Identification of distinct clinical profiles and trajectories in individuals at high risk of developing psychosis: A latent profile analysis of the north American prodrome longitudinal study consortium‐3 dataset

Author:

Bergé Daniel1ORCID,Carter Cameron S.2,Smucny Jason2ORCID

Affiliation:

1. Hospital del Mar Research Institute; Centro de Investigación Biomédica en Red, Área de Salud Mental (CIBERSAM) Pompeu Fabra University Barcelona Spain

2. Department of Psychiatry University of California Davis California USA

Abstract

AbstractAimPeople at clinical high risk (CHR) for psychosis are a heterogeneous population in regard to clinical presentation and outcome. It is unclear, however, if their baseline clinical characteristics can be used to construct orthogonal subgroups that differ in their clinical trajectory to provide early identification of individuals in need of tailored interventions.MethodsWe used latent profile analysis (LPA) to determine the number of distinct clinical profiles within the CHR population using the NAPLS‐3 dataset, focusing on the clinical features incorporated in the NAPLS psychosis risk calculator (including age, unusual thought content and suspiciousness, processing speed, verbal learning and memory function, social functioning decline, life events, childhood trauma, and family history of psychosis). We then conducted a between‐profile comparisons of clinical trajectories based on psychotic and depressive symptoms as well as substance use disorder (SUD) related features over time.ResultsTwo distinct profiles emerged. One profile, comprising approximately 25% of the sample, was significantly older, displayed better cognitive performance, experienced more types of traumatic and undesirable life events, exhibited a greater decline in functioning in the past year, and was more likely to have relatives with psychosis. This group showed worse positive symptoms and SUD‐related features over time, although groups did not differ in the proportion of individuals who developed psychosis.ConclusionsLPA results suggest CHRs can be segregated into two profiles with different clinical trajectories. Characterizing individuals within these clinical profiles may help understand the divergent outcomes of this population and ultimately facilitate the development of specialized interventions.

Funder

National Institutes of Health

Publisher

Wiley

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