ReviewNeurobiology of disease2019
Neuroimaging markers of antipsychotic treatment response in schizophrenia: An overview of magnetic resonance imaging studies.
Review in Neurobiology of disease, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers, 1 of them a synthesis that pooled 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.
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
26 citing papers in PubMed, 1 synthesis or guideline pooled it.
- fMRI connectivity as a biomarker of antipsychotic treatment response: A systematic review.NeuroImage. Clinical · 2023Pooled it
- Symptom Remission and Brain Cortical Networks at First Clinical Presentation of Psychosis: The OPTiMiSE Study.Schizophrenia bulletin · 2021Trial
- 7T magnetic resonance spectroscopic imaging of subcortical neurometabolites across antipsychotic treatment in acutely symptomatic early-phase schizophrenia spectrum disorders.Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology · 2026Article
- Cortical Structures Underlying Schizophrenia and Sex Differences in Preadolescents: An Adolescent Brain Cognitive Development Study.Child psychiatry and human development · 2026Article
- Longitudinal brain structural changes during clozapine treatment: associations with neuroreceptor architecture and clinical response.medRxiv : the preprint server for health sciences · 2026Article
- Machine Learning Models for Predicting Antipsychotic Effectiveness and Separate Cost-Effectiveness Analysis in Hospitalized Schizophrenia Patients.Neuropsychiatric disease and treatment · 2026Article
- Effects on Multimodal Connectivity Patterns in Female Schizophrenia During 8 Weeks of Antipsychotic Treatment.Schizophrenia bulletin · 2025Article
- Can artificial intelligence be the future solution to the enormous challenges and suffering caused by Schizophrenia?Schizophrenia (Heidelberg, Germany) · 2025Review
- Genetic markers of early response to lurasidone in acute schizophrenia.The pharmacogenomics journal · 2025Article
- Hippocampal subfields in remitted schizophrenia.Journal of the Chinese Medical Association : JCMA · 2024Article
- The network characteristics in schizophrenia with prominent negative symptoms: a multimodal fusion study.Schizophrenia (Heidelberg, Germany) · 2024Article
- Effects of long-term antipsychotic medication on brain instability in first-episode schizophrenia patients: a resting-state fMRI study.Frontiers in pharmacology · 2024Article
- Article
- Structure-function coupling in white matter uncovers the abnormal brain connectivity in Schizophrenia.Translational psychiatry · 2023Article
- Increased Functional Connectivity Involving the Parahippocampal Gyrus in Patients with Schizophrenia during Theory of Mind Processing: A Psychophysiological Interaction Study.Brain sciences · 2023Article
- Machine learning methods to predict outcomes of pharmacological treatment in psychosis.Translational psychiatry · 2023Review
- Schizophrenia: A Narrative Review of Etiopathogenetic, Diagnostic and Treatment Aspects.Journal of clinical medicine · 2022Article
- Antipsychotics Effects on Network-Level Reconfiguration of Cortical Morphometry in First-Episode Schizophrenia.Schizophrenia bulletin · 2022Article
- Predicting Treatment Response in Schizophrenia With Magnetic Resonance Imaging and Polygenic Risk Score.Frontiers in genetics · 2022Article
- The promise of machine learning in predicting treatment outcomes in psychiatry.World psychiatry : official journal of the World Psychiatric Association (WPA) · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
Antipsychotic drugs are the primary treatment for psychosis, yet individual response to their administration remains variable. At present, no biological predictors of response exist to guide clinicians as they select treatments for patients, and our understanding of the neurobiology underlying the heterogeneity of outcomes remains limited. Magnetic Resonance Imaging (MRI) has been applied by numerous studies to examine the response to antipsychotic treatment, though a large gap remains between their results and our clinical practice. To advance patient care with precision medicine approaches, prior work must be accounted for and built upon with future studies. This review provides an overview of studies that relate treatment outcome to various MRI-related measures, including structural, spectroscopic, diffusion tensor, and functional imaging. Knowledge derived from these studies will be discussed along with future directions for the field.
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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.