Psychosis Prediction: Stratification of Risk Estimation With Information-Processing and Premorbid Functioning Variables

Background: The period preceding the first psychotic episode is regarded as a promising period for intervention. We aimed to develop an optimized prediction model of a first psychosis, considering different sources of information. The outcome of this model may be used for individualized risk estimation. Methods: Sixty-one subjects clinically at high risk (CHR), participating in the Dutch Prediction of Psychosis Study, were assessed at baseline with instruments yielding data on neuropsychology, symptomatology, environmental factors, premorbid adjustment, and neurophysiology. The follow-up period was 36 months. Results: At 36 months, 18 partici-pants (29.5%) had made a transition to psychosis. Premorbid adjustment (P =.001, hazard ratio [HR] = 2.13, 95 % CI = 1.39/3.28) and parietal P300 amplitude (P =.004, HR = 1.27, 95 % CI = 1.08/1.45) remained as predictors in the Cox pro