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Forecasting Remission From the Psychosis Risk Syndrome With Mismatch Negativity and P300: Potentials and Pitfalls
Holly K Hamilton1, Brian J Roach2, Daniel H Mathalon1
1San Francisco VA Health Care System, University of California San Francisco, San Francisco, California; Department of Psychiatry and Behavioral Sciences, University of California San Francisco, San Francisco, California.
Abstract:
Clinical outcomes vary for individuals at clinical high risk (CHR) for psychosis, ranging from conversion to a psychotic disorder to full remission from the risk syndrome. Given that most CHR individuals do not convert to psychosis, recent research efforts have turned toward identifying specific predictors of CHR remission, a task that is conceptually and empirically dissociable from the identification of predictors of conversion to psychosis, and one that may reveal specific biological characteristics that confer resilience to psychosis and provide further insights into the mechanisms associated with the pathogenesis of schizophrenia and those underlying a transient CHR syndrome. Such biomarkers may ultimately facilitate the development of novel early interventions and support the optimization of individualized care. In this review, we focus on two event-related brain potential measures, mismatch negativity and P300, that have attracted interest as predictors of future psychosis among CHR individuals. We describe several recent studies examining whether mismatch negativity and P300 predict subsequent CHR remission and suggest that intact mismatch negativity and P300 may reflect the integrity of specific neurocognitive processes that confer resilience against the persistence of the CHR syndrome and its associated risk for future transition to psychosis. We also highlight several major methodological concerns associated with these studies that apply to the broader literature examining predictors of CHR remission. Among them is the concern that studies that predict dichotomous remission versus nonremission and/or dichotomous conversion versus nonconversion outcomes potentially confound remission and conversion effects, a phenomenon we demonstrate with a data simulation.
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