Combining Clinical With Cognitive or Magnetic Resonance Imaging Data for Predicting Transition to Psychosis in Ultra High-Risk Patients: Data From the PACE 400 Cohort

Simon Hartmann, Micah Cearns, Christos Pantelis, Dominic Dwyer, Blake Cavve, Enda Byrne, Isabelle Scott, Hok Pan Yuen, Caroline Gao, Kelly Allott, Ashleigh Lin, Stephen J. Wood, Johanna T.W. Wigman, G. Paul Amminger, Patrick D. McGorry, Alison R. Yung, Barnaby Nelson, Scott R. Clark

Research output: Contribution to journalArticlepeer-review

Abstract

Background: Multimodal modeling that combines biological and clinical data shows promise in predicting transition to psychosis in individuals who are at ultra-high risk. Individuals who transition to psychosis are known to have deficits at baseline in cognitive function and reductions in gray matter volume in multiple brain regions identified by magnetic resonance imaging. Methods: In this study, we used Cox proportional hazards regression models to assess the additive predictive value of each modality—cognition, cortical structure information, and the neuroanatomical measure of brain age gap—to a previously developed clinical model using functioning and duration of symptoms prior to service entry as predictors in the Personal Assessment and Crisis Evaluation (PACE) 400 cohort. The PACE 400 study is a well-characterized cohort of Australian youths who were identified as ultra-high risk of transitioning to psychosis using the Comprehensive Assessment of At Risk Mental States (CAARMS) and followed for up to 18 years; it contains clinical data (from N = 416 participants), cognitive data (n = 213), and magnetic resonance imaging cortical parameters extracted using FreeSurfer (n = 231). Results: The results showed that neuroimaging, brain age gap, and cognition added marginal predictive information to the previously developed clinical model (fraction of new information: neuroimaging 0%–12%, brain age gap 7%, cognition 0%–16%). Conclusions: In summary, adding a second modality to a clinical risk model predicting the onset of a psychotic disorder in the PACE 400 cohort showed little improvement in the fit of the model for long-term prediction of transition to psychosis.

Original languageEnglish
Pages (from-to)417-428
Number of pages12
JournalBiological Psychiatry: Cognitive Neuroscience and Neuroimaging
Volume9
Issue number4
Early online date5 Apr 2024
DOIs
Publication statusPublished - Apr 2024

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