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

van Tricht, Mirjam J.; Ruhrmann, Stephan; Arns, Martijn; Müller, Ralf; Bodatsch, Mitja; Velthorst, Eva; Koelman, Johannes H. T. M.; Bour, Lo J.; Zurek, Katharina; Schultze-Lutter, Frauke; Klosterkötter, Joachim; Linszen, Don H.; de Haan, Lieuwe; Brockhaus-Dumke, Anke; Nieman, Dorien H. (2014). Can quantitative EEG measures predict clinical outcome in subjects at Clinical High Risk for psychosis? A prospective multicenter study. Schizophrenia Research, 153(1-3), pp. 42-47. Elsevier 10.1016/j.schres.2014.01.019

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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 prospective 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 of conversion to psychosis. The resulting equation enabled the development of a prognostic index with 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.

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