Network-based biomarkers in background electroencephalography in childhood epilepsies – A scoping review and narrative synthesis

Abstract

Background: Brain network analysis is an emerging field of research that could lead to the development, testing and validation of novel biomarkers for epilepsy. This could shorten the diagnostic uncertainty period, improve treatment, decrease seizure risk and lead to better management. This scoping review summarises the current state of electroencephalogram (EEG)- based network abnormalities for childhood epilepsies. The review assesses the overall robustness, potential generalizability, strengths, and limitations of the methodological frameworks of the identified research studies. Methods: PRISMA guidelines for Scoping Reviews and the PICO framework was used to guide this review. Studies that evaluated candidate network-based features from EEG in children were retrieved from four international indexing databases (Cochrane Central / Embase / Medline / PsycINFO). Each selected study design, intervention characteristics, methodological design, potential limitations, and key findings were analysed. Results: Of 2,959 studies retrieved nine were included. Studies used a group-level based comparison (e.g. based on a statistical test) or a classification-based method (e.g. based on a statistical model, such as a decision tree). A common limitation was the small sample-sizes (limiting further subgroup or confounder analysis) and the overall heterogeneity in epilepsy syndromes and age groups. Conclusion: The heterogeneity of included studies (e.g. study design, statistical framework, outcome metrics) highlights the need for future studies to adhere to standardized frameworks (e.g. STARD) in order to develop standardized and robust methodologies. This would enable rigorous comparisons between studies, which is critical in assessing the potential of network-based approaches in developing novel biomarkers for childhood epilepsies.