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  Using combined environmental-clinical classification models to predict role functioning outcome in clinical high-risk states for psychosis and recent-onset depression

Antonucci, L. A., Penzel, N., Sanfelici, R., Pigoni, A., Kambeitz-Ilankovic, L., Dwyer, D., et al. (2022). Using combined environmental-clinical classification models to predict role functioning outcome in clinical high-risk states for psychosis and recent-onset depression. BRITISH JOURNAL OF PSYCHIATRY, PII S0007125022000162. doi:10.1192/bjp.2022.16.

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Antonucci, Linda A., Author
Penzel, Nora, Author
Sanfelici, Rachele, Author
Pigoni, Alessandro, Author
Kambeitz-Ilankovic, Lana, Author
Dwyer, Dominic, Author
Ruef, Anne, Author
Sen Dong, Mark, Author
Ozturk, Omer Faruk1, Author           
Chisholm, Katharine, Author
Haidl, Theresa, Author
Rosen, Marlene, Author
Ferro, Adele, Author
Pergola, Giulio, Author
Andriola, Ileana, Author
Blasi, Giuseppe, Author
Ruhrmann, Stephan, Author
Schultze-Lutter, Frauke, Author
Falkai, Peter, Author
Kambeitz, Joseph, Author
Lencer, Rebekka, AuthorDannlowski, Udo, AuthorUpthegrove, Rachel, AuthorSalokangas, Raimo K. R., AuthorPantelis, Christos, AuthorMeisenzahl, Eva, AuthorWood, Stephen J., AuthorBrambilla, Paolo, AuthorBorgwardt, Stefan, AuthorBertolino, Alessandro, AuthorKoutsouleris, Nikolaos, Author more..
Affiliations:
1IMPRS Translational Psychiatry, Max Planck Institute of Psychiatry, Max Planck Society, ou_3318616              

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 Abstract: Background Clinical high-risk states for psychosis (CHR) are associated with functional impairments and depressive disorders. A previous PRONIA study predicted social functioning in CHR and recent-onset depression (ROD) based on structural magnetic resonance imaging (sMRI) and clinical data. However, the combination of these domains did not lead to accurate role functioning prediction, calling for the investigation of additional risk dimensions. Role functioning may be more strongly associated with environmental adverse events than social functioning. Aims We aimed to predict role functioning in CHR, ROD and transdiagnostically, by adding environmental adverse events-related variables to clinical and sMRI data domains within the PRONIA sample. Method Baseline clinical, environmental and sMRI data collected in 92 CHR and 95 ROD samples were trained to predict lower versus higher follow-up role functioning, using support vector classification and mixed k-fold/leave-site-out cross-validation. We built separate predictions for each domain, created multimodal predictions and validated them in independent cohorts (74 CHR, 66 ROD). Results Models combining clinical and environmental data predicted role outcome in discovery and replication samples of CHR (balanced accuracies: 65.4% and 67.7%, respectively), ROD (balanced accuracies: 58.9% and 62.5%, respectively), and transdiagnostically (balanced accuracies: 62.4% and 68.2%, respectively). The most reliable environmental features for role outcome prediction were adult environmental adjustment, childhood trauma in CHR and childhood environmental adjustment in ROD. Conclusions Findings support the hypothesis that environmental variables inform role outcome prediction, highlight the existence of both transdiagnostic and syndrome-specific predictive environmental adverse events, and emphasise the importance of implementing real-world models by measuring multiple risk dimensions.

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 Dates: 2022-02
 Publication Status: Published online
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 Identifiers: ISI: 000756230200001
DOI: 10.1192/bjp.2022.16
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Title: BRITISH JOURNAL OF PSYCHIATRY
Source Genre: Journal
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Pages: - Volume / Issue: - Sequence Number: PII S0007125022000162 Start / End Page: - Identifier: ISSN: 0007-1250