Evidence map›Paper›PMID 36370124›Full record

Trial reportSchizophrenia bulletin2023

Hippocampal Subfield Volumes Predict Disengagement from Maintenance Treatment in First Episode Schizophrenia.

Wei Qi, Julia Marx, Michael Zingman, Yi Li, Eva Petkova, Esther Blessing, Babak Ardekani, Ayse Sakalli Kani, Corinne Cather, Oliver Freudenreich and 4 more

Abstract readRandomized Controlled Trial
In one paragraph

Trial report in Schizophrenia bulletin, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
–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

9 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Review
  5. Article
  6. Article
  7. Article
  8. Article
  9. Candidate biomarkers in psychiatric disorders: state of the field.World psychiatry : official journal of the World Psychiatric Association (WPA) · 2023
    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

14 authors.

Wei QiDepartment of Psychiatry, NYU Langone Health, 1 Park Avenue, New York, NY, USA.
Julia MarxDepartment of Psychiatry, NYU Langone Health, 1 Park Avenue, New York, NY, USA.
Michael ZingmanDepartment of Psychiatry, NYU Langone Health, 1 Park Avenue, New York, NY, USA.
Yi LiDepartment of Population Health, Division of Biostatistics, NYU School of Medicine, 180 Madison Avenue, New York, NY, USA.
Eva PetkovaDepartment of Population Health, Division of Biostatistics, NYU School of Medicine, 180 Madison Avenue, New York, NY, USA.
Esther BlessingDepartment of Psychiatry, NYU Langone Health, 1 Park Avenue, New York, NY, USA.
Babak ArdekaniDepartment of Psychiatry, NYU Langone Health, 1 Park Avenue, New York, NY, USA.
Ayse Sakalli KaniDepartment of Psychiatry, NYU Langone Health, 1 Park Avenue, New York, NY, USA.
Corinne CatherDepartment of Psychiatry, Massachusetts General Hospital, Harvard Medical School, 55 Fruit Street, Boston, MA, USA.
Oliver FreudenreichDepartment of Psychiatry, Massachusetts General Hospital, Harvard Medical School, 55 Fruit Street, Boston, MA, USA.
Daphne HoltDepartment of Psychiatry, Massachusetts General Hospital, Harvard Medical School, 55 Fruit Street, Boston, MA, USA.ORCID 0000-0002-6428-9603
Jingping ZhaoNational Clinical Research Center for Mental Disorders, Mental Health Institute, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China.
Jijun WangShanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai, China.
Donald C GoffDepartment of Psychiatry, NYU Langone Health, 1 Park Avenue, New York, NY, USA.

Funding

Citalopram in First Episode SchizophreniaR01MH084900 · NIMH · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI GOFF, DONALD C. · 2009 to 2013
$2.9M
NIMH NIH HHS R01 MH084900
6 · The paper itself

Abstract

objectivesDisengagement from treatment is common in first episode schizophrenia (FES) and is associated with poor outcomes. Our aim was to determine whether hippocampal subfield volumes predict disengagement during maintenance treatment of FES.

methodsFES patients were recruited from sites in Boston, New York, Shanghai, and Changsha. After stabilization on antipsychotic medication, participants were randomized to add-on citalopram or placebo and followed for 12 months. Demographic, clinical and cognitive factors at baseline were compared between completers and disengagers in addition to volumes of hippocampal subfields.

resultsBaseline data were available for 95 randomized participants. Disengagers (n = 38, 40%) differed from completers (n = 57, 60%) by race (more likely Black; less likely Asian) and in more alcohol use, parkinsonism, negative symptoms and more impairment in visual learning and working memory. Bilateral dentate gyrus (DG), CA1, CA2/3 and whole hippocampal volumes were significantly smaller in disengagers compared to completers. When all the eight volumes were entered into the model simultaneously, only left DG volume significantly predicted disengagement status and remained significant after adjusting for age, sex, race, intracranial volume, antipsychotic dose, duration of untreated psychosis, citalopram status, alcohol status, and smoking status (P < .01). Left DG volume predicted disengagement with 57% sensitivity and 83% specificity.

conclusionsSmaller left DG was significantly associated with disengagement status over 12 months of maintenance treatment in patients with FES participating in a randomized clinical trial. If replicated, these findings may provide a biomarker to identify patients at risk for disengagement and a potential target for interventions.

Indexed as

Psychotic DisordersSchizophreniaChinaCitalopramHippocampusHumansMagnetic Resonance ImagingCitaloprambiomarkerbrain volumedentate gyruspredictionretention

Identifiers

PMID36370124
PMCPMC9810017

What OpenQuestion holds

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LicenceCC BY-NC
Read underepoch 390

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.