The use of referenced-EEG (rEEG) in assisting medication selection for the treatment of depression

Charles DeBattista, Gustavo Kinrys, Daniel Hoffman, Corey Goldstein, John Zajecka, James Kocsis, Martin Teicher, Steven Potkin, Adrian Preda, Gurmeet Multani, Len Brandt, Mark Schiller, Dan Iosifescu, Maurizio Fava

Research output: Contribution to journalArticlepeer-review

41 Scopus citations

Abstract

Objective: To evaluate the efficacy of rEEG®-guided pharmacotherapy for the treatment of depression in those circumstances where rEEG and STAR*D provided different recommendations. Materials and methods: This was a randomized, single-blind, parallel group, 12 center, US study of rEEG-guided pharmacotherapy vs. the most effective treatment regimens reported in the NIH sponsored STAR*D study. Relatively treatment-resistant subjects ≥18 years who failed one or more antidepressants were required to have a QIDS-16-SR score ≥13 and a MADRS score ≥26 at baseline. All subjects underwent a washout of all current medications (with some protocol-specified exceptions) for at least five half-lives before receiving a QEEG and rEEG report. Subjects randomized to rEEG were assigned a regimen based on the rEEG report. Control subjects who had failed only SSRI's in their current episode were randomized to receive venlafaxine XR. Control subjects who had failed antidepressants from ≥2 classes of antidepressants were randomized to receive a regimen from Steps 2-4 of the STAR*D study. Treatment lasted 12 weeks. The primary outcome measures were change from baseline for self-rated QIDS-SR16 and Q-LES-Q-SF. Results: A total of 114 subjects were randomized and 89 subjects were evaluable. rEEG-guided pharmacotherapy exhibited significantly greater improvement for both primary endpoints, QIDS-SR16 (-6.8 vs. -4.5, p<0.0002) and Q-LES-Q-SF (18.0 vs. 8.9, p<0.0002) compared to control, respectively, as well as statistical superiority in 9 out of 12 secondary endpoints. Conclusions: These results warrant additional studies to determine the role of rEEG-guided psychopharmacology in the treatment of depression. If these results were confirmed, rEEG-guided pharmacotherapy would represent an easy, relatively inexpensive, predictive, objective office procedure that builds upon clinical judgment to guide antidepressant medication choice.

Original languageEnglish
Pages (from-to)64-75
Number of pages12
JournalJournal of Psychiatric Research
Volume45
Issue number1
DOIs
StatePublished - Jan 2011
Externally publishedYes

Keywords

  • Antidepressants
  • Biomarkers
  • QEEG
  • REEG
  • Resistant depression
  • Response prediction

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