Efficacy of Using Cognitive Status in Predicting Psychosis: A 7-Year Follow-Up

Abstract

Despite extensive early detection research in schizophrenic psychoses, methods for identifying at-risk individuals and predicting their transition to psychosis are still unreliable. Moreover, there are sparse data on long-term prediction. We therefore investigated long-term psychosis transition in individuals with an At Risk Mental State (ARMS) and examined the relative efficacy of clinical and neuropsychological status in optimizing the prediction of transition. Sixty-four individuals with ARMS for psychosis were identified from all referrals to our early detection clinic between March 1, 2000 and February 29, 2004. Fifty-three (83%) were followed up for up to 7 (mean 5.4) years. Twenty-one of the 53 staying in follow-up developed psychosis, corresponding to a transition rate of .34 (Kaplan-Meier estimates). Median time to transition was 10 months (range <1-55). Six of all transitions (29%) occurred only after 12 months from referral. Best transition predictors within this population were selected attenuated psychotic symptoms (suspiciousness), negative symptoms (anhedonia/asociality), and cognitive deficits (reduced speed of information processing). With these predictors in an integrated model for predicting transition to psychosis, the overall predictive accuracy was 80.9% with a sensitivity of 83.3% and a specificity of 79.3%. Follow-up of ARMS subjects should exceed the usual 12 months. Prediction of transitions could be improved by a stronger weighting of certain early symptoms and by introducing neurocognitive tests into a stepwise risk assessment. Confirmatory research will hopefully further improve risk algorithm, including psychopathology and neuropsychological performance, for clinical application in early detection clinics.