SynthesisMolecular psychiatry2025
Predicting treatment outcomes in major depressive disorder using brain magnetic resonance imaging: a meta-analysis.
Synthesis in Molecular psychiatry, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 2 of them syntheses that pooled 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.
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
14 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Early Predictive Accuracy of Machine Learning for Hemorrhagic Transformation in Acute Ischemic Stroke: Systematic Review and Meta-Analysis.Journal of medical Internet research · 2025Pooled it
- Neural Activity Alterations and Their Association With Neurotransmitter and Genetic Profiles in Schizophrenia: Evidence From Clinical Patients and Unaffected Relatives.CNS neuroscience & therapeutics · 2025Pooled it
- Insular spontaneous activity changes after dialectical behavior therapy skills training for depressed patients with non-suicidal self-injury: a randomized controlled trial.BMC psychiatry · 2026Trial
- Prediction of generalized anxiety disorder treatment outcomes with neurobehavioral responses to approach-avoidance conflict: a randomized clinical trial.Translational psychiatry · 2025Trial
- Resting-state functional connectivity of the default mode network as a predictor for escitalopram response in adolescents with depression.Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology · 2026Article
- Neural predictors of treatment outcome through emotion regulation in internalizing disorders: a narrative review.Translational psychiatry · 2026Review
- Little information, great impact? A clinical tool for the prediction of electroconvulsive therapy effectiveness in depression.BJPsych open · 2026Article
- Clinical and biological markers of electroconvulsive therapy effectiveness: a narrative review.Translational psychiatry · 2026Review
- Network localization of genetic risk for schizophrenia and bipolar disorder.Psychological medicine · 2025Article
- Predicting antidepressant response via local-global graph neural network and neuroimaging biomarkers.NPJ digital medicine · 2025Article
- Default mode network static-dynamic functional signatures in first-episode drug-naive major depressive disorder.Comprehensive psychoneuroendocrinology · 2025Article
- Individualized gray matter morphological abnormalities unveil two neuroanatomical obsessive-compulsive disorder subtypes.Translational psychiatry · 2025Article
- Group-specific discriminant analysis enhances detection of sex differences in brain functional network lateralization.GigaScience · 2025Article
- Effects of intermittent theta burst to the left dorsolateral prefrontal cortex on brain volumes and neurometabolites in people with alcohol use disorder: a preliminary investigation.Frontiers in human neuroscience · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
13 authors.
Funding
Abstract
Recent studies have provided promising evidence that neuroimaging data can predict treatment outcomes for patients with major depressive disorder (MDD). As most of these studies had small sample sizes, a meta-analysis is warranted to identify the most robust findings and imaging modalities, and to compare predictive outcomes obtained in magnetic resonance imaging (MRI) and studies using clinical and demographic features. We conducted a literature search from database inception to July 22, 2023, to identify studies using pretreatment clinical or brain MRI features to predict treatment outcomes in patients with MDD. Two meta-analyses were conducted on clinical and MRI studies, respectively. The meta-regression was employed to explore the effects of covariates and compare the predictive performance between clinical and MRI groups, as well as across MRI modalities and intervention subgroups. Meta-analysis of 13 clinical studies yielded an area under the curve (AUC) of 0.73, while in 44 MRI studies, the AUC was 0.89. MRI studies showed a higher sensitivity than clinical studies (0.78 vs. 0.62, Z = 3.42, P = 0.001). In MRI studies, resting-state functional MRI (rsfMRI) exhibited a higher specificity than task-based fMRI (tbfMRI) (0.79 vs. 0.69, Z = -2.86, P = 0.004). No significant differences in predictive performance were found between structural and functional MRI, nor between different interventions. Of note, predictive MRI features for treatment outcomes in studies using antidepressants were predominantly located in the limbic and default mode networks, while studies of electroconvulsive therapy (ECT) were restricted mainly to the limbic network. Our findings suggest a promise for pretreatment brain MRI features to predict MDD treatment outcomes, outperforming clinical features. While tasks in tbfMRI studies differed, those studies overall had less predictive utility than rsfMRI data. Overlapping but distinct network-level measures predicted antidepressants and ECT outcomes. Future studies are needed to predict outcomes using multiple MRI features, and to clarify whether imaging features predict outcomes generally or differ depending on treatments.
Indexed as
Identifiers
39187625What Socratic 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 Socratic graph.