Evidence map›Paper›PMID 37503088›Full record

ArticlemedRxiv : the preprint server for health sciences2023

Replication of a neuroimaging biomarker for striatal dysfunction in psychosis.

Jose M Rubio, Todd Lencz, Hengyi Cao, Nina Kraguljac, Elvisha Dhamala, Philipp Homan, Guillermo Horga, Deepak K Sarpal, Miklos Argyelan, Juan Gallego and 4 more

Abstract readPreprint
In one paragraph

Article in medRxiv : the preprint server for health sciences, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

14 authors.

Jose M RubioDonald and Barbara Zucker School of Medicine at Hofstra University - Northwell Health, New York, USA.
Todd LenczDonald and Barbara Zucker School of Medicine at Hofstra University - Northwell Health, New York, USA.
Hengyi CaoDonald and Barbara Zucker School of Medicine at Hofstra University - Northwell Health, New York, USA.
Nina KraguljacDepartment of Psychiatry and Behavioral Health, The Ohio State University, Columbus, Ohio.
Elvisha DhamalaDonald and Barbara Zucker School of Medicine at Hofstra University - Northwell Health, New York, USA.
Philipp HomanDepartment of Psychiatry, Psychotherapy, and Psychosomatics, Psychiatric University Hospital Zurich, University of Zurich, 8032, Zurich, Switzerland.
Guillermo HorgaDepartment of Psychiatry, Columbia University, and New York State Psychiatric Institute, New York, USA.
Deepak K SarpalDepartment of Psychiatry, School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania, USA.
Miklos ArgyelanDonald and Barbara Zucker School of Medicine at Hofstra University - Northwell Health, New York, USA.
Juan GallegoDonald and Barbara Zucker School of Medicine at Hofstra University - Northwell Health, New York, USA.
John CholewaInstitute of Behavioral Science, Feinstein Institutes for Medical Research, Northwell Health, New York, USA.
Anita BarberDonald and Barbara Zucker School of Medicine at Hofstra University - Northwell Health, New York, USA.
John KaneDonald and Barbara Zucker School of Medicine at Hofstra University - Northwell Health, New York, USA.
Anil MalhotraDonald and Barbara Zucker School of Medicine at Hofstra University - Northwell Health, New York, USA.

Funding

Striatal Connectivity and Clinical Outcome in PsychosisR01MH108654 · NIMH · FEINSTEIN INSTITUTE FOR MEDICAL RESEARCH · PI MALHOTRA, ANIL K · 2016 to 2021
$2.8M
Striatal Function in Psychosis RelapseK23MH127300 · NIMH · FEINSTEIN INSTITUTE FOR MEDICAL RESEARCH · PI RUBIO, JOSE M · 2021 to 2024
$689k
NIMH NIH HHS K23 MH127300NIMH NIH HHS R01 MH108654
6 · The paper itself

Abstract

To bring biomarkers closer to clinical application, they should be generalizable, reliable, and maintain performance within the constraints of routine clinical conditions. The functional striatal abnormalities (FSA), is among the most advanced neuroimaging biomarkers in schizophrenia, trained to discriminate diagnosis, with post-hoc analyses indicating prognostic properties. Here, we attempt to replicate its diagnostic capabilities measured by the area under the curve (AUC) in receiver operator characteristic curves discriminating individuals with psychosis (n=101) from healthy controls (n=51) in the Human Connectome Project for Early Psychosis. We also measured the test-retest (run 1 vs 2) and phase encoding direction (i.e., AP vs PA) reliability with intraclass correlation coefficients (ICC). Additionally, we measured effects of scan length on classification accuracy (i.e., AUCs) and reliability (i.e., ICCs). Finally, we tested the prognostic capability of the FSA by the correlation between baseline scores and symptom improvement over 12 weeks of antipsychotic treatment in a separate cohort (n=97). Similar analyses were conducted for the Yeo networks intrinsic connectivity as a reference. The FSA had good/excellent diagnostic discrimination (AUC=75.4%, 95%CI=67.0%-83.3%; in non-affective psychosis AUC=80.5%, 95%CI=72.1-88.0%, and in affective psychosis AUC=58.7%, 95%CI=44.2-72.0%). Test-retest reliability ranged between ICC=0.48 (95%CI=0.35-0.59) and ICC=0.22 (95%CI=0.06-0.36), which was comparable to that of networks intrinsic connectivity. Phase encoding direction reliability for the FSA was ICC=0.51 (95%CI=0.42-0.59), generally lower than for networks intrinsic connectivity. By increasing scan length from 2 to 10 minutes, diagnostic classification of the FSA increased from AUC=71.7% (95%CI=63.1%-80.3%) to 75.4% (95%CI=67.0%-83.3%) and phase encoding direction reliability from ICC=0.29 (95%CI=0.14-0.43) to ICC=0.51 (95%CI=0.42-0.59). FSA scores did not correlate with symptom improvement. These results reassure that the FSA is a generalizable diagnostic - but not prognostic - biomarker. Given the replicable results of the FSA as a diagnostic biomarker trained on case-control datasets, next the development of prognostic biomarkers should be on treatment-response data.

Identifiers

PMID37503088
PMCPMC10371185

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LicenceCC BY-NC-ND
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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.