TY - JOUR
T1 - Can quantitative EEG measures predict clinical outcome in subjects at Clinical High Risk for psychosis? A prospective multicenter study
AU - Van Tricht, Mirjam J.
AU - Ruhrmann, Stephan
AU - Arns, Martijn
AU - Müller, Ralf
AU - Bodatsch, Mitja
AU - Velthorst, Eva
AU - Koelman, Johannes H.T.M.
AU - Bour, Lo J.
AU - Zurek, Katharina
AU - Schultze-Lutter, Frauke
AU - Klosterkötter, Joachim
AU - Linszen, Don H.
AU - De Haan, Lieuwe
AU - Brockhaus-Dumke, Anke
AU - Nieman, Dorien H.
N1 - Funding Information:
This study was supported by a grant for the Dutch Prediction of Psychosis Study from ZON-MW (ZorgOnderzoek Nederland/NWO-Medische Wetenschappen , project # 2630.0001 ) and a grant from the European Commission in Brussels, Belgium , for the European Prediction of Psychosis study (grant QLGU-CT-2001-01081 ). The funding sources had no influence on the design or conduct of the study; collection, management, analysis, or interpretation of the data; or preparation, review, or approval of the manuscript.
PY - 2014/3
Y1 - 2014/3
N2 - 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.
AB - 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.
KW - Clinical high risk
KW - Psychosis prediction
KW - QEEG
UR - https://www.scopus.com/pages/publications/84895819886
U2 - 10.1016/j.schres.2014.01.019
DO - 10.1016/j.schres.2014.01.019
M3 - Article
C2 - 24508483
AN - SCOPUS:84895819886
SN - 0920-9964
VL - 153
SP - 42
EP - 47
JO - Schizophrenia Research
JF - Schizophrenia Research
IS - 1-3
ER -