Can quantitative EEG measures predict clinical outcome in subjects at Clinical High Risk for psychosis? A prospective multicenter study

article i nfo Background: Prediction studies in subjects at Clinical High Risk (CHR) for psychosis are hampered by a high proportion of uncertain outcomes. We therefore investigated whether quantitative EEG (QEEG) parameters can contribute to an improved identification of CHR subjects with a later conversion to psychosis. Methods: This investigation was a project within the European Prediction of Psychosis Study (EPOS), a prospec- tive multicenter, naturalistic field study with an 18-month follow-up period. QEEG spectral power and alpha peak frequencies (APF) were determined in 113 CHR subjects. The primary outcome measure was conversion to psychosis. Results: Cox regression yielded a model including frontal theta (HR = 1.82; (95% CI 1.00-3.32)) and delta (HR = 2.60; (95% CI 1.30-5.20)) power, and occipital-parietal APF (HR = .52; (95% CI .35-.80)) as predictors ofconversionto psychosis.The resultingequation enabledthe developmentof a prognosticindexwith three risk classes (hazard rate 0.057 to 0.81). Conclusions: Power in theta and delta ranges and APF contribute to the short-term prediction of psychosis and enable a further stratification of risk in CHR samples. Combined with (other) clinical ratings, EEG parameters may therefore be a useful tool for individualized risk estimation and, consequently, targeted prevention.