Prevalence and associated factors of drug-resistant epilepsy in an adult epilepsy population

Introduction: Approximately 65-70% of people with epilepsy respond to their first or second anti-seizure medication, while 15-40% are refractory to pharmacotherapy. Different epilepsy types have varying treatment approaches and prognoses and there could be significant early predictors of drug resistance. Patients with refractory epilepsy experience more adverse effects and diminished quality of life, making prompt identification of this state vital. This study aimed to assess the burden of drug resistance in a cohort of adult epilepsy patients, and compare resistance rates among different seizure types. It also sought to identify early predictors of drug resistance.
Methods: We analysed cross-sectional data from 445 patients with adult-onset epilepsy, categorising participants according to response to therapy to two primary groups: drugresistant (DR) and adequate response (AR). We further categorised them according to the seizure type and evaluated for possible associated factors such as epilepsy type, febrile seizures, family history, electroencephalogram (EEG) and imaging abnormalities, and adverse events.
Results: The overall drug resistance rate was 36%, with epilepsy with focal motor onset seizures showing the highest rate at 48.4% and epilepsy with generalised non-motor seizures exhibiting zero resistance. Factors associated with higher drug resistance included motor onset seizures (p=0.003), positive imaging findings (p=0.001), and a history of status epilepticus (p=0.02). No significant differences were found regarding focal versus generalised seizures, family history, febrile seizures, or EEG abnormalities. Adverse consequences of seizures were more common in the DR group (p< 0.001), and the AR group required significantly fewer medications (p< 0.00001).
Conclusions: The study highlights a 36% drug resistance rate in a cohort of adult patients with epilepsy beginning after the age of 12 years. Early identification and tailored management strategies for these high-risk patients based on seizure type and predictors may help to control their epilepsy better.