Dynamic Prediction of Outcomes for Youth at Clinical High Risk for Psychosis: A Joint Modeling Approach.

ABSTRACT:

Importance

Leveraging the dynamic nature of clinical variables in the clinical high risk for psychosis (CHR-P) population has the potential to significantly improve the performance of outcome prediction models.

Objective

To improve performance of prediction models and elucidate dynamic clinical profiles using joint modeling to predict conversion to psychosis and symptom remission.

Design, setting, and participants

Data were collected as part of the third wave of the North American Prodrome Longitudinal Study (NAPLS 3), which is a 9-site prospective longitudinal study. Participants were individuals aged 12 to 30 years who met criteria for a psychosis-risk syndrome. Clinical, neurocognitive, and demographic variables were collected at baseline and at multiple follow-up

SUBMITTER: Worthington MA 

PROVIDER: S-EPMC10398543 | biostudies-literature | 2023 Oct

REPOSITORIES: biostudies-literature