Context: Early detection and prospective evaluation of in-dividuals who will develop schizophrenia or other psy-chotic disorders are critical to efforts to isolate mecha-nisms underlying psychosis onset and to the testing of preventive interventions, but existing risk prediction ap-proaches have achieved only modest predictive accuracy. Objectives: To determine the risk of conversion to psy-chosis and to evaluate a set of prediction algorithms maxi-mizingpositivepredictivepowerinaclinicalhigh-risksample. Design, Setting, and Participants: Longitudinal study with a 2 1 ⁄2-year follow-up of 291 prospectively identi-fied treatment-seeking patients meeting Structured In-terview for Prodromal Syndromes criteria. The patients were recruited and underwent evaluation across 8 clini-cal research centers as part of the North American Pro-drome 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 2 1 ⁄2-year follow-up. Five features assessed at baseline con-tributed uniquely to the prediction of psychosis: a ge-netic risk for schizophrenia with recent deterioration in functioning, higher levels of unusual thought content, higher levels of suspicion/paranoia, greater social im-pairment, 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 prospec-tive 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 pro-vide a benchmark for the rate and shape of the psycho-sis risk function against which standardized preventive intervention programs can be compared.
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