The concept of indicated prevention has proliferated in psychiatry. Accumulating evidence suggests that it may indeed be possible to prevent or delay the onset of a First Episode of Psychosis (FEP) though adequate interventions in individuals deemed at Clinical High Risk (CHR) for such an event. However, a challenge undermining these efforts is the relatively poor predictive accuracy of clinical assessments used in practice for CHR individuals. to improve prediction by combining different types of assessments.

To improve prediction of clinical course of disease by combining biological and clinical types of assessment.

To present a probabilistic prediction model containing clinical and biological data for the transition to first episode psychosis.

Using data from published studies, and employing predictive models based on the odds ratio form of Bayes’ rule, we simulated scenarios where clinical interview, neurocognitive testing, structural magnetic resonance imaging (MRI) and electrophysiology are part of the initial assessment process of a CHR individual (Extended Diagnostic Approach).

Our findings indicate that for most at-risk patients, at least three types of assessments are necessary to arrive at a clinically meaningful differentiation into high- intermediate-, and low-risk groups. In particular, patients with equivocal results in the initial assessments require additional diagnostic testing to produce an accurate risk profile forming part of the comprehensive initial assessment.

The findings may inform future research into reliable identification and personalized therapeutic targeting of CHR patients, to prevent transition to full-blown psychosis and to inform decision in intervention.