title: Towards indicated prevention of psychosis: using probabilistic assessments of transition risk in psychosis prodrome.
abstract: The concept of indicated prevention has proliferated in psychiatry, and accumulating evidence suggests that it may indeed be possible to prevent or delay the onset of a first episode of psychosis though adequate interventions in individuals deemed at clinical high risk (CHR) for such an event. One challenge undermining these efforts is the relatively poor predictive accuracy of clinical assessments used in practice for CHR individuals, often leading to diagnostic and therapeutic uncertainty reflected in clinical guidelines promoting a 'watch and wait' approach to CHR patients. 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 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 of these 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.
authors.affiliation: School of Medicine, Discipline of Psychiatry, Royal Adelaide Hospital, University of Adelaide, 4th Floor, Eleanor Harrald Building, 5005, Adelaide, SA, Australia.
authors.forename: Scott Richard
authors.initials: SR
authors.lastname: Clark
authors.forename: Klaus Oliver
authors.initials: KO
authors.lastname: Schubert
authors.forename: Bernhard Theodor
authors.initials: BT
authors.lastname: Baune
mesh_terms: D001499:Bayes Theorem; D016206:Databases, Bibliographic / Q000706:statistics & numerical data; D018450:Disease Progression; D042241:Early Diagnosis; D006801:Humans; D011237:Predictive Value of Tests; D062706:Prodromal Symptoms; D011618:Psychotic Disorders / Q000175:diagnosis* / Q000517:prevention & control*; D055502:Secondary Prevention