TY - JOUR
T1 - Prediction of clinical outcomes beyond psychosis in the ultra-high risk for psychosis population
AU - Polari, Andrea
AU - Yuen, Hok Pan
AU - Amminger, Paul
AU - Berger, Gregor
AU - Chen, Eric
AU - deHaan, Lieuwe
AU - Hartmann, Jessica
AU - Markulev, Connie
AU - McGorry, Patrick
AU - Nieman, Dorien
AU - Nordentoft, Merete
AU - Riecher-Rössler, Anita
AU - Smesny, Stefan
AU - Stratford, John
AU - Verma, Swapna
AU - Yung, Alison
AU - Lavoie, Suzie
AU - Nelson, Barnaby
N1 - Funding Information: We thank all of the participants and their families. The Neurapro study was supported by the Stanley Medical Research Institute (07TGF‐1102), the NHMRC Australia Program (566529) and the Colonial Foundation. B. N. was supported by an NHMRC Senior Research Fellowship. Funding Information: Colonial Foundation; NHMRC Australia Program, Grant/Award Number: 566529; NHMRC Senior Research Fellowship; Stanley Medical Research Institute, Grant/Award Number: 07TGF‐1102 Funding information Publisher Copyright: © 2020 John Wiley & Sons Australia, Ltd
PY - 2021/6/1
Y1 - 2021/6/1
N2 - 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.
AB - 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.
KW - BPD
KW - UHR
KW - non-psychotic outcomes
KW - outcomes
KW - prediction
KW - transition
UR - http://www.scopus.com/inward/record.url?scp=85105083627&partnerID=8YFLogxK
U2 - https://doi.org/10.1111/eip.13002
DO - https://doi.org/10.1111/eip.13002
M3 - Article
C2 - 32558302
SN - 1751-7885
VL - 15
SP - 642
EP - 651
JO - Early intervention in psychiatry
JF - Early intervention in psychiatry
IS - 3
ER -