ArticleSchizophrenia bulletin2014
Psychosis prediction: stratification of risk estimation with information-processing and premorbid functioning variables.
Article in Schizophrenia bulletin, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 43 papers, 3 of them syntheses that pooled it.
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Who cites it
43 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- Individualized Prediction of Transition to Psychosis in 1,676 Individuals at Clinical High Risk: Development and Validation of a Multivariable Prediction Model Based on Individual Patient Data Meta-Analysis.Frontiers in psychiatry · 2019Pooled it
- Improving Prognostic Accuracy in Subjects at Clinical High Risk for Psychosis: Systematic Review of Predictive Models and Meta-analytical Sequential Testing Simulation.Schizophrenia bulletin · 2017Pooled it
- Pooled it
- Machine learning helps predict early onset psychosis with serum protein biomarkers, neuropsychometry, and clinicodemographic data.Scientific reports · 2025Article
- Clinical prediction model for transition to psychosis in individuals meeting At Risk Mental State criteria.Schizophrenia (Heidelberg, Germany) · 2025Article
- Psychosis Endophenotypes: A Gene-Set-Specific Polygenic Risk Score Analysis.Schizophrenia bulletin · 2023Article
- Value of P300 amplitude in the diagnosis of untreated first-episode schizophrenia and psychosis risk syndrome in children and adolescents.BMC psychiatry · 2023Article
- Developmental trajectories of premorbid functioning predict cognitive remediation treatment response in first-episode schizophrenia.Psychological medicine · 2023Article
- A multivariate approach to investigate the associations of electrophysiological indices with schizophrenia clinical and functional outcome.European psychiatry : the journal of the Association of European Psychiatrists · 2023Article
- A systematic review of premorbid cognitive functioning and its timing of onset in schizophrenia spectrum disorders.Schizophrenia research. Cognition · 2022Article
- Identifying Electroencephalography Biomarkers in Individuals at Clinical High Risk for Psychosis in an International Multi-Site Study.Frontiers in psychiatry · 2022Article
- Timing dysfunction and cerebellar resting state functional connectivity abnormalities in youth at clinical high-risk for psychosis.Psychological medicine · 2021Article
- Prolonged P300 Latency in Antipsychotic-Free Subjects with At-Risk Mental States Who Later Developed Schizophrenia.Journal of personalized medicine · 2021Article
- Forecasting Remission From the Psychosis Risk Syndrome With Mismatch Negativity and P300: Potentials and Pitfalls.Biological psychiatry. Cognitive neuroscience and neuroimaging · 2021Review
- P300 as an index of transition to psychosis and of remission: Data from a clinical high risk for psychosis study and review of literature.Schizophrenia research · 2020Review
- Longitudinal evaluation of visual P300 amplitude in clinical high-risk subjects: An event-related potential study.Psychiatry and clinical neurosciences · 2020Article
- Familial and socioeconomic contributions to premorbid functioning in psychosis: Impact on age at onset and treatment response.European psychiatry : the journal of the Association of European Psychiatrists · 2020Article
- Brain functional connectivity data enhance prediction of clinical outcome in youth at risk for psychosis.NeuroImage. Clinical · 2020Article
- Models Predicting Psychosis in Patients With High Clinical Risk: A Systematic Review.Frontiers in psychiatry · 2020Review
- Psychosocial characteristics differentiate non-distressing and distressing voices in 10,346 adolescents.European child & adolescent psychiatry · 2019Article
Corrections and comments
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Authors and funding
12 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe period preceding the first psychotic episode is regarded as a promising period for intervention. We aimed to develop an optimized prediction model of a first psychosis, considering different sources of information. The outcome of this model may be used for individualized risk estimation.
methodsSixty-one subjects clinically at high risk (CHR), participating in the Dutch Prediction of Psychosis Study, were assessed at baseline with instruments yielding data on neuropsychology, symptomatology, environmental factors, premorbid adjustment, and neurophysiology. The follow-up period was 36 months.
resultsAt 36 months, 18 participants (29.5%) had made a transition to psychosis. Premorbid adjustment (P = .001, hazard ratio [HR] = 2.13, 95% CI = 1.39/3.28) and parietal P300 amplitude (P = .004, HR = 1.27, 95% CI = 1.08/1.45) remained as predictors in the Cox proportional hazard model. The resulting prognostic score (PS) showed a sensitivity of 88.9% and a specificity of 82.5%. The area under the curve of the PS was 0.91 (95% CI = 0.83-0.98, cross-validation: 0.86), indicating an outstanding ability of the model to discriminate between transition and nontransition. The PS was further stratified into 3 risk classes establishing a prognostic index. In the class with the worst social-personal adjustment and lowest P300 amplitudes, 74% of the subjects made a transition to psychosis. Furthermore, transition emerged on average more than 17 months earlier than in the lowest risk class.
conclusionsOur results suggest that predicting a first psychotic episode in CHR subjects could be improved with a model including premorbid adjustment and information-processing variables in a multistep algorithm combining risk detection and stratification.
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