Deconstructing Pretest Risk Enrichment to Optimize Prediction of Psychosis in Individuals at Clinical High Risk
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IMPORTANCE: Pretest risk estimation is routinely used in clinical medicine to inform further diagnostic testing in individuals with suspected diseases. To our knowledge, the overall characteristics and specific determinants of pretest risk of psychosis onset in individuals undergoing clinical high risk (CHR) assessment are unknown. OBJECTIVES: To investigate the characteristics and determinants of pretest risk of psychosis onset in individuals undergoing CHR assessment and to develop and externally validate a pretest risk stratification model. DESIGN, SETTING, AND PARTICIPANTS: Clinical register-based cohort study. Individuals were drawn from electronic, real-world, real-time clinical records relating to routine mental health care of CHR services in South London and the Maudsley National Health Service Trust in London, United Kingdom. The study included nonpsychotic individuals referred on suspicion of psychosis risk and assessed by the Outreach and Support in South London CHR service from 2002 to 2015. Model development and validation was performed with machine-learning methods based on Least Absolute Shrinkage and Selection Operator for Cox proportional hazards model. MAIN OUTCOMES AND MEASURES: Pretest risk of psychosis onset in individuals undergoing CHR assessment. Predictors included age, sex, age × sex interaction, race/ethnicity, socioeconomic status, marital status, referral source, and referral year. RESULTS: A total of 710 nonpsychotic individuals undergoing CHR assessment were included. The mean age was 23 years. Three hundred ninety-nine individuals were men (56%), their race/ethnicity was heterogenous, and they were referred from a variety of sources. The cumulative 6-year pretest risk of psychosis was 14.55% (95% CI, 11.71% to 17.99%), confirming substantial pretest risk enrichment during the recruitment of individuals undergoing CHR assessment. Race/ethnicity and source of referral were associated with pretest risk enrichment. The predictive model based on these factors was externally validated, showing moderately good discrimination and sufficient calibration. It was used to stratify individuals undergoing CHR assessment into 4 classes of pretest risk (6-year): low, 3.39% (95% CI, 0.96% to 11.56%); moderately low, 11.58% (95% CI, 8.10% to 16.40%); moderately high, 23.69% (95% CI, 16.58% to 33.20%); and high, 53.65% (95% CI, 36.78% to 72.46%). CONCLUSIONS AND RELEVANCE: Significant risk enrichment occurs before individuals are assessed for a suspected CHR state. Race/ethnicity and source of referral are associated with pretest risk enrichment in individuals undergoing CHR assessment. A stratification model can identify individuals at differential pretest risk of psychosis. Identification of these subgroups may inform outreach campaigns and subsequent testing and eventually optimize psychosis prediction.
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Unstructured recruitment processes and risk enrichment procedures in samples undergoing clinical high-risk for psychosis assessment substantially determine the actual level of psychosis risk in these individuals, leading to underpowered and non-significant trials.
“For example, it is apparent that unstructured recruitment processes and risk enrichment procedures in samples undergoing CHR-P assessment have a substantial role in determining the actual level of risk for psychosis in these individuals 107-109 , leading to underpowered and non-significant trials 95 .”
From Lack of evidence to favor specific preventive interventions in psychosis: a network meta‐analysis (2018) · cites this paper as [108]
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Self-citationEstablishing a clinical service to prevent psychosis: What, how and when? Systematic review
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Self-citationWhat Is an Attenuated Psychotic Symptom? On the Importance of the Context
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Self-citationFusar-Poli, P., Spencer, T., De Micheli, A., Curzi, V., Nandha, S., & McGuire, P. (2020) · European Neuropsychopharmacology · doi:10.1016/j.euroneuro.2020.08.002 · Cited by 57 · see citing works
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Self-citationSemistructured Interview for Bipolar At Risk States (SIBARS)
Fusar‐Poli, P., Micheli, A. D., Rocchetti, M., Cappucciati, M., Ramella‐Cravaro, V., Rutigliano, G., Bonoldi, I., McGuire, P. K., & Falkenberg, I. (2018) · Psychiatry Research · doi:10.1016/j.psychres.2018.03.074 · Cited by 59 · see citing works
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Extending the Benefits of Indicated Prevention to Improve Outcomes of First-Episode Psychosis
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Self-citationDiagnosis, prognosis, and treatment of brief psychotic episodes: a review and research agenda
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Self-citationPredicting Remission in Subjects at Clinical High Risk for Psychosis Using Mismatch Negativity
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Self-citationMinichino, A., Rutigliano, G., Merlino, S., Davies, C., Oliver, D., Micheli, A. D., Patel, R., McGuire, P. K., & Fusar‐Poli, P. (2019) · European Psychiatry · doi:10.1016/j.eurpsy.2018.12.006 · Cited by 36 · see citing works
