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. 2021 Jun;15(3):642-651.
doi: 10.1111/eip.13002. Epub 2020 Jun 17.

Prediction of clinical outcomes beyond psychosis in the ultra-high risk for psychosis population

Andrea Polari  1 , Hok Pan Yuen  2   3 , Paul Amminger  2   3 , Gregor Berger  4 , Eric Chen  5 , Lieuwe deHaan  6 , Jessica Hartmann  2   3 , Connie Markulev  2   3 , Patrick McGorry  2   3 , Dorien Nieman  7 , Merete Nordentoft  8 , Anita Riecher-Rössler  9 , Stefan Smesny  10 , John Stratford  1 , Swapna Verma  11 , Alison Yung  2   3 , Suzie Lavoie  2   3 , Barnaby Nelson  2   3
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Prediction of clinical outcomes beyond psychosis in the ultra-high risk for psychosis population

Andrea Polari et al. Early Interv Psychiatry. 2021 Jun.

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.

Keywords: BPD; UHR; non-psychotic outcomes; outcomes; prediction; transition.

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References

REFERENCES

    1. Addington, J., Liu, L., Buchy, L., Cadenhead, K. S., Cannon, T. D., Cornblatt, B. A., … McGlashan, T. H. (2015). North American Prodrome Longitudinal Study (NAPLS 2): The prodromal symptoms. The Journal of Nervous and Mental Disease, 203(5), 328-335. https://doi.org/10.1097/NMD.0000000000000290
    1. Allswede, D. M., Addington, J., Bearden, C. E., Cadenhead, K. S., Cornblatt, B. A., Mathalon, D. H., … Cannon, T. D. (2020). Characterizing covariant trajectories of individuals at clinical high risk for psychosis across symptomatic and functional domains. The American Journal of Psychiatry, 177(2), 164-171. https://doi.org/10.1176/appi.ajp.2019.18111290
    1. Amminger, G. P., Leicester, S., Yung, A. R., Phillips, L. J., Berger, G. E., Francey, S. M., … McGorry, P. D. (2006). Early-onset of symptoms predicts conversion to non-affective psychosis in ultra-high risk individuals. Schizophrenia Research, 84(1), 67-76. https://doi.org/10.1016/j.schres.2006.02.018
    1. Andreasen, N. C. (1984). Scale for assessing negative symptoms (SANS). Iowa, IA: University of Iowa.
    1. Beck, K., Andreou, C., Studerus, E., Heitz, U., Ittig, S., Leanza, L., & Riecher-Rossler, A. (2019). Clinical and functional long-term outcome of patients at clinical high risk (CHR) for psychosis without transition to psychosis: A systematic review. Schizophrenia Research, 210, 39-47. https://doi.org/10.1016/j.schres.2018.12.047

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