EEG, Seizure Type Combinations Predict Antiseizure Medication Resistance

In idiopathic generalized epilepsy (IGE), numerous clinical and electroencephalogram (EEG) characteristics were found to independently predict antiseizure medication (ASM) resistance, according to study results presented at the 2022 American Academy of Neurology (AAN) Annual Meeting, held from April 2 to April 7 in Seattle, Washington, and virtually from April 24-26, 2022.

Several factors, such as catamenial epilepsy, or the change in seizure frequency with menstrual cycle, have been found to predict ASM resistance in IGE. In order to assess for other predictors, patients with IGE were recruited at 5 centers in the United States and Australia between 2002 and 2018. This case-control study compared clinical and EEG characteristics between patients with ASM-resistant IGE (n=118) and ASM-responsive IGE (n=114).

This study confirmed the association of catamenial epilepsy with ASM resistance (odds ratio [OR], 3.53; 95% CI, 1.32-10.41).

In addition, ASM resistance was observed to be associated with EEG-detected features of abundant generalized spike-wave (GSW) discharges in sleep (OR, 7.21; 95% CI, 1.50-54.07), presence of generalized polyspike trains (OR, 5.49; 95% CI, 1.27-38.69), and frequent increased GSW discharges in sleep (OR, 3.43; 95% CI, 1.12-11.36).

The combinations of specific seizure types of absence, myoclonic, and generalized tonic-clonic seizures (OR, 7.06; 95% CI, 2.55-20.96) and of absence and generalized tonic-clonic seizures (OR, 4.45; 95% CI, 1.84-11.34) were also predictors of ASM resistance.

The final multivariate model comprising catamenial epilepsy, 3 EEG characteristics, and 2 seizure type combinations had an area under the receiving operating characteristic curve of 0.80 for predicting ASM in IGE.

This study was limited by its small sample size. These findings should be confirmed in a larger, independent cohort.

These data indicated that multiple clinical and EEG characteristics could independently predict ASM resistance in IGE. Considering EEG findings and asking patients about the specific seizure type combinations they experience may allow for physicians to better predict and manage drug resistance in IGE.

“Obtaining prolonged EEG studies to record the burden of GSW in sleep and assessing for the presence of GPT may provide additional predictive value,” the researchers concluded.

Reference

Kamitaki B, Lin H, Heiman G, Choi H. Clinical and EEG factors associated with antiseizure medication resistance in idiopathic generalized epilepsy. Presented at: the 2022 AAN Annual Meeting; April 2-7, 2022; Seattle, Washington; April 24-26, 2022; Virtual Meeting. Abstract S24.008.