ArticleBiological psychiatry2021
Toward Generalizable and Transdiagnostic Tools for Psychosis Prediction: An Independent Validation and Improvement of the NAPLS-2 Risk Calculator in the Multisite PRONIA Cohort.
Article in Biological psychiatry, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers, 2 of them syntheses that pooled it.
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Who cites it
26 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Prognostic accuracy and clinical utility of psychometric instruments for individuals at clinical high-risk of psychosis: a systematic review and meta-analysis.Molecular psychiatry · 2022Pooled it
- Examining the variability of neurocognitive functioning in individuals at clinical high risk for psychosis: a meta-analysis.Translational psychiatry · 2022Pooled it
- Psychosis Polyrisk Score and Polygenic Risk Score to Improve Detection and Prognosis in Individuals at Clinical High Risk for Psychosis: Model Development and Internal Validation.Schizophrenia bulletin · 2026Article
- Precision sleep signatures to predict mental health outcomes in youth.Biological psychiatry. Cognitive neuroscience and neuroimaging · 2026Review
- Decoding Psychosis Risk: Neuroanatomical Correlates of the NAPLS-2 Calculator in the PRONIA Cohort.Schizophrenia bulletin · 2026Article
- Pediatric precision sleep network: a study protocol for identifying sleep signatures of mental health risk in peri-adolescents.BMC pediatrics · 2026Article
- Prediction modeling in transdiagnostic risk: results from the PROCAN study.Brain imaging and behavior · 2026Article
- Value representation in youth psychopathology: evidence of a transdiagnostic risk mechanism for psychosis.Translational psychiatry · 2026Article
- Increased Brain-Age Gap in Young Adults With Psychotic Experiences.Biological psychiatry global open science · 2026Article
- Predicting Ultra-High Risk Outcomes Using Linguistic and Acoustic Measures From High-Risk Social Challenge Recordings: mHealth Longitudinal Cohort Exploratory Study.JMIR formative research · 2025Article
- Characterizing the Clinical Trajectory and Predicting Persistence and Deterioration of Attenuated Psychotic Symptoms in Ultra-High-Risk Individuals.Schizophrenia bulletin · 2025Article
- Data analysis strategies for the Accelerating Medicines Partnership® Schizophrenia Program.Schizophrenia (Heidelberg, Germany) · 2025Article
- Mapping the neurodevelopmental predictors of psychopathology.Molecular psychiatry · 2025Article
- Towards collaborative data science in mental health research: The ECNP neuroimaging network accessible data repository.Neuroscience applied · 2025Article
- Multimodal prediction of the need of clozapine in treatment resistant schizophrenia; a pilot study in first-episode psychosis.Biomarkers in neuropsychiatry · 2024Article
- Multivariable prediction of functional outcome after first-episode psychosis: a crossover validation approach in EUFEST and PSYSCAN.Schizophrenia (Heidelberg, Germany) · 2024Article
- Are factors that predict conversion to psychosis associated with initial transition to a high risk state? An adolescent brain cognitive development study analysis.Schizophrenia research · 2024Article
- Identification of distinct clinical profiles and trajectories in individuals at high risk of developing psychosis: A latent profile analysis of the north American prodrome longitudinal study consortium-3 dataset.Early intervention in psychiatry · 2024Article
- Using brain structural neuroimaging measures to predict psychosis onset for individuals at clinical high-risk.Molecular psychiatry · 2024Article
- Accelerating Medicines Partnership® Schizophrenia (AMP® SCZ): Rationale and Study Design of the Largest Global Prospective Cohort Study of Clinical High Risk for Psychosis.Schizophrenia bulletin · 2024Article
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Abstract
backgroundTransition to psychosis is among the most adverse outcomes of clinical high-risk (CHR) syndromes encompassing ultra-high risk (UHR) and basic symptom states. Clinical risk calculators may facilitate an early and individualized interception of psychosis, but their real-world implementation requires thorough validation across diverse risk populations, including young patients with depressive syndromes.
methodsWe validated the previously described NAPLS-2 (North American Prodrome Longitudinal Study 2) calculator in 334 patients (26 with transition to psychosis) with CHR or recent-onset depression (ROD) drawn from the multisite European PRONIA (Personalised Prognostic Tools for Early Psychosis Management) study. Patients were categorized into three risk enrichment levels, ranging from UHR, over CHR, to a broad-risk population comprising patients with CHR or ROD (CHR|ROD). We assessed how risk enrichment and different predictive algorithms influenced prognostic performance using reciprocal external validation.
resultsAfter calibration, the NAPLS-2 model predicted psychosis with a balanced accuracy (BAC) (sensitivity, specificity) of 68% (73%, 63%) in the PRONIA-UHR cohort, 67% (74%, 60%) in the CHR cohort, and 70% (73%, 66%) in patients with CHR|ROD. Multiple model derivation in PRONIA-CHR|ROD and validation in NAPLS-2-UHR patients confirmed that broader risk definitions produced more accurate risk calculators (CHR|ROD-based vs. UHR-based performance: 67% [68%, 66%] vs. 58% [61%, 56%]). Support vector machines were superior in CHR|ROD (BAC = 71%), while ridge logistic regression and support vector machines performed similarly in CHR (BAC = 67%) and UHR cohorts (BAC = 65%). Attenuated psychotic symptoms predicted psychosis across risk levels, while younger age and reduced processing speed became increasingly relevant for broader risk cohorts.
conclusionsClinical-neurocognitive machine learning models operating in young patients with affective and CHR syndromes facilitate a more precise and generalizable prediction of psychosis. Future studies should investigate their therapeutic utility in large-scale clinical trials.
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