Variation in prognosis and treatment outcome in juvenile myoclonic epilepsy: a Biology of Juvenile Myoclonic Epilepsy Consortium proposal for a practical definition and stratified medicine classifications

• Published in: Brain communications Vol. 5; no. 3; p. fcad182
• Main Authors: Rubboli, Guido, Beier, Christoph P, Selmer, Kaja K, Syvertsen, Marte, Shakeshaft, Amy, Collingwood, Amber, Hall, Anna, Andrade, Danielle M, Fong, Choong Yi, Gesche, Joanna, Greenberg, David A, Hamandi, Khalid, Lim, Kheng Seang, Ng, Ching Ching, Orsini, Alessandro, Striano, Pasquale, Thomas, Rhys H, Zarubova, Jana, Richardson, Mark P, Strug, Lisa J, Pal, Deb K
• Format: Journal Article
• Language: English
• Published: US Oxford University Press 01-01-2023
• Subjects: Review; definition; drug resistance; classification; prognosis; juvenile myoclonic epilepsy
• ISSN: 2632-1297; 2632-1297
• DOI: 10.1093/braincomms/fcad182

Abstract
Reliable definitions, classifications and prognostic models are the cornerstones of stratified medicine, but none of the current classifications systems in epilepsy address prognostic or outcome issues. Although heterogeneity is widely acknowledged within epilepsy syndromes, the significance of variation in electroclinical features, comorbidities and treatment response, as they relate to diagnostic and prognostic purposes, has not been explored. In this paper, we aim to provide an evidence-based definition of juvenile myoclonic epilepsy showing that with a predefined and limited set of mandatory features, variation in juvenile myoclonic epilepsy phenotype can be exploited for prognostic purposes. Our study is based on clinical data collected by the Biology of Juvenile Myoclonic Epilepsy Consortium augmented by literature data. We review prognosis research on mortality and seizure remission, predictors of antiseizure medication resistance and selected adverse drug events to valproate, levetiracetam and lamotrigine. Based on our analysis, a simplified set of diagnostic criteria for juvenile myoclonic epilepsy includes the following: (i) myoclonic jerks as mandatory seizure type; (ii) a circadian timing for myoclonia not mandatory for the diagnosis of juvenile myoclonic epilepsy; (iii) age of onset ranging from 6 to 40 years; (iv) generalized EEG abnormalities; and (v) intelligence conforming to population distribution. We find sufficient evidence to propose a predictive model of antiseizure medication resistance that emphasises (i) absence seizures as the strongest stratifying factor with regard to antiseizure medication resistance or seizure freedom for both sexes and (ii) sex as a major stratifying factor, revealing elevated odds of antiseizure medication resistance that correlates to self-report of catamenial and stress-related factors including sleep deprivation. In women, there are reduced odds of antiseizure medication resistance associated with EEG-measured or self-reported photosensitivity. In conclusion, by applying a simplified set of criteria to define phenotypic variations of juvenile myoclonic epilepsy, our paper proposes an evidence-based definition and prognostic stratification of juvenile myoclonic epilepsy. Further studies in existing data sets of individual patient data would be helpful to replicate our findings, and prospective studies in inception cohorts will contribute to validate them in real-world practice for juvenile myoclonic epilepsy management.
Rubboli et al. provide evidence-based diagnostic criteria for juvenile myoclonic epilepsy based on clinical data from the BIOJUME Consortium and literature review. They propose a predictive model showing the prognostic value of absence seizures and female sex in predicting drug resistance and photosensitivity in females in reducing the odds of drug refractoriness.
Graphical Abstract
Graphical Abstract