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  Vol. 65 No. 1, January 2008 TABLE OF CONTENTS
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Prediction of Psychosis in Youth at High Clinical Risk

A Multisite Longitudinal Study in North America

Tyrone D. Cannon, PhD; Kristin Cadenhead, MD; Barbara Cornblatt, PhD; Scott W. Woods, MD; Jean Addington, PhD; Elaine Walker, PhD; Larry J. Seidman, PhD; Diana Perkins, MD; Ming Tsuang, MD; Thomas McGlashan, MD; Robert Heinssen, PhD

Arch Gen Psychiatry. 2008;65(1):28-37.

Context  Early detection and prospective evaluation of individuals who will develop schizophrenia or other psychotic disorders are critical to efforts to isolate mechanisms underlying psychosis onset and to the testing of preventive interventions, but existing risk prediction approaches have achieved only modest predictive accuracy.

Objectives  To determine the risk of conversion to psychosis and to evaluate a set of prediction algorithms maximizing positive predictive power in a clinical high-risk sample.

Design, Setting, and Participants  Longitudinal study with a 21/2-year follow-up of 291 prospectively identified treatment-seeking patients meeting Structured Interview for Prodromal Syndromes criteria. The patients were recruited and underwent evaluation across 8 clinical research centers as part of the North American Prodrome Longitudinal Study.

Main Outcome Measure  Time to conversion to a fully psychotic form of mental illness.

Results  The risk of conversion to psychosis was 35%, with a decelerating rate of transition during the 21/2-year follow-up. Five features assessed at baseline contributed uniquely to the prediction of psychosis: a genetic risk for schizophrenia with recent deterioration in functioning, higher levels of unusual thought content, higher levels of suspicion/paranoia, greater social impairment, and a history of substance abuse. Prediction algorithms combining 2 or 3 of these variables resulted in dramatic increases in positive predictive power (ie, 68%-80%) compared with the prodromal criteria alone.

Conclusions  These findings demonstrate that prospective ascertainment of individuals at risk for psychosis is feasible, with a level of predictive accuracy comparable to that in other areas of preventive medicine. They provide a benchmark for the rate and shape of the psychosis risk function against which standardized preventive intervention programs can be compared.


Author Affiliations: Departments of Psychology and Psychiatry and Biobehavioral Sciences, University of California, Los Angeles (Dr Cannon); Departments of Psychiatry, University of California, San Diego (Drs Cadenhead and Tsuang), Zucker Hillside Hospital, Long Island, New York (Dr Cornblatt), Yale University, New Haven, Connecticut (Drs Woods and McGlashan), University of Toronto, Toronto, Ontario, Canada (Dr Addington), Harvard Medical School, Boston, Massachussetts (Drs Seidman and Tsuang), University of North Carolina, Chapel Hill (Dr Perkins); Departments of Psychology and Psychiatry, Emory University, Atlanta, Georgia (Dr Walker); and Schizophrenia Spectrum Disorders Research Program, Division of Adult Translational Research, National Institute of Mental Health, Bethesda, Maryland (Dr Heinssen).



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