Abstract
BackgroundThe vast majority of studies of neuropsychological (NP) functioning in Clinical High Risk (CHR) cohorts have examined group averages, possibly concealing a range of subgroups ranging from very impaired to high functioning. Our objective was to assess NP profiles and to explore associations with conversion to psychosis, functional and diagnostic outcome.MethodsData were acquired from 324 participants (mean age 18.4) in the first phase of the North American Prodrome Longitudinal Study (NAPLS-1), a multi-site consortium following individuals for up to 2½ years. We applied Ward’s method for hierarchical clustering data to 8 baseline neurocognitive measures, in 166 CHR individuals, 49 non-CHR youth with a family history of psychosis, and 109 healthy controls. We tested whether cluster membership was associated with conversion to psychosis, social and role functioning, and follow-up diagnosis. Analyses were repeated after data were clustered based on independently developed clinical decision rules.ResultsFour neurocognitive clusters were identified: Significantly Impaired (n=33); Mildly Impaired (n=82); Normal (n=145) and High (n=64). The Significantly Impaired subgroup demonstrated the largest deviations on processing speed and memory tasks and had a conversion rate of 58%, a 40% chance of developing a schizophrenia spectrum diagnosis (compared to 24.4% in the Mildly Impaired, and 10.3% in the other two groups combined), and significantly worse functioning at baseline and 12-months. Data clustered using clinical decision rules yielded similar results, pointing to high convergent validity.DiscussionDespite extensive neuropsychological investigations within CHR cohorts, this is one of the first studies to investigate NP clustering profiles as a contributor to heterogeneity in outcome. Our results indicate that the four NP profiles vary substantially in their outcome, underscoring the relevance of cognitive functioning in the prediction of illness progression. Our findings tentatively suggest that individualized cognitive profiling should be explored in clinical settings.
Highlights
Neurocognitive dysfunction is a central feature of schizophrenia (Heinrichs, 2005; Kahn and Keefe, 2013; Nuechterlein et al, 2012; Schulz and Murray, 2016) and, to a lesser extent, other psychoses (Lewandowski et al, 2011)
Using Chi-square analyses we explored whether the clusters indicating greater neurocognitive impairment were associated with higher rates of schizophrenia-spectrum diagnoses
We labeled them according to their level of performance: Significantly Impaired (SI; n=33); Mildly Impaired (MI; n=82); Normal (N; n=145) and High Normal (HN; n=64)
Summary
Neurocognitive dysfunction is a central feature of schizophrenia (Heinrichs, 2005; Kahn and Keefe, 2013; Nuechterlein et al, 2012; Schulz and Murray, 2016) and, to a lesser extent, other psychoses (Lewandowski et al, 2011). It is a key determinant of social and role functioning (Green, 1996), (Meyer et al, 2014). We aimed to identify neurocognitive subgroups and to explore associated outcomes
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