4.7 Article

Predicting the antiepileptic drug response by brain connectivity in newly diagnosed focal epilepsy

Journal

JOURNAL OF NEUROLOGY
Volume 267, Issue 4, Pages 1179-1187

Publisher

SPRINGER HEIDELBERG
DOI: 10.1007/s00415-020-09697-4

Keywords

Epilepsy; Connectivity; Anticonvulsants

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Objective Growing evidence has suggested that epilepsy is a disease with alterations in brain connectivity. The aim of this study was to investigate whether the changes in brain connectivity can predict the response to an antiepileptic drug (AED) in patients with a newly diagnosed focal epilepsy of unknown etiology. Methods This observational study was independently performed at two tertiary hospitals (Group A and B). Thirty-eight patients with newly diagnosed focal epilepsy of unknown etiology were enrolled in Group A and 46 patients in Group B. We divided these patients into two groups according to their seizure control after AED treatment: AED good and poor responders. We defined the AED good responders as those in whom had seizure free for at least the last 6 months while AED poor responders who were not. All of the subjects underwent diffusion tensor imaging, and graph theoretical analysis was applied to reveal the brain connectivity. We investigated the difference in the clinical characteristics and network measurements between the two groups. Results Of the network measures, the assortativity coefficient in the AED good responders was significantly higher than that in the AED poor responders in both Groups A and B (- 0.0239 vs. - 0.0473, p = 0.0110 in Group A; 0.0173 vs. - 0.0180, p = 0.0024 in Group B). The Kaplan-Meier survival analysis revealed that the time to failure to retain the first AED was significantly longer in the patients with assortative networks (assortativity coefficient > 0) than in those with disassortative networks (assortativity coefficient < 0) in Group B. Conclusion We demonstrated that the assortativity coefficient differed between patients with newly diagnosed focal epilepsy of unknown etiology according to their AED responses, which suggests that the changes in brain connectivity could be a biomarker for predicting the responses to AED.

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