Adherence to Antiseizure vs Other Medications Among US Medicare Beneficiaries With and Without Epilepsy

Technological Vanguard: the outstanding performance of the LTY-CNN model for the early prediction of epileptic seizures

BACKGROUND

Epilepsy is a common neurological disorder that affects approximately 60 million people worldwide. Characterized by unpredictable neural electrical activity abnormalities, it results in seizures with varying intensity levels. Electroencephalography (EEG), as a crucial technology for monitoring and predicting epileptic seizures, plays an essential role in improving the quality of life for people with epilepsy.

METHOD

This study introduces an innovative deep learning model, a lightweight triscale yielding convolutional neural network" (LTY-CNN), that is specifically designed for EEG signal analysis. The model integrates a parallel convolutional structure with a multihead attention mechanism to capture complex EEG signal features across multiple scales and enhance the efficiency achieved when processing time series data. The lightweight design of the LTY-CNN enables it to maintain high performance in environments with limited computational resources while preserving the interpretability and maintainability of the model.

RESULTS

In tests conducted on the SWEC-ETHZ and CHB-MIT datasets, the LTY-CNN demonstrated outstanding performance. On the SWEC-ETHZ dataset, the LTY-CNN achieved an accuracy of 99.9%, an area under the receiver operating characteristic curve (AUROC) of 0.99, a sensitivity of 99.9%, and a specificity of 98.8%. Furthermore, on the CHB-MIT dataset, it recorded an accuracy of 99%, an AUROC of 0.932, a sensitivity of 99.1%, and a specificity of 93.2%. These results signify the remarkable ability of the LTY-CNN to distinguish between epileptic seizures and nonseizure events. Compared to other existing epilepsy detection classifiers, the LTY-CNN attained higher accuracy and sensitivity.

CONCLUSION

The high accuracy and sensitivity of the LTY-CNN model demonstrate its significant potential for epilepsy management, particularly in terms of predicting and mitigating epileptic seizures. Its value in personalized treatments and widespread clinical applications reflects the broad prospects of deep learning in the health care sector. This also highlights the crucial role of technological innovation in enhancing the quality of life experienced by patients.

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.

Perampanel's forgiveness factor in a variable medication adherence paradigm in a rat model of chronic epilepsy

BACKGROUND

Poor medication adherence contributes to increased morbidity and mortality in patients with epilepsy and may be under-addressed in clinical practice. Ethical concerns make it impossible to study the impact of medication nonadherence in clinical trials, but our previous work emphasizes the importance of using preclinical approaches to address these questions. With over 30 clinically available antiseizure medicines (ASM's), it remains an important question to understand the relationship between poor adherence and seizure incidence across mechanistically distinct ASM's, including the broad-spectrum ASM, perampanel (PER).

METHODS

We formulated PER into chow pellets to deliver to rats in a 100% fully adherent or 50% variable nonadherent paradigm via our novel automated medication-in-food delivery system. Chronic oral dosing was initiated in male rats with chronic epilepsy while monitoring 24/7 for videoEEG evidence of seizures during a 4-week placebo baseline and 4-week treatment phase. PER concentrations were monitored in plasma at 1-week intervals and correlated with degree of seizure control. The relationship between missed doses and extended patterns of nonadherence were correlated with breakthrough seizures.

RESULTS

Fully adherent rats demonstrated a median reduction in seizure frequency of 50%, whereas nonadherent rats had a median increase of 54%. Plasma concentrations of PER were stable over the 4-week treatment period in both fully adherent and nonadherent groups, with levels being twice as high in fully adherent animals. There was no correlation between a single missed dose or series of missed doses and the incidence of breakthrough seizures. However, those animals in the nonadherent group that received PER for every meal during a 24-h period had a reduced likelihood of seizure incidence.

CONCLUSIONS

If our preclinical data is supported in the clinic, PER's favorable pharmacokinetic profile in humans, combined with a lowered risk of breakthrough seizures suggests that it may provide a certain forgiveness factor if a dose is missed within a 24-h window.

