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.
English
Clinical high-risk for psychosis; depression; personalized prediction; psychosocial functioning; translational psychiatry;
Settore MED/25 - Psichiatria
Articolo
Esperti anonimi
Pubblicazione scientifica
   Personalised Prognostic Tools for Early Psychosis Management
   PRONIA
   EUROPEAN COMMISSION
   FP7
   602152
16-giu-2022
6-ott-2022
Cambridge University Press
220
6
PII S0007125021001410
318
321
4
Pubblicato
Periodico con rilevanza internazionale
crossref
Aderisco
info:eu-repo/semantics/article
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]
reserved
Prodotti della ricerca::01 - Articolo su periodico
20
262
Article (author)
si
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
File in questo prodotto:
File Dimensione Formato  
detailed-clinical-phenotyping-and-generalisability-in-prognostic-models-of-functioning-in-at-risk-populations.pdf

accesso riservato

Tipologia: Publisher's version/PDF
Dimensione 323.89 kB
Formato Adobe PDF
323.89 kB Adobe PDF   Visualizza/Apri   Richiedi una copia
Pubblicazioni consigliate

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/912347
Citazioni
  • ???jsp.display-item.citation.pmc??? 0
  • Scopus 0
  • ???jsp.display-item.citation.isi??? 0
social impact