Summary: A new study finds a strong association between catamenial epilepsy—where seizure frequency increases around the menstrual cycle—and drug-resistant genetic generalized epilepsy. Women with catamenial epilepsy were nearly four times more likely to have epilepsy that does not respond to standard anti-seizure medications.
Source: Rutgers University
A Rutgers coauthored study published in Neurology reports for the first time a significant link between catamenial epilepsy in women with genetic generalized epilepsy (GGE) and drug-resistant epilepsy, offering a possible path toward more personalized treatment strategies.
Researchers found that women whose seizures increase in frequency around their menstrual cycle—referred to as catamenial epilepsy—were nearly four times more likely to have drug-resistant GGE than women who do not experience menstrual-related changes in seizure patterns. This association was replicated across two independent patient samples, strengthening the finding.
“Genetic generalized epilepsy is often considered more responsive to anti-seizure medications than focal epilepsy. Still, a notable minority—previous estimates range from 18 to 36 percent—do not respond well to standard treatments,” said Gary A. Heiman, associate professor in the Department of Genetics at Rutgers University–New Brunswick and the study’s senior author. “Discovering a connection between menstrual cycle–related seizure increases and drug resistance suggests a specific subgroup of patients who might benefit from targeted research and tailored therapies.”
In generalized epilepsy, seizures arise bilaterally across both hemispheres of the brain, unlike focal epilepsy where seizures begin in a single localized region. Anti-seizure medications reduce the spread of abnormal brain activity and are effective for roughly two-thirds of people with epilepsy; surgical and other therapies are options when medications fail.
The multicenter study analyzed clinical data from 589 patients at the Columbia Comprehensive Epilepsy Center and 66 patients at the Yale Comprehensive Epilepsy Center to develop and validate a predictive model for identifying drug-resistant GGE. The model aimed to help clinicians recognize patients at higher risk of failing standard anti-seizure therapy so they can consider alternative or more aggressive treatment earlier in care.
Heiman noted that women with catamenial drug-resistant GGE may represent a relatively homogeneous clinical group with a distinct underlying cause. “If genetic or treatment-response studies focus on this subgroup, we may uncover mechanisms that explain medication resistance and develop personalized therapies tailored to those mechanisms,” he said. The authors caution that larger studies are needed to confirm these results and to better define optimal treatment approaches.
Contributing authors include Suzanne Thornton (Rutgers, now at Swarthmore University) and collaborators from leading centers: Columbia University Medical Center, University of Miami, Yale University, University of Oxford, Free University of Brussels, Monash University, The Royal Melbourne Hospital, The University of Melbourne, and Alfred Health.
About this neurology research article
Source:
Rutgers University
Contacts:
Todd Bates – Rutgers University
Image Source:
The image is credited to National Institute of Mental Health, National Institutes of Health.
Original Research: Closed access
“Development and validation of a predictive model of drug-resistant genetic generalized epilepsy” by Gary A. Heiman et al. Neurology.
Abstract
Development and validation of a predictive model of drug-resistant genetic generalized epilepsy
Objective
To develop and validate a clinical prediction model that identifies patients with genetic generalized epilepsy (GGE) who are likely to be resistant to antiepileptic drugs (AED-resistant GGE).
Method
The researchers conducted a nested case-control study within ongoing longitudinal observational cohorts at two tertiary epilepsy centers. Three candidate predictive models were created from a training dataset and then evaluated using internal validation and an external testing dataset to assess performance and generalizability.
Results
Among 5,189 patients in the longitudinal study, 122 met criteria for AED-resistant GGE and 468 were AED-responsive. The external testing dataset included 66 GGE patients, 17 of whom were drug-resistant cases. Catamenial epilepsy, a history of psychiatric conditions, and the combined seizure phenotype of generalized tonic-clonic, myoclonic, and absence seizures were strongly associated with drug-resistant status. Women with catamenial epilepsy had about a four-fold increased risk of AED resistance compared with women without menstrual-cycle–related seizure increases. Model calibration was acceptable, while discriminative performance measured by area under the ROC curve (AUC) ranged from 0.58 to 0.65, indicating modest ability to distinguish cases from controls.
Conclusion
Catamenial epilepsy, psychiatric comorbidity, and the specific combination of generalized seizure types are negative prognostic indicators for drug-resistant GGE. The model’s AUC near 0.6 suggests limited separation between groups, implying that additional clinical, genetic, or environmental variables may be necessary to improve predictive accuracy in future research.