Changes in the Use of Brand Name and Generic Medications and Total Prescription Cost Among Medicare Beneficiaries With Epilepsy

Correlation between prescription volumes of generic antiepileptic drugs and the number of clinical epileptologists across prefectural regions in Japan: A descriptive study using a national claims database

PURPOSE

Although generic drugs are essential in reducing medical costs, their use in epilepsy therapy remains a subject of ongoing debate. In this study, we analysed prescription trends of generic drugs using data from the National Database of Health Insurance Claims and Specific Health Checkups (NDB) Open Data Japan.

METHODS

The number of generic drug prescriptions from 2017-2021 was extracted from the NDB Open Data Japan, with data for each medication stratified by prefectural region, sex, and age, allowing for the analysis of the impact of each factor. We analysed the correlation between the prescription volumes of generic antiseizure medications (ASMs) and the number of clinical epileptologists registered with the Japan Epilepsy Society per 100,000 population.

RESULTS

In 2021, the prescription volume of generic ASMs was 49 %, whereas that for other pharmacological agents was between 70-80 %. Notably, for children < 15 years of age, generics made up approximately 20 % of prescriptions, which was significantly less than that in other age groups. Analysis by prefecture revealed a negative correlation between prescription volumes of ASMs and the number of clinical epileptologists across prefectural regions in Japan (R = -0.47, p < 0.01).

CONCLUSION

Our findings indicate that the higher the proportion of clinical epileptologists in each prefecture, the lower the number of prescribed generic ASMs. Clinical epileptologists in Japan therefore prescribe antiseizure agents in accordance with the Japanese epilepsy treatment guidelines that do not recommend the use of generic agents.

Pharmacogenetic Variants and Plasma Concentrations of Antiseizure Drugs: A Systematic Review and Meta-Analysis

Importance

Precise estimation of a patient's drug metabolism capacity is important for antiseizure dose personalization.

Objective

To quantify the differences in plasma concentrations for antiseizure drugs associated with variants of genes encoding drug metabolizing enzymes.

Data Sources

PubMed, Clinicaltrialsregister.eu, ClinicalTrials.gov, International Clinical Trials Registry Platform, and CENTRAL databases were screened for studies from January 1, 1990, to September 30, 2023, without language restrictions.

Study Selection

Two reviewers performed independent study screening and assessed the following inclusion criteria: appropriate genotyping was performed, genotype-based categorization into subgroups was possible, and each subgroup contained at least 3 participants.

Data Extraction and Synthesis

The Meta-analysis of Observational Studies in Epidemiology (MOOSE) guidelines were followed for data extraction and subsequent quality, validity, and risk-of-bias assessments. The results from the included studies were pooled with random-effect meta-analysis.

Main Outcomes and Measures

Plasma concentrations of antiseizure drugs were quantified with the dose-normalized area under the concentration-time curve, the dose-normalized steady state concentration, or the concentrations after a single dose at standardized dose and sampling time. The ratio of the means was calculated by dividing the mean drug plasma concentrations of carriers and noncarriers of the pharmacogenetic variant.

Results

Data from 98 studies involving 12 543 adult participants treated with phenytoin, valproate, lamotrigine, or carbamazepine were analyzed. Studies were mainly conducted within East Asian (69 studies) or White or European (15 studies) cohorts. Significant increases of plasma concentrations compared with the reference subgroup were observed for phenytoin, by 46% (95% CI, 33%-61%) in CYP2C9 intermediate metabolizers, 20% (95% CI, 17%-30%) in CYP2C19 intermediate metabolizers, and 39% (95% CI, 24%-56%) in CYP2C19 poor metabolizers; for valproate, by 12% (95% CI, 4%-20%) in CYP2C9 intermediate metabolizers, 12% (95% CI, 2%-24%) in CYP2C19 intermediate metabolizers, and 20% (95% CI, 2%-41%) in CYP2C19 poor metabolizers; and for carbamazepine, by 12% (95% CI, 3%-22%) in CYP3A5 poor metabolizers.

Conclusions and Relevance

This systematic review and meta-analysis found that CYP2C9 and CYP2C19 genotypes encoding low enzymatic capacity were associated with a clinically relevant increase in phenytoin plasma concentrations, several pharmacogenetic variants were associated with statistically significant but only marginally clinically relevant changes in valproate and carbamazepine plasma concentrations, and numerous pharmacogenetic variants were not associated with statistically significant differences in plasma concentrations of antiseizure drugs.

