Abstract
The purpose of this pilot study was to analyze treatment pathways of pediatric epilepsy using the common data model (CDM) based on electronic health record (EHR) data. We also aimed to reveal whether CDM analysis was feasible and applicable to epilepsy research. We analyzed the treatment pathways of pediatric epilepsy patients from our institute who underwent antiseizure medication (ASM) treatment for at least 2 years, using the Observational Medical Outcomes Partnership (OMOP)-CDM. Subgroup analysis was performed for generalized or focal epilepsy, varying age of epilepsy onset, and specific epilepsy syndromes. Changes in annual prescription patterns were also analyzed to reveal the different trends. We also calculated the proportion of drug-resistant epilepsy by applying the definition of seizure persistence after application of two ASMs for a sufficient period of time (more than 6 months). We identified 1,192 patients who underwent treatment for more than 2 years (mean ± standard deviation: 6.5 ± 3.2 years). In our pediatric epilepsy cohort, we identified 313 different treatment pathways. Drug resistance, calculated as the application of more than three ASMs during the first 2 years of treatment, was 23.8%. Treatment pathways and ASM resistance differed between subgroups of generalized vs. focal epilepsy, different onset age of epilepsy, and specific epilepsy syndromes. The frequency of ASM prescription was similar between onset groups of different ages; however, phenobarbital was frequently used in children with epilepsy onset < 4 years. Ninety-one of 344 cases of generalized epilepsy and 187 of 835 cases of focal epilepsy were classified as medically intractable epilepsy. The percentage of drug resistance was markedly different depending on the specific electro-clinical epilepsy syndrome [79.0% for Lennox-Gastaut syndrome (LGS), 7.1% for childhood absence epilepsy (CAE), and 9.0% for benign epilepsy with centrotemporal spikes (BECTS)]. We could visualize the annual trend and changes of ASM prescription for pediatric epilepsy in our institute from 2004 to 2017. We revealed that CDM analysis was feasible and applicable for epilepsy research. The strengths and limitations of CDM analysis should be carefully considered when planning the analysis, result extraction, and interpretation of results.
Highlights
Epilepsy is a heterogeneous and complex brain disorder comprising of many seizure types and epilepsy syndromes [1, 2]
We identified 1,192 patients [male: female, 653:539; mean age at diagnosis, 8.3 ± 5.0 years] who had > 2 years follow-up and anti-seizure medication (ASM) prescription data after the common data model (CDM) query application
We applied the CDM analysis to estimate the proportion of Drug-Resistant Epilepsy (DRE) in a cohort of all pediatric epilepsy patients in our institution using the International League Against Epilepsy (ILAE) criteria for DRE [11]
Summary
Epilepsy is a heterogeneous and complex brain disorder comprising of many seizure types and epilepsy syndromes [1, 2]. Since the 1980s more than (>) 15 ASMs have been introduced, giving rise to more choices in selecting the first drug for epilepsy treatment but making it more difficult to make optimal treatment decisions [1]. Regarding treatment choices for pediatric epilepsy, research findings are limited, and many clinical questions remain unresolved; physicians must often rely on clinical judgement [6]. The available information about the treatment sequence for pediatric syndromes and the use of therapy in actual medical practice is limited [6]. In an effort to achieve consensus on a number of treatment options, 41 U.S experts were surveyed on pediatric epilepsy and seizures, including opinions regarding 645 treatment options, and the overall recommendations were reported in 2015 [6]. The experts reached consensus on many treatment options, it remains to be evaluated whether treatment recommendations reflect actual practice and whether there is any difference between actual practice and recommendations
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