Andrea Polari1, Hok Pan Yuen2,3, Paul Amminger2,3, Gregor Berger4, Eric Chen5, Lieuwe deHaan6, Jessica Hartmann2,3, Connie Markulev2,3, Patrick McGorry2,3, Dorien Nieman7, Merete Nordentoft8, Anita Riecher-Rössler9, Stefan Smesny10, John Stratford1, Swapna Verma11, Alison Yung2,3, Suzie Lavoie2,3, Barnaby Nelson2,3. 1. Orygen Specialist Programs, Melbourne, Australia. 2. Orygen, Parkville, Victoria, Australia. 3. Centre for Youth Mental Health, The University of Melbourne, Parkville, Victoria, Australia. 4. Department of Child and Adolescent Psychiatry and Psychotherapy, University Hospital of Psychiatry Zurich, University of Zurich, Zurich, Switzerland. 5. Department of Psychiatry, The University of Hong Kong, Hong Kong, China. 6. Academic Medical Centre, University of Amsterdam and Arkin Institute for Mental Health, Amsterdam, The Netherlands. 7. Department of Psychiatry, Academic Medical Centre, Amsterdam, The Netherlands. 8. Psykiatrisk Center København, Forskningsenheden, København, Denmark. 9. Department of Psychiatry, University of Basel, Basel, Switzerland. 10. Department of Psychiatry, Universitätsklinikum Jena, Jena, Germany. 11. Early Psychosis Intervention Programme (EPIP), Institute of Mental Health, Singapore, Singapore.
Abstract
AIM: Several prediction models have been introduced to identify young people at greatest risk of transitioning to psychosis. To date, none has examined the possibility of developing a clinical prediction model of outcomes other than transition. The aims of this study were to examine the association between baseline clinical predictors and outcomes including, but not limited to, transition to psychosis in young people at risk for psychosis, and to develop a prediction model for these outcomes. METHODS: Several evidence-based variables previously associated with transition to psychosis and some important clinical comorbidities experienced by ultra-high risk (UHR) individuals were identified in 202 UHR individuals. Secondary analysis of the Neurapro clinical trial were conducted to investigate the associations between these variables and favourable (remission and recovery) or unfavourable (transition to psychosis, no remission, any recurrence and relapse) clinical outcomes. Logistic regression, best subset selection, Akaike Information Criterion and receiver operating characteristic curves were used to seek the best prediction model for clinical outcomes from all combinations of possible predictors. RESULTS: When considered individually, only higher general psychopathology levels (P = .023) was associated with the unfavourable outcomes. Prediction models suggest that general psychopathology and functioning are predictive of unfavourable outcomes. CONCLUSION: The predictive performance of the resulting models was modest and further research is needed. Nonetheless, when designing early intervention centres aiming to support individuals in the early phases of a mental disorder, the proper assessment of general psychopathology and functioning should be considered in order to inform interventions and length of care provided.
AIM: Several prediction models have been introduced to identify young people at greatest risk of transitioning to psychosis. To date, none has examined the possibility of developing a clinical prediction model of outcomes other than transition. The aims of this study were to examine the association between baseline clinical predictors and outcomes including, but not limited to, transition to psychosis in young people at risk for psychosis, and to develop a prediction model for these outcomes. METHODS: Several evidence-based variables previously associated with transition to psychosis and some important clinical comorbidities experienced by ultra-high risk (UHR) individuals were identified in 202 UHR individuals. Secondary analysis of the Neurapro clinical trial were conducted to investigate the associations between these variables and favourable (remission and recovery) or unfavourable (transition to psychosis, no remission, any recurrence and relapse) clinical outcomes. Logistic regression, best subset selection, Akaike Information Criterion and receiver operating characteristic curves were used to seek the best prediction model for clinical outcomes from all combinations of possible predictors. RESULTS: When considered individually, only higher general psychopathology levels (P = .023) was associated with the unfavourable outcomes. Prediction models suggest that general psychopathology and functioning are predictive of unfavourable outcomes. CONCLUSION: The predictive performance of the resulting models was modest and further research is needed. Nonetheless, when designing early intervention centres aiming to support individuals in the early phases of a mental disorder, the proper assessment of general psychopathology and functioning should be considered in order to inform interventions and length of care provided.
Authors: Michelle A Worthington; Jean Addington; Carrie E Bearden; Kristin S Cadenhead; Barbara A Cornblatt; Matcheri Keshavan; Daniel H Mathalon; Thomas H McGlashan; Diana O Perkins; William S Stone; Ming T Tsuang; Elaine F Walker; Scott W Woods; Tyrone D Cannon Journal: Schizophr Bull Date: 2022-03-01 Impact factor: 7.348