Evidence map›Paper›PMID 38077276›Full record

ArticlePsychiatric research and clinical practice2023

Factors Affecting Antidepressant Response Trajectories: A Veterans Affairs Augmentation and Switching Treatments for Improving Depression Outcomes Trial Report.

Paul B Hicks, Varadan Sevilimedu, Gary R Johnson, Ilanit R Tal, Peijun Chen, Lori L Davis, Julia E Vertrees, Sidney Zisook, Somaia Mohamed

Open access · goldAbstract read
In one paragraph

Article in Psychiatric research and clinical practice, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.7field-weighted citation impact, top 28% 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.

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

3 citing papers in PubMed, 3 citations in OpenAlex.

  1. Article
  2. Review
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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

9 authors at 2 institutions in 1 country.

Paul B HicksDepartment of Psychiatry Baylor Scott & White Health Temple Texas.ORCID https://orcid.org/0000-0002-3921-9056
Varadan SevilimeduBiostatistics Service Department of Epidemiology and Biostatistics Memorial Sloan Kettering Cancer Center New York New York.
Gary R JohnsonCooperative Studies Program Coordinating Center VA Connecticut Healthcare System West Haven Connecticut.
Ilanit R TalVA San Diego Healthcare System San Diego California.
Peijun ChenDepartment of Psychiatry VISN10 Geriatric Research, Education and Clinical Center VA Northeast Ohio Healthcare System Cleveland Ohio.
Lori L DavisTuscaloosa VA Medical Center Tuscaloosa Alabama.
Julia E VertreesCooperative Studies Program Clinical Research Pharmacy Coordinating Center Albuquerque New Mexico.
Sidney ZisookVA San Diego Healthcare System San Diego California.
Somaia MohamedVeterans Affairs (VA) New England Mental Illness Research, Education and Clinical Center VA Connecticut Healthcare System West Haven Connecticut.
Texas A&M University System · USMemorial Sloan Kettering Cancer Center · US

Funding

X-RAY CRYSTALLOGRAPHYP30CA008748 · NCI · SLOAN-KETTERING INSTITUTE FOR CANCER RES · PI Nicholas D Socci · 1985 to 2026
$347.4M
NCI NIH HHS P30 CA008748
6 · The paper itself

Abstract

Background: In this secondary analysis of the VA Augmentation and Switching Treatments for Improving Depression Outcomes (VAST-D) study we used antidepressant response trajectories to assess the association of treatment and multiple clinical/demographic factors with the probability of response. Methods: Using data from VAST-D, a multi-site, randomized, single-blind trial with parallel-assignment to one of three treatment interventions in 1522 Veterans whose major depressive disorder was unresponsive to at least one antidepressant trial, we evaluated response patterns using group-based trajectory modeling (GBTM). A weighted multinomial logistic regression analysis with backward elimination and additional exploratory analyses were performed to evaluate the association of multiple clinical/demographic factors with the probability of inclusion into specific trajectories. Additional exploratory analyses were used to identify factors associated with trajectory group membership that could have been missed in the primary analysis. Results: GBTM showed the best fit for depression symptom change was comprised of six trajectories, with some trajectories demonstrating minimal improvement and others showing a high probability of remission. High baseline depression and anxiety severity scores decreased, and early improvement increased, the likelihood of inclusion into the most responsive trajectory in both the GBTM and exploratory analyses. Conclusion: While multiple factors influence responsiveness, the probability of inclusion into a specific depression symptom trajectory is most strongly influenced by three factors: baseline depression, baseline anxiety, and the presence of early improvement.

Identifiers

PMID38077276
PMCPMC10698706
OpenAlexW4385244450

What OpenQuestion holds

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LicenceCC BY-NC
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Registered trials

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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.