About 1/3rd of people with epilepsy are medically refractory, that is, do not achieve seizure freedom with antiepileptic drugs (AEDs). There are few evidence-based guidelines on the optimal treatment of refractory patients. In previous work, we studied an institutionalized, developmentally disabled patient population in Washington State and discovered that of the most frequently-used AED regimens, only the combination of lamotrigine (LTG) and valproate (VPA) demonstrated significant benefit in refractory epilepsy. A caveat to this finding was the specialized patient population in which the study was conducted. In this proposal, we will use two complementary approaches in community-based patients to search for AED regimens with superior efficacy in refractory patients, so to determine whether our previous findings are applicable to the general refractory epilepsy population. In the first Specific Aim, we will study individuals with epilepsy who use either of two online seizure diaries to track their seizure occurrences and AED usage. In the second Aim, we also study the entire outpatient epilepsy population of the University of Washington Regional Epilepsy Center, using automated analysis of the electronic health record, to determine which AED regimens had the highest success rate in producing seizure freedom. The potential outcome of this study will be the identification of AED regimens that are the most effective in a prevalent but difficult to treat epilepsy population.

Public Health Relevance

Epilepsy is one of the most common neurological diseases, affecting nearly 1% of the population, and causing significant disability in the 30% of medically refractory epilepsy patients whose seizures are uncontrolled by existing medication. In this proposal, we intend to discover which antiepileptic drug (AED) regimens are most effective using a ?big data? approach that leverages the wealth of patient data created both in online seizure diaries and in hospital system electronic health records.

Agency
National Institute of Health (NIH)
Institute
National Institute of Neurological Disorders and Stroke (NINDS)
Type
Small Research Grants (R03)
Project #
1R03NS114801-01
Application #
9875142
Study Section
Acute Neural Injury and Epilepsy Study Section (ANIE)
Program Officer
Klein, Brian
Project Start
2020-03-15
Project End
2022-02-28
Budget Start
2020-03-15
Budget End
2021-02-28
Support Year
1
Fiscal Year
2020
Total Cost
Indirect Cost
Name
University of Washington
Department
Neurology
Type
Schools of Medicine
DUNS #
605799469
City
Seattle
State
WA
Country
United States
Zip Code
98195