Simultaneous Use of Two Different Tools to Assess Compliance with Antiepileptic Drugs: Experience in A Community-Based Study

Greater need for treatment optimization in patients with epilepsy initiating adjunctive therapy: Results of a retrospective claims analysis of antiseizure medication drug load in the United States

BACKGROUND

This retrospective, observational study used US claims data to assess changes in antiseizure medication (ASM) drug load for a cohort of patients with epilepsy.

METHODS

Adults (≥18 years) with a diagnosis of epilepsy (ICD-10 code G40.xxx) who started new adjunctive ASM treatment with one of 4 branded (brivaracetam, eslicarbazepine, lacosamide, perampanel) or 4 unbranded (carbamazepine, lamotrigine, levetiracetam, topiramate) ASMs between January 1, 2016 and December 31, 2020 were identified from IBM MarketScan® research databases (primary study population). Patients must have been continuously enrolled 360 days before the start of the new ASM (eligibility period). Follow-up was from the start of new ASM until Day 540 (∼18 months). The primary endpoint was concomitant ASM drug load, which included all ASMs except the new (comparator) ASM. A sensitivity analysis population included adults with epilepsy who were continuously enrolled for ≥ 180 days during at least one calendar year in the study period (2016-2020), whether or not the comparator ASM was new or existing during that period. Total ASM drug load, which included comparator ASM and concomitant ASMs, was assessed in the sensitivity analysis population.

RESULTS

In total, 21,332 patients were included in the primary study population, of which 5767 initiated branded ASMs and 15,565 initiated unbranded ASMs. A total of 392,426 patients were included in the sensitivity analysis population during at least one calendar year 2016-2020. Concomitant ASM drug load increased in the 360 days prior to new ASM start and slightly declined thereafter. Mean concomitant ASM drug load for the primary population was 1.6 (SD 1.8) at new ASM start. Concomitant drug load was higher among those starting branded ASM comparators compared to those starting unbranded comparators. Mean total ASM drug load for patients increased over time and was approximately double for patients exposed to branded ASMs (mean range 2.1 to 2.7) compared to that of patients exposed to any unbranded ASM (mean range 1.0 to 1.3).

CONCLUSION

Concomitant ASM drug load increased prior to addition of new ASM, with higher increases observed among patients starting branded vs unbranded ASMs, followed by slight decreases thereafter. Total drug load increased linearly among all patients. These findings underscore the need for ongoing ASM regimen evaluation and treatment optimization in patients with epilepsy.

Reductions in concomitant antiseizure medication drug load during adjunctive cenobamate therapy: Post-hoc analysis of a subset of patients from a phase 3, multicenter, open-label study

OBJECTIVE

Many patients with epilepsy require polytherapy, which increases their antiseizure medication (ASM) drug load, a measure that considers the doses of all ASMs a patient is taking. Changes in concomitant ASM drug load after adding cenobamate were evaluated post-hoc in a subset of the open-label, phase 3 study.

METHODS

Patients 18-70 years old with uncontrolled focal seizures taking 1-3 ASMs were enrolled. Total concomitant ASM drug load (not including cenobamate) was calculated by dividing the patient's prescribed dose for each ASM by its defined daily dose, per the World Health Organization, then summing the ratios. Changes in concomitant ASM drug load were measured from baseline in 3-month intervals up to 24 months by both total and class-specific ASM drug load. Subgroups of interest included: older adults (65-70 years), prior epilepsy-related surgery vs none, and baseline seizure frequency < 3 vs ≥ 3 seizures/28 days.

RESULTS

Data from 240 patients were available (mean age 41.8 years, mean baseline drug load 3.57). Following cenobamate initiation, the mean concomitant ASM drug load was reduced by 29.4 % at Month 12 % and 31.8 % at Month 24. Reductions occurred in all assessed ASM drug classes, with the largest reduction in benzodiazepines (55.2 % at Month 24). Each assessed subgroup exceeded a 30 % reduction in concomitant ASM drug load at Month 24. Over 24 months, maintenance of ≥ 50 % response occurred in 89.3 %, 86.4 %, and 90.6 % of patients with low (-0.25 to <0), moderate (-0.59 to -0.25), or high (-3.3 to -0.59) numerical reductions in concomitant ASM drug load from baseline, respectively, compared with 86.0 % in patients with no change in drug load; maintenance of 100 % response occurred in 80.7 %, 84.3 %, and 70.0 % of patients with low, moderate, or high numerical reductions in concomitant ASM drug load, compared with 82.0 % in patients with no change.

