Selection and Continuation of Antiseizure Medication in Children With Epilepsy in Sweden From 2007 to 2020

Trends in prescription of anti-seizure medications in Japan between 2018 and 2021: A retrospective study using the National Database Open Data Japan

PURPOSE

This retrospective study aimed to analyze anti-seizure medication (ASM) prescription trends in Japan, particularly among older adults and women of childbearing age, to inform future treatment strategies and optimize ASM selection criteria.

METHODS

Data were extracted from the National Database Open Data Japan for fiscal years (FY) 2018-2021, covering prescriptions across sex and 5-year age groups. We conducted data imputation for prescriptions under 1,000 units to maintain anonymity, calculated the estimated number of patients using standard adult maintenance doses, and adjusted for pediatric dosing using Augsberger's formula.

RESULTS

Our analysis revealed a 7.6% increase in ASM usage, with a notable shift from older to newer ASMs, such as levetiracetam (LEV) and lamotrigine (LTG). LEV and LTG prescriptions increased by 26.7% and 15.0% from FY 2018 to FY 2021, respectively, whereas older ASMs such as phenytoin, declined. Sex-specific analysis showed a higher LTG prescription rate among women, especially in adolescent and young adult cohorts, where the female-to-male prescription ratio increased from 1.65 to 1.85. Valproate (VPA) and LEV accounted for 57.0% of ASM prescriptions in older adults. The number of inpatient LTG prescriptions was notably lower than that of outpatient LTG prescriptions across age groups. Pediatric use of generics was lower than that in other age groups.

CONCLUSION

This study revealed that newer ASMs are being used increasingly, with a significant proportion of VPA continuously prescribed among women of childbearing age. In older adults, VPA and LEV accounted for more than half of the ASM prescriptions. These findings are crucial for developing future treatment strategies and improving the ASM selection criteria.

Comparing the efficacy of anti-seizure medications using matched cohorts on a large insurance claims database

Epilepsy is a severe chronic neurological disease affecting 60 million people worldwide. Primary treatment is with anti-seizure medicines (ASMs), but many patients continue to experience seizures. We used retrospective insurance claims data on 280,587 patients with uncontrolled epilepsy (UE), defined as status epilepticus, need for a rescue medicine, or admission or emergency visit for an epilepsy code. We conducted a computational risk ratio analysis between pairs of ASMs using a causal inference method, in order to match 1034 clinical factors and simulate randomization. Data was extracted from the MarketScan insurance claims Research Database records from 2011 to 2015. The cohort consisted of individuals over 18 years old with a diagnosis of epilepsy who took one of eight ASMs and had more than a year of history prior to the filling of the drug prescription. Seven ASM exposures were analyzed: topiramate, phenytoin, levetiracetam, gabapentin, lamotrigine, valproate, and carbamazepine or oxcarbazepine (treated as the same exposure). We calculated the risk ratio of UE between pairs of ASM after controlling for bias with inverse propensity weighting applied to 1034 factors, such as demographics, confounding illnesses, non-epileptic conditions treated by ASMs, etc. All ASMs exhibited a significant reduction in the prevalence of UE, but three drugs showed pair-wise differences compared to other ASMs. Topiramate consistently was associated with a lower risk of UE, with a mean risk ratio range of 0.68-0.93 (average 0.82, CI: 0.56-1.08). Phenytoin and levetiracetam were consistently associated with a higher risk of UE with mean risk ratio ranges of 1.11 to 1.47 (average 1.13, CI 0.98-1.65) and 1.15 to 1.43 (average 1.2, CI 0.72-1.69), respectively. Large-scale retrospective insurance claims data - combined with causal inference analysis - provides an opportunity to compare the effect of treatments in real-world data in populations 1,000-fold larger than those in typical randomized trials. Our causal analysis identified the clinically unexpected finding of topiramate as being associated with a lower risk of UE; and phenytoin and levetiracetam as associated with a higher risk of UE (compared to other studied drugs, not to baseline). However, we note that our data set for this study only used insurance claims events, which does not comprise actual seizure frequencies, nor a clear picture of side effects. Our results do not advocate for any change in practice but demonstrate that conclusions from large databases may differ from and supplement those of randomized trials and clinical practice and therefore may guide further investigation.

What are the considerations when initiating treatment for epilepsy in children?

INTRODUCTION

There is a very wide spectrum of epilepsies and developmental and epileptic encephalopathies that affect children, from self-limited forms, not necessarily requiring treatment, to severe drug-resistant ones.

AREAS COVERED

In this perspective, the authors discuss the main factors to consider before drug prescription in children, considering the most recent clinical research, including age, seizure type, epilepsy syndrome, etiology, efficacy and safety profile, comorbidities, gender, available formulations, costs and drug coverage, and regulatory issues. The literature search was conducted through a PubMed search on antiseizure medications for patients aged 0-18, with respect to each of the aforementioned factors, and by checking the reference lists of relevant papers.

EXPERT OPINION

The most expanding field of research and innovation for clinical practice is precision medicine, which addresses the holistic treatment of genetic epilepsies and developmental and epileptic encephalopathies. It achieves this by addressing their detrimental effects on synapses, neurotransmission, and cellular signaling pathways with the double aim to treat seizures and to rescue neurodevelopmental trajectories, but also the issue of adverse events and drug resistance through pharmacogenomics.