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Detailed clinical phenotyping and generalisability in prognostic models of functioning in at-risk populations

Research output: Contribution to journalArticlepeer-review

Marlene Rosen, Linda T. Betz, Natalie Kaiser, Nora Penzel, Dominic Dwyer, Theresa K. Lichtenstein, Frauke Schultze-Lutter, Lana Kambeitz-Ilankovic, Alessandro Bertolino, Stefan Borgwardt, Paolo Brambilla, Rebekka Lencer, Eva Meisenzahl, Christos Pantelis, Raimo K.R. Salokangas, Rachel Upthegrove, Stephen Wood, Stephan Ruhrmann, Nikolaos Koutsouleris, Joseph Kambeitz

Original languageEnglish
Pages (from-to)318-321
Number of pages4
JournalBritish Journal of Psychiatry
Volume220
Issue number6
Early online date6 Oct 2021
DOIs
E-pub ahead of print6 Oct 2021
Published16 Jun 2022

Bibliographical note

Funding Information: PRONIA is a Collaboration Project funded by the European Union under the 7th Framework Programme (grant agreement no. 602152). M.R. is supported by a grant from the Koeln Fortune Program/Faculty of Medicine, University of Cologne. R.U. reports grants from the Medical Research Council, grants from the National Institute for Health Research, and personal fees from Sunovion, outside the submitted work. J.K. and N.Ko. received honoraria for talks presented at education meetings organised by Otsuka/Lundbeck. C.P. was supported by a National Health and Medical Research Council (NHMRC) Senior Principal Research Fellowship (1105825) and an NHMRC L3 Investigator Grant (1196508), has received honoraria for talks at educational meetings and has served on an advisory board for Lundbeck, Australia Pty Ltd. Publisher Copyright: Copyright © The Author(s), 2021. Published by Cambridge University Press on behalf of the Royal College of Psychiatrists.

King's Authors

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.

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