CONCLUSIONS

Adding cenobamate led to reduced mean concomitant ASM drug loads during 1 and 2 years of treatment. Reductions occurred regardless of ASM drug class, patient age, or epilepsy disease characteristics and did not impact maintenance of response rates.

Detecting Reasons for Nonadherence to Medication in Adults with Epilepsy: A Review of Self-Report Measures and Key Predictors

This review presents individual reasons for self-reported nonadherence in people with epilepsy (PWE). A literature search was performed on the PubMed/Medline and Scopus databases for studies published up to March 2022. Thirty-six studies were included using the following inclusion criteria: original studies on adults with epilepsy, use of subjective self-report adherence measurement methods, and publication in English. Data were extracted using a standardized data extraction table, including the year of publication, authors, cohort size, study design, adherence measurement method, and self-reported reasons for nonadherence. Self-reported reasons for nonadherence were grouped following the WHO model with the five dimensions of nonadherence. In addition, study characteristics and sociodemographic information are reported. Of the 36 included studies, 81% were observational. The average nonadherence rate was nearly 50%. Across all studies, patient-associated, therapy-associated, and circumstance-related factors were the most frequently reported dimensions of nonadherence. These factors include forgetfulness, presence of side-effects, and history of seizures. Regarding healthcare system factors, financial problems were the most reported reason for nonadherence. Stigmatization and quality of life were the most frequently cited factors influencing nonadherence in the disease- and circumstance-related dimensions. The results suggest that interventions for improving adherence should incorporate all dimensions of nonadherence.

Current Principles in the Management of Drug-Resistant Epilepsy

Drug-resistant epilepsy is associated with poor health outcomes and increased economic burden. In the last three decades, various new antiseizure medications have been developed, but the proportion of people with drug-resistant epilepsy remains relatively unchanged. Developing strategies to address drug-resistant epilepsy is essential. Here, we define drug-resistant epilepsy and emphasize its relationship to the conceptualization of epilepsy as a symptom complex, delineate clinical risk factors, and characterize mechanisms based on current knowledge. We address the importance of ruling out pseudoresistance and consider the impact of nonadherence on determining whether an individual has drug-resistant epilepsy. We then review the principles of epilepsy drug therapy and briefly touch upon newly approved and experimental antiseizure medications.

The worldwide epilepsy treatment gap: A systematic review and recommendations for revised definitions - A report from the ILAE Epidemiology Commission

OBJECTIVE

In order to more appropriately apply and understand the "epilepsy treatment gap" (ETG) concept in current health systems, revised conceptual and operational definitions of ETG are timely and necessary. This article therefore systematically reviews worldwide studies of the ETG, distinguishing high-, middle-, and low-income regions, and provides recommendations for an updated International League Against Epilepsy (ILAE) definition of ETG.

METHODS

A systematic review of the ETG was performed using Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) standards. The search was conducted from January 1990 to July 2019, in the online databases of Ovid MEDLINE and Embase. Identified abstracts were reviewed in duplicate and data independently extracted using a standard proforma. Data describing treatment gap information including both diagnostic and therapeutic aspects of access to epilepsy treatment were recorded. Descriptive statistics are presented.

RESULTS

The treatment gap reported in the 45 distinctive populations represented 33 countries. Treatment gap definitions varied widely. The reported ETGs ranged broadly from 5.6% in Norway to 100% in parts of Tibet, Togo, and Uganda. The wide range of reported ETGs was multifactorial in origin including true differences in the availability and utilization of health care among study populations, variations in operational definitions of the epilepsy treatment gap, and methodological differences in sampling and identifying representative epilepsy cases in populations. Significance and recommendations For the ETG to be a useful metric to compare levels of unmet epilepsy care across different countries and regions, a standardized definition must be adapted, recognizing some of the limitations of the current definitions. Our proposed definition takes into account the lack of effective health care insurance, the diagnostic gap, the therapeutic gap, quality-of-care, and other unmet health care needs."