Predicting ordinal clinical outcomes in at-risk mental states: a multimodal approach

Clinical outcomes in individuals with at-risk mental states (ARMS) are heterogeneous and extend beyond the simple dichotomy between transition and non-transition to psychosis. While previous studies have primarily focused on predicting the transition to psychosis, few have systematically examined multiple outcome stages, including remission and persistent subthreshold symptoms, using integrated neurobiological markers. This study aimed to identify the predictors of multilevel clinical outcomes in ARMS using a multimodal framework that incorporates clinical, functional, and electrophysiological measures.

Eighty-seven subjects with ARMS were included and followed up, and the clinical outcomes were classified into four ordered categories based on a framework derived from the North American Prodrome Longitudinal Study 2 (NAPLS-2): remission, symptomatic, prodromal progression, and psychotic. Ordinal logistic regression analyses were conducted to identify predictors associated with ordered clinical outcomes using baseline measures as candidate predictors. Fifteen explanatory variables were used, including clinical symptoms, cognitive functioning, and electrophysiological measures [amplitudes and latencies of P300, duration mismatch negativity (dMMN), and frequency MMN (fMMN)].

Reduced baseline dMMN amplitude, greater severity of attenuated positive symptoms indexed by unusual thought content, and poor cognitive functioning associated with daily living, assessed using the Schizophrenia Cognition Rating Scale, were independently associated with worse ordered clinical outcomes.

These findings suggest that future clinical trajectories of ARMS can be predicted by multimodal factors spanning neurophysiological, clinical, and functional domains. Early stratification of individuals at the ARMS stage may contribute to the development of personalized and stage-appropriate intervention strategies tailored to subsequent clinical outcomes.