Evidence map›Paper›PMID 38628260›Full record

ArticleFrontiers in psychiatry2024

One size does not fit all: notable individual variation in brain activity correlates of antidepressant treatment response.

Gwen van der Wijk, Yaruuna Enkhbold, Kelsey Cnudde, Matt W Szostakiwskyj, Pierre Blier, Verner Knott, Natalia Jaworska, Andrea B Protzner

Registry-linked trialOpen access · goldAbstract read
In one paragraph

Article in Frontiers in psychiatry, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT00519428 (Combining Antidepressants to Hasten Remission From Depression), which is not on this map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
1.0field-weighted citation impact, top 27% of its field
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.

NCT00519428 phase4completednot on this map

Combining Antidepressants to Hasten Remission From Depression

TypeinterventionalSponsorNew York State Psychiatric InstituteRan2007 to 2012Enrolled245ConditionsMajor Depressive DisorderArmsescitalopram, bupropion extra long (XL), escitalopram + bupropion
3 · Its place in the literature

Who cites it

2 citing papers in PubMed, 3 citations in OpenAlex.

  1. Trial
  2. Article
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

8 authors at 2 institutions in 1 country.

Gwen van der WijkDepartment of Psychology, University of Calgary, Calgary, AB, Canada.
Yaruuna EnkhboldDepartment of Psychology, University of Calgary, Calgary, AB, Canada.
Kelsey CnuddeDepartment of Psychology, University of Calgary, Calgary, AB, Canada.
Matt W SzostakiwskyjDepartment of Psychology, University of Calgary, Calgary, AB, Canada.
Pierre BlierInstitute of Mental Health Research, Affiliated with the University of Ottawa, Ottawa, ON, Canada.
Verner KnottInstitute of Mental Health Research, Affiliated with the University of Ottawa, Ottawa, ON, Canada.
Natalia JaworskaInstitute of Mental Health Research, Affiliated with the University of Ottawa, Ottawa, ON, Canada.
Andrea B ProtznerDepartment of Psychology, University of Calgary, Calgary, AB, Canada.
University of Calgary · CAUniversity of Ottawa · CA

Funding

Combining Antidepressants to Hasten Remission from DepressionR01MH077285 · NIMH · UNIV OF OTTAWA INSTITUTE/MENTAL HLTH RES · PI BLIER, PIERRE · 2007 to 2010
$800k
NIMH NIH HHS R01 MH077285
6 · The paper itself

Abstract

Introduction: To date, no robust electroencephalography (EEG) markers of antidepressant treatment response have been identified. Variable findings may arise from the use of group analyses, which neglect individual variation. Using a combination of group and single-participant analyses, we explored individual variability in EEG characteristics of treatment response. Methods: Resting-state EEG data and Montgomery-Åsberg Depression Rating Scale (MADRS) symptom scores were collected from 43 patients with depression before, at 1 and 12 weeks of pharmacotherapy. Partial least squares (PLS) was used to: 1) identify group differences in EEG connectivity (weighted phase lag index) and complexity (multiscale entropy) between eventual medication responders and non-responders, and 2) determine whether group patterns could be identified in individual patients. Results: Responders showed decreased alpha and increased beta connectivity, and early, widespread decreases in complexity over treatment. Non-responders showed an opposite connectivity pattern, and later, spatially confined decreases in complexity. Thus, as in previous studies, our group analyses identified significant differences between groups of patients with different treatment outcomes. These group-level EEG characteristics were only identified in ~40-60% of individual patients, as assessed quantitatively by correlating the spatiotemporal brain patterns between groups and individual results, and by independent raters through visualization. Discussion: Our single-participant analyses suggest that substantial individual variation exists, and needs to be considered when investigating characteristics of antidepressant treatment response for potential clinical applicability. Clinical trial registration: https://clinicaltrials.gov, identifier NCT00519428.

Indexed as

EEG complexityEEG connectivityindividual variabilitymajor depressiontreatment response

Identifiers

PMID38628260
PMCPMC11018891
OpenAlexW4393479335

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

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.