TY - JOUR
T1 - Clinical and EEG factors associated with antiseizure medication resistance in idiopathic generalized epilepsy
AU - Kamitaki, Brad K.
AU - Janmohamed, Mubeen
AU - Kandula, Padmaja
AU - Elder, Christopher
AU - Mani, Ram
AU - Wong, Stephen
AU - Perucca, Piero
AU - O’Brien, Terence J
AU - Lin, Haiqun
AU - Heiman, Gary A.
AU - Choi, Hyunmi
N1 - Funding Information:
Dr. Janmohamed is funded by an RTP stipend scholarship from Monash University. Dr. Perucca is supported by the National Health and Medical Research Council (APP1163708), the Epilepsy Foundation, the University of Melbourne, Monash University, Brain Australia, and the Weary Dunlop Research Foundation. Dr. O’Brien acknowledges funding from NHMRC Program APP1091593 and Investigator APP1176426 Grants.
Funding Information:
Dr. Perucca has received speaker honoraria or consultancy fees to his institution from Chiesi, Eisai, LivaNova, Novartis, Sun Pharma, Supernus, and UCB Pharma outside the submitted work. He is an associate editor for . Dr. O’Brien acknowledges his institution has received consultancy and research funding from UCB Pharma, Eisai, ES Therapeutics, Zynerba, Praxis Pharmaceuticals, and BioGen. The remaining authors have no conflicts of interest. Epilepsia Open
Publisher Copyright:
© 2021 International League Against Epilepsy
PY - 2022/1
Y1 - 2022/1
N2 - Objective: We sought to determine which combination of clinical and electroencephalography (EEG) characteristics differentiate between an antiseizure medication (ASM)–resistant vs ASM-responsive outcome for patients with idiopathic generalized epilepsy (IGE). Methods: This was a case-control study of ASM-resistant cases and ASM-responsive controls with IGE treated at five epilepsy centers in the United States and Australia between 2002 and 2018. We recorded clinical characteristics and findings from the first available EEG study for each patient. We then compared characteristics of cases vs controls using multivariable logistic regression to develop a predictive model of ASM-resistant IGE. Results: We identified 118 ASM-resistant cases and 114 ASM-responsive controls with IGE. First, we confirmed our recent finding that catamenial epilepsy is associated with ASM-resistant IGE (odds ratio [OR] 3.53, 95% confidence interval [CI] 1.32–10.41, for all study subjects) after covariate adjustment. Other independent factors seen with ASM resistance include certain seizure-type combinations (absence, myoclonic, and generalized tonic-clonic seizures [OR 7.06, 95% CI 2.55–20.96]; absence and generalized tonic-clonic seizures [OR 4.45, 95% CI 1.84–11.34]), as well as EEG markers of increased generalized spike-wave discharges (GSWs) in sleep (OR 3.43, 95% CI 1.12–11.36 for frequent and OR 7.21, 95% CI 1.50–54.07 for abundant discharges in sleep) and the presence of generalized polyspike trains (GPTs; OR 5.49, 95% CI 1.27–38.69). The discriminative ability of our final multivariable model, as measured by area under the receiver-operating characteristic curve, was 0.80. Significance: Multiple clinical and EEG characteristics independently predict ASM resistance in IGE. To improve understanding of a patient's prognosis, clinicians could consider asking about specific seizure-type combinations and track whether they experience catamenial epilepsy. Obtaining prolonged EEG studies to record the burden of GSWs in sleep and assessing for the presence of GPTs may provide additional predictive value.
AB - Objective: We sought to determine which combination of clinical and electroencephalography (EEG) characteristics differentiate between an antiseizure medication (ASM)–resistant vs ASM-responsive outcome for patients with idiopathic generalized epilepsy (IGE). Methods: This was a case-control study of ASM-resistant cases and ASM-responsive controls with IGE treated at five epilepsy centers in the United States and Australia between 2002 and 2018. We recorded clinical characteristics and findings from the first available EEG study for each patient. We then compared characteristics of cases vs controls using multivariable logistic regression to develop a predictive model of ASM-resistant IGE. Results: We identified 118 ASM-resistant cases and 114 ASM-responsive controls with IGE. First, we confirmed our recent finding that catamenial epilepsy is associated with ASM-resistant IGE (odds ratio [OR] 3.53, 95% confidence interval [CI] 1.32–10.41, for all study subjects) after covariate adjustment. Other independent factors seen with ASM resistance include certain seizure-type combinations (absence, myoclonic, and generalized tonic-clonic seizures [OR 7.06, 95% CI 2.55–20.96]; absence and generalized tonic-clonic seizures [OR 4.45, 95% CI 1.84–11.34]), as well as EEG markers of increased generalized spike-wave discharges (GSWs) in sleep (OR 3.43, 95% CI 1.12–11.36 for frequent and OR 7.21, 95% CI 1.50–54.07 for abundant discharges in sleep) and the presence of generalized polyspike trains (GPTs; OR 5.49, 95% CI 1.27–38.69). The discriminative ability of our final multivariable model, as measured by area under the receiver-operating characteristic curve, was 0.80. Significance: Multiple clinical and EEG characteristics independently predict ASM resistance in IGE. To improve understanding of a patient's prognosis, clinicians could consider asking about specific seizure-type combinations and track whether they experience catamenial epilepsy. Obtaining prolonged EEG studies to record the burden of GSWs in sleep and assessing for the presence of GPTs may provide additional predictive value.
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U2 - 10.1111/epi.17104
DO - 10.1111/epi.17104
M3 - Article
C2 - 34705264
AN - SCOPUS:85118218115
SN - 0013-9580
VL - 63
SP - 150
EP - 161
JO - Epilepsia
JF - Epilepsia
IS - 1
ER -