US Generic Antiseizure Medication Supply Chain: Observations from Analysis of US Government Databases

BACKGROUND

Generic drug manufacturing has shifted away from the U.S. in the last few decades. The medication supply chain, from manufacturers to resellers, has become increasingly globalized and complex. This has led to bottlenecks in their manufacture resulting in medication shortages. Review of this process as it pertains to antiseizure medications (ASM) shows gaps in our comprehension of its complexities. Understanding these processes will be essential for preventing medication shortages.

OBJECTIVES

The aim of this research is to examine the generic ASM supply with an emphasis on production, labeling, and repackaging.

METHODS

Data from the United States Food and Drug Administration (FDA) and the National Library of Medicine (NLM) website DailyMed was used to evaluate supply chain details to gather information on antiseizure medication formulations, manufacturing locations, and labeling.

RESULTS

Out of 3142 ASM-related active National Drug Code (NDC-9) codes, 2663 NDC-9 codes with Abbreviated New Drug Application (ANDA) status were included in the analysis. Most (94.8 %) were enteral, with only 5.2 % being parenteral (intravenous and intramuscular route). We identified the manufacturing country for 82 % of these codes, corresponding to 306 unique ANDA numbers. 119 manufacturing sites in 12 countries produce generic ASM Finished Dosage Forms (FDF): 103 for enteral and 21 for parenteral. India is the main producer of enteral ASM FDFs with 49 sites, followed by the US with 36. Regarding parenteral formulation, five countries had 21 unique manufacturing locations. 42 % of the 103 enteral ASM FDFs manufacturing sites produced multiple ASM FDFs, with one facility making eight distinct ASMs. 34.4 % of facilities were associated with over 3 ANDAs, and 15.1 % with more than 5. 22.7 % of ANDAs lacked a manufacturing facility identifier. Repackaged ASM FDFs constituted 48 % of NDC-9 s. Gabapentin and pregabalin were the most common oral ASMs.

CONCLUSIONS

India is the major source for generic ASM FDFs manufacturing, leading to concerns about overall supply dependency on that country. There is a paucity of facilities for the global supply of parenteral ASM FDFs. There is missing data for many NDC-9 codes emphasizing urgency for transparency in the supply chain.

Characteristics and Attendance of Patients Eligible for the PASS Clinic: A Transition of Care Model After Acute Symptomatic Seizures

Background and Objectives

Most acute symptomatic seizure (ASyS) patients stay on antiseizure medications (ASM) long-term, despite low epilepsy development risk. The Post-Acute Symptomatic Seizure (PASS) clinic is a transition of care model for ASyS patients who individualize ASM management with the goal of a safe deprescription. We evaluated patients discharged on ASMs after a witnessed or suspected ASyS to analyze their PASS clinic visit attendance and its predictors.

Methods

A single-center, retrospective cohort study of adults without epilepsy who were discharged from January 1, 2019, to September 30, 2019, on first-time ASMs due to witnessed or suspected ASyS (PASS clinic-eligible). We fit a cause-specific Cox proportional hazards model to analyze factors associated with PASS clinic attendance, which depends on survival in this patient population that has a high early postdischarge mortality (a competing risk). We checked for multicollinearity and the assumption of proportional hazards.

Results

Among 307 PASS clinic-eligible patients, 95 (30.9%) attended the clinic and 136 (44.3%) died during a median follow-up of 14 months (interquartile range = 2-34). ASyS occurred in 60.2% (convulsive 47%; electrographic 26.7%) of patients. ASMs were continued in the absence of ASyS or epileptiform abnormalities (EAs) in 27% of patients. Multivariable analysis revealed that the presence of EAs (HR = 1.69, 95% CI 1.10-2.59), PASS clinic appointments provided before discharge (HR = 3.39, 95% CI 2.15-5.33), and less frequently noted ASyS etiologies such as autoimmune encephalitis (HR = 2.03, 95% CI 1.07-3.86) were associated with an increased clinic attendance rate. Medicare/Medicaid insurance (HR = 0.43, 95% CI 0.24-0.78, p = 0.005) and the presence of progressive brain injury (i.e., tumors; HR = 0.55, 95% CI 0.32-0.95, p = 0.032) were associated with reduced rate of PASS clinic attendance.

Discussion

Our real-world data highlight the need for appropriate postdischarge follow-up of ASyS patients, which can be fulfilled by the PASS clinic model. Modest PASS clinic attendance can be significantly improved by adhering to a structured discharge planning process whereby appointments are provided before discharge. Future research comparing patient outcomes, specifically safe ASM discontinuation in a PASS clinic model to routine clinical care, is needed.

