Personalised prediction of functional outcomes is a promising approach for targeted early intervention in psychiatry. However, generalisability and resource efficiency of such prognostic models represent challenges. In the PRONIA study (German Clinical Trials Register: DRKS00005042), we demonstrate excellent generalisability of prognostic models in individuals at clinical high-risk for psychosis or with recent-onset depression, and substantial contributions of detailed clinical phenotyping, particularly to the prediction of role functioning. These results indicate that it is possible that functioning prediction models based only on clinical data could be effectively applied in diverse healthcare settings, so that neuroimaging data may not be needed at early assessment stages.
Detailed clinical phenotyping and generalisability in prognostic models of functioning in at-risk populations / M. Rosen, L.T. Betz, N. Kaiser, N. Penzel, D. Dwyer, T.K. Lichtenstein, F. Schultze-Lutter, L. Kambeitz-Ilankovic, A. Bertolino, S. Borgwardt, P. Brambilla, R. Lencer, E. Meisenzahl, C. Pantelis, R.K.R. Salokangas, R. Upthegrove, S. Wood, S. Ruhrmann, N. Koutsouleris, J. Kambeitz. - In: BRITISH JOURNAL OF PSYCHIATRY. - ISSN 0007-1250. - 220:6(2022 Jun 16), pp. PII S0007125021001410.318-PII S0007125021001410.321. [10.1192/bjp.2021.141]
Detailed clinical phenotyping and generalisability in prognostic models of functioning in at-risk populations
P. Brambilla;
2022
Abstract
Personalised prediction of functional outcomes is a promising approach for targeted early intervention in psychiatry. However, generalisability and resource efficiency of such prognostic models represent challenges. In the PRONIA study (German Clinical Trials Register: DRKS00005042), we demonstrate excellent generalisability of prognostic models in individuals at clinical high-risk for psychosis or with recent-onset depression, and substantial contributions of detailed clinical phenotyping, particularly to the prediction of role functioning. These results indicate that it is possible that functioning prediction models based only on clinical data could be effectively applied in diverse healthcare settings, so that neuroimaging data may not be needed at early assessment stages.File | Dimensione | Formato | |
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