Self-citationFusar‐Poli, P., Micheli, A. D., Cappucciati, M., Rutigliano, G., Davies, C., Ramella‐Cravaro, V., Oliver, D., Bonoldi, I., Rocchetti, M., Gavaghan, L., et al. (2017) · Schizophrenia Bulletin · doi:10.1093/schbul/sbx055 · Cited by 34 · see citing works
Self-citationThe critical need for help-seeking controls in clinical high-risk research
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Care Pathways Before First Diagnosis of a Psychotic Disorder in Adolescents and Young Adults
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Self-citationMillman, Z. B., Roemer, C., Vargas, T., Schiffman, J. E., Mittal, V. A., & Gold, J. M. (2022) · Schizophrenia Bulletin · doi:10.1093/schbul/sbac031 · Cited by 30 · see citing works
Exploring causal mechanisms of psychosis risk
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Pan-London Network for Psychosis-Prevention (PNP)
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Self-citationLongitudinal Analyses of Blood Transcriptome During Conversion to Psychosis
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Prediction of psychosis: model development and internal validation of a personalized risk calculator
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A transdiagnostic prodrome for severe mental disorders: an electronic health record study
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A Case of a College Student Presenting With Mild Mental Health Problems
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Cullen, A. E., Labad, J., Oliver, D., Al‐Diwani, A., Minichino, A., & Fusar‐Poli, P. (2023) · Current Neuropharmacology · doi:10.2174/1570159x21666230322145049 · Cited by 22 · see citing works
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Self-citationByrne, M., Codjoe, L., Morgan, C., Stahl, D. R., Day, F., Fearon, P., Fusar‐Poli, P., Power, P., McGuire, P. K., & Valmaggia, L. (2018) · Psychiatry Research · doi:10.1016/j.psychres.2018.12.111 · Cited by 16 · see citing works
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Negative Psychosis Prevention Trials
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Self-citationDoes reason for referral to an ultra‐high risk clinic predict transition to psychosis?
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Mapping the implementation and challenges of clinical services for psychosis prevention in England
Estradé, A., Spencer, T. J., Micheli, A. D., Murguia, S., Provenzani, U., McGuire, P. K., & Fusar‐Poli, P. (2023) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2022.945505 · Cited by 9 · see citing works
Self-citationITAlian Partnership for Psychosis Prevention (ITAPP): improving the mental health of young people
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Self-citationFederated multi-site longitudinal study of at-risk mental state for psychosis in Japan
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Resurrection of the Follow-Back Method to Study the Transdiagnostic Origins of Psychosis
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- Authors
- Fusar-Poli, P., Rutigliano, G., Stahl, D., Schmidt, A., Ramella-Cravaro, V., Hitesh, S., & McGuire, P.
- Affiliations
- King's College London, Institute of Psychiatry, Psychology, and Neuroscience, London, United Kingdom2Outreach and Support in South London service, South London and the Maudsley National Health Service Foundation Trust, London, United Kingdom
- University of Pisa (IT)
- King's College London (GB)
- King's College London, Institute of Psychiatry, Psychology, and Neuroscience, London, United Kingdom4Department of Neurosciences, Psychology, Drug Research and Child Health, University of Florence, Florence, Italy
- South London and the Maudsley National Health Service Foundation Trust, Biomedical Research Centre Nucleus, London, United Kingdom
- Venue
- JAMA Psychiatry
- Publisher
- American Medical Association (AMA)
- Published
- 2016-12-01
- Volume
- 73
- Issue
- 12
- Pages
- 1260
- ISSN
- 2168-622X (ISSN-L)
- OpenAlex
- W2541736368
- Cited by
- 121
- References
- 59
- Citations by year
- 2026: 4 · 2025: 7 · 2024: 6 · 2023: 7 · 2022: 8 · 2021: 18 · 2020: 16 · 2019: 20 · 2018: 20 · 2017: 12 · 2016: 3
- FWCI
- 16.32
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- JAMA Psychiatry (publishedVersion)
- PubMed (publishedVersion)
- edoc (University of Basel) (acceptedVersion)
- CINECA IRIS Institutial research information system (University of Pisa) (submittedVersion)
- Research Portal (King's College London) (submittedVersion, other-oa)
- Funders
- National Science Foundation
- National Alliance for Research on Schizophrenia and Depression
- National Institute for Health and Care Research
- King's College London
- Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung
- Medical Research Council (MR/N026063/1)
- Topics
- Health Sciences › Medicine › Psychiatry and Mental health › Schizophrenia research and treatment
- Social Sciences › Psychology › Clinical Psychology › Psychopathy, Forensic Psychiatry, Sexual Offending
- Health Sciences › Medicine › Psychiatry and Mental health › Bipolar Disorder and Treatment
- Keywords
- psychosis onset prediction, clinical high risk, risk stratification model, race and ethnicity, referral sources, external validation, LASSO Cox regression, psychosis prevention, socioeconomic status, sex differences, sex-age interaction, mental health services
- MeSH terms
- Adult, Female, Follow-Up Studies, Humans, London, Male, Patient Acceptance of Health Care, Psychotic Disorders, Referral and Consultation, Cohort Studies, Proportional Hazards Models, Risk Assessment, Young Adult
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