IMR Press / JIN / Volume 17 / Issue 3 / DOI: 10.31083/JIN-170054
Open Access Research article
Neurobiological parameters in quantitative prediction of treatment outcome in schizophrenic patients
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1 Laboratory of Neurophysiology, Mental Health Research Center, Moscow, Russia
2 Laboratory of Neuroimmunology, Mental Health Research Center, Moscow, Russia
3 Department of Computational Mathematics, Faculty of Mechanics and Mathematics, M.V. Lomonosov Moscow State University, Moscow, Russia
4 Department of Brain Research, Research Center of Neurology, Moscow, Russia
5 Department of Endogenous Mental Disorders and Affective Conditions, Mental Health Research Center, Moscow, Russia
J. Integr. Neurosci. 2018 , 17(3), 221–228; https://doi.org/10.31083/JIN-170054
Submitted: 14 August 2017 | Accepted: 13 October 2017 | Published: 15 August 2018
Abstract

The aim of this study was to reveal the set of neurobiological parameters informative for individual quantitative prediction of therapeutic response in schizophrenic subjects. Correlation and regression analyses of quantitative Positive And Negative Syndromes Scale clinical scores, together with background electroencephalographic spectral power values and four immunological parameters: enzymatic activity of leukocyte elastase and of alpha-1 proteinase inhibitor, as well as serum levels of autoantibodies to common myelin protein and to nerve growth factor, were performed for 50 female subjects with hallucinatory-delusional disorders such as attack-like paranoid schizophrenia. Background neurobiological data obtained before the beginning of a syndrome based treatment course were matched with Positive And Negative Syndromes Scale clinical scores of the same subjects after a treatment course to the stage of establishment of remission. The multiple linear regression equations were created which were described by only three or four (from an initial 80) background electroencephalographic parameters and one of four immunological parameters. These mathematical models allowed prediction of 65-76% of Positive and Negative Syndromes Scale score variance after a treatment course. The data obtained may be useful for elaboration of methods for individual quantitative prediction of treatment outcome for schizophrenic subjects.

Keywords
Quantitative electroencephalography
immunological parameters
paranoid schizophrenia
hallucinatory-delusional disorders
mathematical modeling
prediction of treatment outcome
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