Lamotrigine and exogenous estrogen among females with epilepsy: A retrospective analysis of administrative claims data

OBJECTIVE

Exogenous estrogen reduces lamotrigine serum concentrations. Little is known about whether providers adjust lamotrigine doses for addition of exogenous estrogen among people with epilepsy, despite expert recommendations. We determined the incidence of dose increases in lamotrigine following incident prescription of estrogen among females with epilepsy (FWE) in claims data.

METHODS

We used Optum's de-identified Clinformatics® Data Mart Database to create a cohort of U.S. FWE prescribed lamotrigine at a stable dose, with a subsequent prescription for estrogen from 2011 to 2021. We calculated cumulative incidence functions of dose increases in lamotrigine following prescription of exogenous estrogen. We performed a Cox proportional hazards model for multiple candidate predictors of a lamotrigine dose increase.

RESULTS

The cohort included 643 FWE, with median age of 31 (interquartile ratio [IQR] 20-42). The cumulative incidence of any lamotrigine increase was 28% (95% confidence interval [CI] 25%-32%). The median number of days after the first estrogen fill until the first lamotrigine adjustment was 118 (IQR 48-188). In unadjusted Cox models, older age, use of estrogen in hormone replacement therapy as opposed to contraception, and annual household income of $50,000-$99,999 (compared with <$50,000) were significant negative predictors of a dose adjustment in lamotrigine with hazard ratios (HRs) of 0.82 (95% CI 0.72-0.92), 0.63 (95% CI 0.42-0.95), and 0.62 (95% CI 0.40-0.95). In the adjusted Cox model, age and income remained significant predictors with HRs of 0.79 (95% CI 0.66-0.94) and 0.59 (95% CI 0.36-0.95).

CONCLUSION

Dose increase of lamotrigine following addition of exogenous estrogen is rare among U.S. FWE, with potential disparities based on age and income level. More guidance may be needed for providers on this topic.

Evolution of antiseizure medication use and cost in the United States of America 2006-2021

OBJECTIVE

To describe the evolution in use and cost of antiseizure medications (ASM) in the United States of America (USA).

METHODS

Retrospective descriptive study using the IBM MarketScan Commercial Database (data of privately-insured patients) for the years 2006 to 2021. We identified patients with epilepsy who were on ASM. We adjusted cost for inflation with the Gross Domestic Product Implicit Price Deflator.

RESULTS

We evaluated 347,158 patients (46.9 % males; median (p25-p75) age: 33 (17-49) years; 28 % with pediatric-onset epilepsy and 72 % with adult-onset epilepsy) with a total of 1,385,382 person-years and 588,285,065 ASM prescription days. The most commonly prescribed (as percentage of prescription days) ASMs in 2006 were valproate (18 %) and lamotrigine (17 %) in pediatric-onset epilepsy and phenytoin (21 %) and carbamazepine (17 %) in adult-onset epilepsy, but starting in the 2010s, levetiracetam and lamotrigine became the most commonly prescribed ASMs in both pediatric-onset (in 2021, levetiracetam 25 %, lamotrigine 16 %) and adult-onset (in 2021, levetiracetam 27 %, lamotrigine 20 %) epilepsy. The proportion of generic ASM use increased 3.6-fold: from 23 % of prescription days in 2006 to 83 % of prescription days in 2021. The median (p25-p75) average wholesale price (AWP) per person-year increased by 102 % from $2,684 ($990-$5,509) in 2006 to $5,417 ($2,858-$12,310) in 2021. The increases were greater in absolute terms for brand-name ASMs by 419 %: $3,109 ($1,564-$5,068 in 2006 and $16,149 ($12,950-$23,377) in 2021 than for generic ASMs by 462 %: $699 ($457-$1,678) in 2006 and $3,931 ($2,618-$6,081) in 2021. The costs directly borne by the patient (copay, coinsurance, deductibles, and pharmacy processing fees) increased by 69 % for brand-name ASMs from $393 ($246-$570) in 2006 to $665 ($335-$1,308) in 2021, but decreased by 37 % for generic ASMs from $147 ($98-$213) in 2006 to $92 ($51-$141) in 2021.

CONCLUSIONS

The median cost of ASMs per person-year approximately doubled from 2006 to 2021. The increase in use of generic ASMs probably helped buffer the growing costs of ASMs. However, generic ASMs already represent 83 % of prescription days in 2021, with limited room to further contain costs by just increasing the proportion of generics.

The evolution of antiseizure medication therapy selection in adults: Is artificial intelligence -assisted antiseizure medication selection ready for prime time?

