witte, E.A.Morgan, M.Abrams, M.Changes in brain function of depressed subjects during treatment with placebo Am J Psychiatry 159 2002 122–129.Google Scholar
Leuchter, A.F.Uijtdehaage, S.H.Cook, I.A.O'Hara, R.Mandelkern, M.Relationship between brain electrical activity and cortical perfusion in normal subjects Psychiatry Res Neuroimaging 90 1999 125–140.Google Scholar
Mayberg, H.S.Brannan, S.K.Tekell, J.L.Silva, J.A.Mahurin, R.K.McGinnis, S. et al Regional metabolic effects of fluoxetine in major depression: serial changes and relationship to clinical response Biol Psychiatry 48 2000 830–843.Google Scholar
Mayberg, H.S.Brannan, S.K.Mahurin, R.K.Jerabek, P.A.Brickan, J.S.Tekell, J.L. et al Cingulate function in depression: a potential predictor of treatment response Neuroreport 8 1997 1057–1061.Google Scholar
Mitchell, A.J.Two-week delay in onset of action of antidepressants: new evidence Br J Psychiatry 188 2006 105–106.Google Scholar
Montgomery, S.A.Åsberg, M.A new depression scale designed to be sensitive to change Br J Psychiatry 134 1979 382–389.Google Scholar
Mulert, C.Juckel, G.Brunmeier, M.Karch, S.Leicht, G.Margi, R. et al Rostral anterior cingulate cortex activity in the theta band predicts response to antidepressant medication Clin EEG Neurosci 38 2007 78–81.Google Scholar
Nierenberg, A.A.Farabaugh, A.H.Alpert, J.E.Gordon, J.Worthington, J.J.Rosenbaum, J.F. et al Timing onset of antidepressant response with fluoxetine treatment Am J Psychiatry 157 2000 1423–1428.Google Scholar
Nuwer, M.R.Lehmann, D.Lopes da Silva, F.Matsuoka, S.Sutherling, W.Vibert, J.F.IFCN guidelines for topographic and frequency analysis of EEGs and EPsDeuschl, G.Eisen, A.Recommendations for the practice of clinical neurophysiology: guidelines of the International Federation of Clinical Neurophysiology 1999 Amsterdam, The Netherlands: Elsevier; 15–20.Google Scholar
Pizzagalli, D.A.Oakes, T.R.Davidson, R.J.Coupling of theta activity and glucose metabolism in the human rostral anterior cingulate cortex: an EEG/PET study of normal and depressed subjects Psychophysiology 40 2003 939–949.Google Scholar
Pizzagalli, D.Pascual-Marqui, R.D.Nitschke, J.B.Oakes, T.R.Larson, C.L.Abercrombie, H.C. et al Anterior cingulate activity as a predictor of degree of treatment response in major depression: evidence from brain electrical tomography analysis Am J Psychiatry 158 2001 405–415.Google Scholar
Poirer, M.F.Boyer, P.Venlafaxine and paroxetine in treatment-resistant depression: double-blind randomized comparison Br J Psychiatry 175 1999 12–16.Google Scholar
Posternak, M.A.Zimmerman, M.Is there a delay in the antidepressant effect? A meta-analysis J Clin Psychiatry 66 2005 148–158.Google Scholar
Pridmore, S.Turnier-Shea, Y.Medication options in the treatment of treatment-resistant depression Aust N Z J Psychiatry 38 2004 219–225.Google Scholar
Rudolph, R.L.Fabre, L.F.Feighner, J.P.Rickels, K.Entsuah, R.Derivan, A.T.A randomized, placebo-controlled, dose–response trial of venlafaxine hydrochloride in the treatment of major depression J Clin Psychiatry 59 1998 116–122.Google Scholar
Rush, A.J.Jizer, W.Gilda, D.E.A comparison of self-reported versus clinician-related symptoms in depression J Clin Psychiatry 48 1987 246–248.Google Scholar
Rush, A.J.Prien, R.F.From scientific knowledge to the clinical practice of psychopharmacology: can the gap be bridged? Psychopharmacol Bull 31 1995 7–20.Google Scholar
Rush, A.J.Trivedi, M.H.Wisniewski, S.R.Stewart, J.W.Nierenberg, A.A.Thase, M.E. et al Bupropion-SR, sertraline, or venlafaxine-XR after failure of SSRIs for depression N Engl J Med 354 2006 1231–1242.Google ScholarPubMed
Rush, A.J.Trivedi, M.H.Wisniewski, S.R.Nierenberg, A.A.Stewart, J.W.Warden, D. et al Acute and long-term outcomes in depressed outpatients requiring one or several treatment steps: a STAR*D report Am J Psychiatry 163 2006 1905–1917.Google Scholar
Sackeim, H.A.Roose, S.P.Burt, T.Optimal length of antidepressant trials in late-life depression J Clin Psychopharmacol 25 Suppl. 1 2005 S34–S37.Google Scholar
Sheehan, D.V.Lecrubier, Y.Sheehan, K.H.Amorim, P.Janavs, J.Weiller, E. et al The Mini-International Neuropsychiatric Interview (M.I.N.I.): the development and validation of a structured diagnostic psychiatric interview for DSM-IV and ICD-10 J Clin Psychiatry 59 Suppl. 20 1998 22–33.Google Scholar
Souery, D.Oswald, P.Massat, I.Bailer, U.Bollen, J.Demyttenaere, K. et al Clinical factors associated with treatment resistance in major depressive disorder: results from a European multicenter study J Clin Psychiatry 68 2007 1062–1070.Google Scholar
Thase, M.E.Entsuah, A.R.Rudolph, R.L.Remission rates during treatment with venlafaxine or selective serotonin reuptake inhibitors Br J Psychiatry 178 2001 234–241.Google ScholarPubMed
Thase, M.E.Rush, A.J.When at first you don't succeed: sequential strategies for antidepressant nonresponders J Clin Psychiatry 58 Suppl. 13 1997 23–29.Google Scholar
Trivedi, M.H.Kurian, B.T.Grannemann, B.D. Clinical predictors in major depressive disorder Psychiatry Weekly May 21, 2007 Available from: http://www.psychiatryweekly.com.Google Scholar
Trivedi, M.H.Morris, D.W.Graemann, B.D.Mahadi, S.Symptom clusters as predictors of late response to antidepressant treatment J Clin Psychiatry 66 2005 1064–1070.Google Scholar
Trivedi, M.H.Rush, A.J.Wisniewski, S.R.Nierenberg, A.A.Warden, D.Ritz, L. et al Evaluation of outcomes with citalopram for depression using measurement-based care in STAR*D: implications for clinical practice Am J Psychiatry 163 2006 28–40.Google Scholar
Ulrich, G.Renfordt, 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 17 1994 178–183.Google Scholar
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