Literature DB >> 32169689

Prospective testing of a neurophysiologic biomarker for treatment decisions in major depressive disorder: The PRISE-MD trial.

Ian A Cook1, Aimee M Hunter2, Marissa M Caudill2, Michelle J Abrams2, Andrew F Leuchter3.   

Abstract

Management of Major Depressive Disorder (MDD) might be improved by a biomarker to predict whether a selected medication is likely to lead to remission. We previously reported on a quantitative electroencephalogram-based biomarker, the Antidepressant Treatment Response (ATR) index, that integrated recordings at baseline and after one week of treatment. The present study prospectively tested whether treatment directed by the biomarker increased the likelihood of remission; we hypothesized that continued treatment with a drug predicted to lead to remission (i.e., high ATR values) would be associated with better outcomes than if the drug was predicted not to lead to remission (i.e., low ATR values). We enrolled 180 adult outpatients with unipolar MDD from the community. After one week of escitalopram treatment to determine the biomarker, stratified randomization (high vs. low ATR) was used to assign subjects to either continued escitalopram or a switch to bupropion as a blinded control condition, for seven additional weeks. For the 73 evaluable subjects assigned to continued escitalopram treatment, the remission rate was significantly higher for those in whom ATR had predicted remission versus non-remission (60.4% vs. 30.0%, respectively, p = 0.01). Accuracy was enhanced by combining 1-week depressive symptom change with ATR (68.6% vs 28.9%). This prospective validation study supports further development of the ATR biomarker, alone or together with early symptom change, to improve care by identifying individuals unlikely to remit with their current treatment, and support the decision to change treatment after one week rather than after failing a full, prolonged course of medication.
Copyright © 2020 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Antidepressants; Drug response biomarkers; EEG; Major depressive disorder

Mesh:

Substances:

Year:  2020        PMID: 32169689      PMCID: PMC7141143          DOI: 10.1016/j.jpsychires.2020.02.028

Source DB:  PubMed          Journal:  J Psychiatr Res        ISSN: 0022-3956            Impact factor:   4.791


  41 in total

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Authors:  Tali Manber Ball; Sarah E Knapp; Martin P Paulus; Murray B Stein
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2.  Do prefrontal midline electrodes provide unique neurophysiologic information in Major Depressive Disorder?

Authors:  Ian A Cook; Aimee M Hunter; Alexander S Korb; Andrew F Leuchter
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3.  SAFTEE: a technique for the systematic assessment of side effects in clinical trials.

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4.  Early change of prefrontal theta cordance and occipital alpha asymmetry in the prediction of responses to antidepressants.

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Journal:  Int J Psychophysiol       Date:  2019-06-10       Impact factor: 2.997

5.  Escitalopram but not placebo modulates brain rhythmic oscillatory activity in the first week of treatment of Major Depressive Disorder.

Authors:  Andrew F Leuchter; Aimee M Hunter; Felipe A Jain; Molly Tartter; Caroline Crump; Ian A Cook
Journal:  J Psychiatr Res       Date:  2016-10-07       Impact factor: 4.791

6.  Treating depression after initial treatment failure: directly comparing switch and augmenting strategies in STAR*D.

Authors:  Bradley N Gaynes; Stacie B Dusetzina; Alan R Ellis; Richard A Hansen; Joel F Farley; William C Miller; Til Stürmer
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Review 7.  Toward biomarkers of the addicted human brain: Using neuroimaging to predict relapse and sustained abstinence in substance use disorder.

Authors:  Scott J Moeller; Martin P Paulus
Journal:  Prog Neuropsychopharmacol Biol Psychiatry       Date:  2017-03-18       Impact factor: 5.067

8.  Examining relations between alpha power as well as anterior cingulate cortex-localized theta activity and response to single or dual antidepressant pharmacotherapies.

Authors:  Natalia Jaworska; Claude Blondeau; Pierre Tessier; Sandhaya Norris; Wendy Fusee; Pierre Blier; Verner Knott
Journal:  J Psychopharmacol       Date:  2014-02-20       Impact factor: 4.153

Review 9.  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.

Authors:  D V Sheehan; Y Lecrubier; K H Sheehan; P Amorim; J Janavs; E Weiller; T Hergueta; R Baker; G C Dunbar
Journal:  J Clin Psychiatry       Date:  1998       Impact factor: 4.384

10.  Predictors of therapeutic response to treatments for depression: a review of electrophysiologic and dichotic listening studies.

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Journal:  CNS Spectr       Date:  1999       Impact factor: 3.790

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  2 in total

Review 1.  Predicting treatment response using EEG in major depressive disorder: A machine-learning meta-analysis.

Authors:  Devon Watts; Rafaela Fernandes Pulice; Jim Reilly; Andre R Brunoni; Flávio Kapczinski; Ives Cavalcante Passos
Journal:  Transl Psychiatry       Date:  2022-08-12       Impact factor: 7.989

2.  Special Report on the Impact of the COVID-19 Pandemic on Clinical EEG and Research and Consensus Recommendations for the Safe Use of EEG.

Authors:  Salvatore Campanella; Kemal Arikan; Claudio Babiloni; Michela Balconi; Maurizio Bertollo; Viviana Betti; Luigi Bianchi; Martin Brunovsky; Carla Buttinelli; Silvia Comani; Giorgio Di Lorenzo; Daniel Dumalin; Carles Escera; Andreas Fallgatter; Derek Fisher; Giulia Maria Giordano; Bahar Guntekin; Claudio Imperatori; Ryouhei Ishii; Hendrik Kajosch; Michael Kiang; Eduardo López-Caneda; Pascal Missonnier; Armida Mucci; Sebastian Olbrich; Georges Otte; Andrea Perrottelli; Alessandra Pizzuti; Diego Pinal; Dean Salisbury; Yingying Tang; Paolo Tisei; Jijun Wang; Istvan Winkler; Jiajin Yuan; Oliver Pogarell
Journal:  Clin EEG Neurosci       Date:  2020-09-25       Impact factor: 1.843

  2 in total

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