Evidence map›Paper›PMID 32169689›Full record

ArticleJournal of psychiatric research2020

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

Ian A Cook, Aimee M Hunter, Marissa M Caudill, Michelle J Abrams, Andrew F Leuchter

Abstract read
In one paragraph

Article in Journal of psychiatric research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Towards causal inference-based antidepressant selection with brain and blood biomarkers.Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology · 2026
    Trial
  3. Article
  4. Article
  5. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Ian A CookDepartment of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, David Geffen School of Medicine at UCLA, 760 Westwood Plaza, Los Angeles, CA, USA; Department of Bioengineering, Henry Samueli School of Engineering and Applied Science at UCLA, 410 Westwood Plaza, Los Angeles, CA, USA.
Aimee M HunterDepartment of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, David Geffen School of Medicine at UCLA, 760 Westwood Plaza, Los Angeles, CA, USA.
Marissa M CaudillDepartment of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, David Geffen School of Medicine at UCLA, 760 Westwood Plaza, Los Angeles, CA, USA.
Michelle J AbramsDepartment of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, David Geffen School of Medicine at UCLA, 760 Westwood Plaza, Los Angeles, CA, USA.
Andrew F LeuchterDepartment of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, David Geffen School of Medicine at UCLA, 760 Westwood Plaza, Los Angeles, CA, USA. Electronic address: afl@ucla.edu.

Funding

Personalized Response Indicators of SSRI Effectiveness in Major DepressionR01MH085925 · NIMH · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI COOK, IAN A · 2009 to 2011
$1.5M
NIMH NIH HHS R01 MH085925
6 · The paper itself

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.

Indexed as

Major Depressive DisorderAdultBiomarkersCitalopramHumansProspective StudiesTreatment OutcomeBiomarkersCitalopramAntidepressantsDrug response biomarkersEEGMajor depressive disorder

Identifiers

PMID32169689
PMCPMC7141143

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.