Latest publications

Combining clinical with cognitive or MRI data for predicting transition to psychosis in ultra-high risk patients: Data from the PACE 400 cohort

December 5, 2023

In this study, we looked at the additive predictive value of adding cognition, cortical structure information, or the neuroanatomical measure of “brain age gap” to a previously developed clinical prediction model for psychosis onset in individuals who are at ultra-high risk of psychosis. We used data from the PACE 400 study which is a well characterised cohort of Australian youth identified as UHR using the Comprehensive Assessment of At Risk Mental States followed for up to 18 years, containing clinical data (from N=416 participants), cognitive data (N=213), and MRI cortical parameters extracted using Freesurfer (N=231).

Our 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%).

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 fit of the model for long term prediction of transition to psychosis.



Primary investigator


  • Isabelle Scott
  • Professor Barnaby Nelson, Ph.D.
  • Professor Pat McGorry, M.D, Ph.D.
  • Professor Stephen Wood, Ph.D.
  • Professor Paul Amminger, Ph.D.
  • Professor Alison Yung, M.D.
  • Assistant Professor Johanna Wardenaar-Wigman, Ph.D.
  • Assoc Prof Scott Clark, Ph.D.
  • Professor Ashleigh Lin, Ph.D.
  • Dominic Dwyer
  • Enda Byrne
  • Blake Cavve
  • Hok Pan Yuen
  • Caroline Gao