Antiseizure medications (ASMs) are the mainstay of symptomatic epilepsy treatment. The primary goal of pharmacotherapy with ASMs in epilepsy is to achieve complete seizure remission while minimizing therapy-related adverse events. Over the years, more ASMs have been introduced, with approximately 30 now in everyday use. With such a wide variety, much guidance is needed in choosing ASMs for initial therapy, subsequent replacement monotherapy, or adjunctive therapy. The specific ASMs are typically tailored by the patient's related factors, including epilepsy syndrome, age, sex, comorbidities, and ASM characteristics, including the spectrum of efficacy, pharmacokinetic properties, safety, and tolerability. Weighing these key clinical variables requires experience and expertise that may be limited. Furthermore, with this approach, patients may endure multiple trials of ineffective treatments before the most appropriate ASM is found. A more reliable way to predict response to different ASMs is needed so that the most effective and tolerated ASM can be selected. Soon, alternative approaches, such as deep machine learning (ML), could aid the individualized selection of the first and subsequent ASMs. The recognition of epilepsy as a network disorder and the integration of personalized epilepsy networks in future ML platforms can also facilitate the prediction of ASM response. Augmenting the conventional approach with artificial intelligence (AI) opens the door to personalized pharmacotherapy in epilepsy. However, more work is needed before these models are ready for primetime clinical practice.

Secular Trends in Central Nervous System-Active Polypharmacy Among Serial Cross-Sections of US Adults, 2009-2020

BACKGROUND

Data comprehensively examining trends in central nervous system (CNS)-active polypharmacy are limited. The objective of this cross-sectional study was to characterize the composition of and trends in CNS-active medication use in US adults.

METHODS

We included all participants ≥ 18 years old in the National Health and Nutrition Examination Study (NHANES), 2009-2020. The primary outcome was the percent of adults with CNS-active polypharmacy. This was defined as ≥ 3 medications among antidepressants [tricyclic, selective and serotonin-norepinephrine reuptake inhibitors (SSRIs and SNRIs), opioids, antiepileptics, antipsychotics, benzodiazepines, and nonbenzodiazepine receptor agonists ("Z-drugs")]. Secondary outcomes included prevalence of any CNS-active medication and specific medications and classes over time, and their indications. Percentages were weighted according to NHANES's nationally representative sampling frame. log binomial regressions evaluated the relative risk (RR) for each outcome, comparing the last (2017-2020) versus the first (2010-2011) survey cycle.

RESULTS

We included 34,189 adults (18.8% at least 65 years old) from five serial cross-sections (survey cycles). The prevalence of CNS-active polypharmacy was 2.1% in 2009-2010 and 2.6% in 2017-2020 [RR 1.18, 95% confidence interval (CI) 0.94-1.47]. The prevalence of CNS-active polypharmacy did not significantly change within any specific age group (e.g., age at least 65 years: RR 1.29, CI 0.74-2.24). The prevalence of any CNS-active medication was 21.0% in 2009 and 24.6% in 2017-2020 (RR] 1.12, 95% CI 1.02-1.25). A substantial increase occurred for antiepileptics (5.1-8.3%), specifically among participants aged 65 years and older (8.3-13.7%). This was largely driven by increasing gabapentin prevalence (1.4-3.6% overall; 3.3-7.9% age 65 years and older). Anticholinergic, SSRIs/SNRIs, antiepileptics, and benzodiazepines were elevated in most cycles for participants at least 65 years old compared with participants less than 65 years, and opioid use was increased in several cycles for older participants as well. Alprazolam was the most common benzodiazepine and third most common medication for anxiety/depression. Gabapentin was the most common CNS-active medication (3.6% of all participants in 2017-2020), followed by sertraline, citalopram, and acetaminophen-hydrocodone (each ~2%). The most common categories were antidepressants (13.7% in 2017-2020), followed by opioids (5.1% in 2017-2020).

CONCLUSIONS

CNS-active medications are increasingly common, particularly gabapentin, and use of any CNS-active medication increased by 12%. Numerous CNS-active classes also increased in older adults throughout the years. Increasing suboptimal medication use highlight the need for further investigation into causes for potentially inappropriate prescribing, particularly for older adults.

If the Patient Does Not Take the Medication, It Will Not Work

COGNITIVE AND BEHAVIORAL COMORBIDITIES

AN UNWANTED EFFECT OF ANTIEPILEPTIC DRUGS IN CHILDREN: Adriana Ulate-Campos, Iván Sánchez Fernández Seminars in Pediatric Neurology Volume 24, Issue 4, November 2017, Pages 320-330 Epilepsy is one of the most common neurological disorders and, despite optimally chosen and dosed antiepileptic drugs (AEDs), approximately 20%-30% of patients will continue to have seizures. Behavior and cognition are negatively impacted by seizures, but AEDs are also a major contributor to behavioral and cognitive deficits. However, the cognitive and behavioral effect of AEDs in children is insufficiently emphasized in the literature. This review summarizes the cognitive and behavioral effects of AEDs in the pediatric population with the objective of helping pediatricians and pediatric neurologists to select the AEDs with the best profile for their individual patient's needs.

