SynthesisSchizophrenia bulletin2017
Improving Prognostic Accuracy in Subjects at Clinical High Risk for Psychosis: Systematic Review of Predictive Models and Meta-analytical Sequential Testing Simulation.
Synthesis in Schizophrenia bulletin, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 67 papers, 5 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
67 citing papers in PubMed, 5 syntheses or guidelines pooled it.
- Systematic review of clinical prediction models for psychosis in individuals meeting At Risk Mental State criteria.Frontiers in psychiatry · 2024Pooled it
- Longitudinal Structural MRI Findings in Individuals at Genetic and Clinical High Risk for Psychosis: A Systematic Review.Frontiers in psychiatry · 2021Pooled it
- What Causes the Onset of Psychosis in Individuals at Clinical High Risk? A Meta-analysis of Risk and Protective Factors.Schizophrenia bulletin · 2020Pooled it
- Preventive Treatments for Psychosis: Umbrella Review (Just the Evidence).Frontiers in psychiatry · 2019Pooled 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
- Dopamine-Induced Dysconnectivity Between Salience Network and Auditory Cortex in Subjects With Psychotic-like Experiences: A Randomized Double-Blind Placebo-Controlled Study.Schizophrenia bulletin · 2020Trial
- Using Electronic Health Records to Identify Medical Presentation for Self-harm as a Predictor of Psychotic or Bipolar Disorders: A Systems-level Alternative to the Clinical High-risk Approach.Schizophrenia bulletin · 2026Article
- Predicting long-term poor outcomes in individuals at clinical high risk for psychosis using real-world clinical data: the OASIS1000 prospective study.World psychiatry : official journal of the World Psychiatric Association (WPA) · 2026Article
- Machine learning-based morphological brain analysis in schizophrenia and unaffected siblings: a multisite study of potential risk markers.Frontiers in neuroscience · 2026Article
- Development and Validation of a Nomogram for Estimating the Risk of Suicide Tendencies Among Chinese Middle School Students: A Cross-Sectional Study.Psychology research and behavior management · 2026Article
- Predicting ordinal clinical outcomes in at-risk mental states: a multimodal approach.Frontiers in psychiatry · 2026Article
- A Phenomenological Reappraisal of Dynamical Systems in Psychopathology.Psychopathology · 2025Review
- Revealing differential psychotic symptoms in schizophrenia and bipolar I disorder by manifold learning and network analyses.Translational psychiatry · 2025Article
- Eye Movement Characteristics for Predicting a Transition to Psychosis: Longitudinal Changes and Implications.Schizophrenia bulletin · 2025Observational
- Neurocognitive Deficits in Individuals at Ultra-High-Risk for Psychosis: An Overview of Systematic Reviews.Iranian journal of psychiatry · 2025Review
- Psychotic Arousal and the Psychopathology of Acute Schizophrenia: An Exploratory Study of the Experiential Emotional State in Acute Psychosis.Journal of clinical medicine · 2024Article
- Applicability of machine learning algorithm to predict the therapeutic intervention success in Brazilian smokers.PloS one · 2024Article
- Development of transdiagnostic clinical risk prediction models for 12-month onset and course of eating disorders among adolescents in the community.The International journal of eating disorders · 2023Article
- Diagnostic specificity of the child psychosis-risk screening system with a focus on the differentiation of schizophrenia spectrum disorders and neurodevelopmental disorders.Frontiers in child and adolescent psychiatry · 2023Article
- Implementing predictive tools in surgery: A narrative review in the context of orthopaedic surgery.ANZ journal of surgery · 2022Review
7 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
12 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Discriminating subjects at clinical high risk (CHR) for psychosis who will develop psychosis from those who will not is a prerequisite for preventive treatments. However, it is not yet possible to make any personalized prediction of psychosis onset relying only on the initial clinical baseline assessment. Here, we first present a systematic review of prognostic accuracy parameters of predictive modeling studies using clinical, biological, neurocognitive, environmental, and combinations of predictors. In a second step, we performed statistical simulations to test different probabilistic sequential 3-stage testing strategies aimed at improving prognostic accuracy on top of the clinical baseline assessment. The systematic review revealed that the best environmental predictive model yielded a modest positive predictive value (PPV) (63%). Conversely, the best predictive models in other domains (clinical, biological, neurocognitive, and combined models) yielded PPVs of above 82%. Using only data from validated models, 3-stage simulations showed that the highest PPV was achieved by sequentially using a combined (clinical + electroencephalography), then structural magnetic resonance imaging and then a blood markers model. Specifically, PPV was estimated to be 98% (number needed to treat, NNT = 2) for an individual with 3 positive sequential tests, 71%-82% (NNT = 3) with 2 positive tests, 12%-21% (NNT = 11-18) with 1 positive test, and 1% (NNT = 219) for an individual with no positive tests. This work suggests that sequentially testing CHR subjects with predictive models across multiple domains may substantially improve psychosis prediction following the initial CHR assessment. Multistage sequential testing may allow individual risk stratification of CHR individuals and optimize the prediction of psychosis.
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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.