ArticleSchizophrenia bulletin2024
Disease Progression Patterns of Brain Morphology in Schizophrenia: More Progressed Stages in Treatment Resistance.
Article in Schizophrenia bulletin, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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.
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.
Who cites it
11 citing papers in PubMed, 18 citations in OpenAlex.
- Metabolic biomarkers of treatment-resistant schizophrenia and cognitive correlates: insights from a machine learning.Molecular psychiatry · 2026Article
- Neuroimaging-Based Subgroups in Schizophrenia: A Critical Appraisal of Clustering Studies.Biological psychiatry global open science · 2026Review
- Data-driven schizophrenia subtyping via brain atrophy trajectories and functional connectivity.Translational psychiatry · 2026Article
- Subtyping schizophrenia via machine learning by using structural neuroimaging.Translational psychiatry · 2025Review
- Longitudinal changes in striatocortical connectivity in first-episode psychosis associated with the emergence of treatment resistance.Schizophrenia (Heidelberg, Germany) · 2025Article
- Thinning of the temporal and insular cortex is associated with negative symptoms and impaired attention in Chinese chronic schizophrenia patients with deficit syndrome.BMC psychiatry · 2025Article
- Diagnosis of Schizophrenia and Its Subtypes Using MRI and Machine Learning.Brain and behavior · 2025Article
- Two distinct trajectories of brain volume loss in myotonic dystrophy type 1 via machine learning.Brain communications · 2025Article
- Addressing brain metabolic connectivity in treatment-resistant schizophrenia: a novel graph theory-driven application ofSchizophrenia (Heidelberg, Germany) · 2024Article
- Longitudinal inference of multiscale markers in psychosis: from hippocampal centrality to functional outcome.Molecular psychiatry · 2024Article
- Estimated Disease Progression Trajectory of White Matter Disruption in Unilateral Temporal Lobe Epilepsy: A Data-Driven Machine Learning Approach.Brain sciences · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
29 authors at 4 institutions in 3 countries.
Funding
Abstract
background and hypothesisGiven the heterogeneity and possible disease progression in schizophrenia, identifying the neurobiological subtypes and progression patterns in each patient may lead to novel biomarkers. Here, we adopted data-driven machine-learning techniques to identify the progression patterns of brain morphological changes in schizophrenia and investigate the association with treatment resistance. STUDY
designIn this cross-sectional multicenter study, we included 177 patients with schizophrenia, characterized by treatment response or resistance, with 3D T1-weighted magnetic resonance imaging. Cortical thickness and subcortical volumes calculated by FreeSurfer were converted into z scores using 73 healthy controls data. The Subtype and Stage Inference (SuStaIn) algorithm was used for unsupervised machine-learning analysis. STUDY
resultsSuStaIn identified 3 different subtypes: (1) subcortical volume reduction (SC) type (73 patients), in which volume reduction of subcortical structures occurs first and moderate cortical thinning follows, (2) globus pallidus hypertrophy and cortical thinning (GP-CX) type (42 patients), in which globus pallidus hypertrophy initially occurs followed by progressive cortical thinning, and (3) cortical thinning (pure CX) type (39 patients), in which thinning of the insular and lateral temporal lobe cortices primarily happens. The remaining 23 patients were assigned to baseline stage of progression (no change). SuStaIn also found 84 stages of progression, and treatment-resistant schizophrenia showed significantly more progressed stages than treatment-responsive cases (P = .001). The GP-CX type presented earlier stages than the pure CX type (P = .009).
conclusionsThe brain morphological progressions in schizophrenia can be classified into 3 subtypes, and treatment resistance was associated with more progressed stages, which may suggest a novel biomarker.
Indexed as
Identifiers
What OpenQuestion holds
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.