PRediction of vagal nerve stimulation EfficaCy In drug-reSistant Epilepsy (PRECISE): prospective study for pre-implantation prediction / study design

0561883 - ÚPT 2023 US eng A - Abstract
Doležalová, I. - Koriťáková, E. - Součková, L. - Chrastina, J. - Chládek, Jan - Štěpánová, R. - Brázdil, M.
PRediction of vagal nerve stimulation EfficaCy In drug-reSistant Epilepsy (PRECISE): prospective study for pre-implantation prediction / study design.
Epilepsia. Wiley. Roč. 63, S2 (2022), s. 229. ISSN 0013-9580. E-ISSN 1528-1167.
[European Epilepsy Congress /14./. 09.07.2022-13.07.2022, Geneva]
R&D Projects: GA MZd(CZ) NV19-04-00343
Research Infrastructure: CZECRIN III - 90128
Institutional support: RVO:68081731
Keywords : drug-resistant epilepsy * vagal nerve stimulation * efficacy prediction * statistical model
OECD category: Neurosciences (including psychophysiology
https://onlinelibrary.wiley.com/doi/10.1111/epi.17388

Background: Vagal nerve stimulation (VNS) can be indicated in patients with drug-resistant epilepsy, who are not eligible for resective epilepsy surgery. In VNS therapy, the responder rate (i.e., percentage of subjects experiencing ≥50% seizure reduction) is ~50%. At the moment, there is no widely-accepted possibility to predict VNS efficacy in a particular patient based on pre-implantation data, which can lead to unnecessary surgery and improper allocation of financial resources. The principal aim of PRediction of vagal nerve stimulation EfficaCy In drug-reSistant Epilepsy (PRECISE) study is to verify the predictability of VNS efficacy by analysis of pre-implantation routine electroencephalogram (EEG). Methods: PRECISE is designed as a prospective multicentric study in which patients indicated to VNS therapy will be recruited. Patients will be classified as predicted responders vs. predicted non-responders using pre-implantation EEG analyses. After the first and second year of the study, the real-life outcome (responder vs. non-responder) will be determined. The real-life outcome and predicted outcome will be compared in terms of accuracy, specificity, and sensitivity. In the meantime, the patients will be managed according to the best clinical practice to obtain the best therapeutic response. The primary endpoint will be the accuracy of the statistical model for prediction of response to VNS therapy in terms of responders and non-responders. The secondary endpoint will be the quantification of differences in EEG power spectra (Relative Mean Power, %) between real-life responders and real-life non-responders to VNS therapy in drug-resistant epilepsy and the sensitivity and specificity of the model. Discussion: PRECISE relies on the results of our previous work, through which we developed a statistical classifier for VNS response (responders vs. non-responders) based on differences in EEG power spectra dynamics (Pre-X-Stim).
Permanent Link: https://hdl.handle.net/11104/0336287