Proposed anti-seizure medication combinations with rufinamide in the treatment of Lennox-Gastaut syndrome: Narrative review and expert opinion

Lennox-Gastaut syndrome (LGS) is a severe, chronic, complex form of early childhood-onset epilepsy characterized by multiple seizure types, generalized slow (≤2.5 Hz) spike-and-wave activity and other electroencephalography abnormalities, and cognitive impairment. A key treatment goal is early seizure control, and several anti-seizure medications (ASMs) are available. Due to the low success rate in achieving seizure control with monotherapy and an absence of efficacy data supporting any particular combination of ASMs for treating LGS, a rational approach to selection of appropriate polytherapy should be applied to maximize benefit to patients. Such "rational polytherapy" involves consideration of factors including safety (including boxed warnings), potential drug-drug interactions, and complementary mechanisms of action. Based on the authors' clinical experience, rufinamide offers a well-considered first adjunctive therapy for LGS, particularly in combination with clobazam and other newer agents for LGS, and may be particularly useful for reducing the frequency of tonic-atonic seizures associated with LGS.

Brand Name Versus Generic?

Changes in the Use of Brand Name and Generic Medications and Total Prescription Cost Among Medicare Beneficiaries With Epilepsy Terman SW, Lin CC, Kerr WT, DeLott LB, Callaghan BC, Burke JF. Neurology . 2022;99(8):e751-e761. doi:10.1212/WNL.0000000000200779 Background and Objective: To characterize trends in antiseizure medication (ASM) fills and total prescription costs in people with epilepsy. Methods: This was a retrospective cohort study of beneficiaries with epilepsy (ASM, plus ICD codes) in a 20% random Medicare sample, with continuous Fee-For-Service coverage (Parts A, B, and D) in 2008–2018. We summed the number of pill days and costs (adjusted to 2018 dollars) per person-year for each ASM. ASMs were categorized into brand versus generic, first versus newer generation, and enzyme inducers versus noninducers. Results: There were 77,000–133,000 beneficiaries with epilepsy per year. The most common ASM was phenytoin in 2008, which shifted to levetiracetam in 2018 (2008: phenytoin 25%, levetiracetam 14%; 2018: phenytoin 9%, levetiracetam 27%). Brand name (2008: 56%; 2018: 14%), first-generation (2008: 55%; 2018: 32%), and enzyme-inducing ASMs (2008: 44%; 2018: 24%) each decreased over time as a proportion of pill days. The number of brand pill days per person-year initially decreased (e.g., 2008: 250; 2009: 121; 2010: 96) but then plateaued (2013–2018: between 66 and 69) given a notable increase in lacosamide pill days per person (2008: 0; 2018: 20). Total brand name costs per year initially decreased 2008–2010 (2008: $150 million; 2010: $72 million) but then increased after 2010 (2018: $256 million). In 2018, brand name ASMs represented 79% of costs despite representing only 14% of pill days, a 1-year pill supply became 277% more expensive for brand name medications but 42% less expensive for generic medications over time (2008: brand ∼$2,800 versus generic ∼$800; 2018: brand ∼$10,700 versus generic ∼$460), and many common brand name ASMs cost approximately 10-fold more per pill day than their generic equivalents. Discussion: First-generation and enzyme-inducing ASMs waned from 2008 to 2018. Although brand name ASMs initially waned translating into lower costs and potentially higher value care, after 2010, brand name costs markedly increased because of increasing use of lacosamide plus a 277% increase in per-pill cost of brand name ASMs. Brand name ASMs represented a minority of prescriptions, but the majority of costs.

A framework for health equity in people living with epilepsy

Epilepsy is a disease where disparities and inequities in risk and outcomes are complex and multifactorial. While most epilepsy research to date has identified several key areas of disparities, we set out to provide a multilevel life course model of epilepsy development, diagnosis, treatment, and outcomes to highlight how these disparities represent true inequities. Our piece also presents three hypothetical cases that highlight how the solutions to address inequities may vary across the lifespan. We then identify four key domains (structural, socio-cultural, health care, and physiological) that contribute to the persistence of inequities in epilepsy risk and outcomes in the United States. Each of these domains, and their core components in the context of epilepsy, are reviewed and discussed. Further, we highlight the connection between domains and key areas of intervention to strive towards health equity. The goal of this work is to highlight these domains while also providing epilepsy researchers and clinicians with broader context of how their work fits into health equity.