Making Up Missed Anti-Seizure Medication Doses: Double or Nothing?

Handling Delayed or Missed Dose of Antiseizure Medications: A Model-Informed Individual Remedial Dosing Li ZR, Wang CY, Lin WW, Chen YT, Liu XQ, Jiao Z. Neurology . 2023;100(9):e921-e931. doi:10.1212/WNL.0000000000201604 Background and Objectives: Antiseizure medications are the major treatment modality for patients with epilepsy. Delayed or missed doses are common during long-term or lifelong anti-epilepsy treatment. This study aims to explore optimal individualized remedial dosing regimens for delayed or missed doses of 11 commonly used antiseizure medications. Methods: In order to explore remedial dosing regimens, Monte Carlo simulation was employed based on previously identified and published population pharmacokinetic models. Six remedial strategies for delayed or missed doses were investigated. The deviation time outside the individual therapeutic range was used to evaluate each remedial regimen. The influences of patients’ demographics, concomitant medication, and scheduled dosing intervals on remedial regimens were assessed. RxODE and Shiny in R were employed to perform Monte Carlo simulation and recommend individual remedial regimens. Results: The recommended remedial regimens were highly correlated to delayed time, scheduled dosing interval, and half-life of the antiseizure medication. Moreover, the optimal remedial regimens for pediatric and adult patients were different. The renal function, along with concomitant medication that affect the clearance of the antiseizure medication, may also influence the remedial regimens. A web-based dashboard was developed to provide individualized remedial regimens for the delayed or missed dose, and a user-defined module with all parameters that could be defined flexibly by the user was also built. Discussion: Monte Carlo simulation based on population pharmacokinetic models may provide a rational approach to propose remedial regimens for delayed or missed doses of antiseizure medications in pediatric and adult patients with epilepsy.

Pre-stroke Adherence to Hypertension Medications in a Bi-racial United States Stroke Belt

INTRODUCTION

Blood pressure is not optimally reduced in 3 of 4 patients with hypertension (HTN) in the United States.

AIM

We analyzed for factors associations with premorbid non-adherence to HTN medications in acute stroke patients.

METHODS

This cross-sectional study included 225 acute stroke patients with self-reported adherence to HTM medications in a stroke registry in the Southeastern United States. We defined medication non-adherence as < 90% of prescribed. Logistic regression analyzed demographic and socioeconomic factors for prediction of adherence.

RESULTS

There were 145 (64%) patients with adherence and 80 (36%) with non-adherence. The likelihood of adherence to HTN medications was decreased among black patients, OR 0.49 (95% CI 0.26-0.93), p = 0.03, and those without health insurance, OR 0.29 (95% CI 0.13-0.64), p = 0.002. Specific reasons for non-adherence were high medication cost in 26 (33%), side effects in 8 (10%), and other unspecified reasons in 46 (58%) patients.

CONCLUSION

In this study, adherence to HTN medications was significantly lower among black patients and those without health insurance.

Deep Thoughts—Predicting Initial Treatment Response in Newly Diagnosed Epilepsy

[Box: see text]

Incidence of and predictors for antiseizure medication gaps in Medicare beneficiaries with epilepsy: a retrospective cohort study

BACKGROUND

For the two-thirds of patients with epilepsy who achieve seizure remission on antiseizure medications (ASMs), patients and clinicians must weigh the pros and cons of long-term ASM treatment. However, little work has evaluated how often ASM discontinuation occurs in practice. We describe the incidence of and predictors for sustained ASM fill gaps to measure discontinuation in individuals potentially eligible for ASM withdrawal.

METHODS

This was a retrospective cohort of Medicare beneficiaries. We included patients with epilepsy by requiring International Classification of Diseases codes for epilepsy/convulsions plus at least one ASM prescription each year 2014-2016, and no acute visit for epilepsy 2014-2015 (i.e., potentially eligible for ASM discontinuation). The main outcome was the first day of a gap in ASM supply (30, 90, 180, or 360 days with no pills) in 2016-2018. We displayed cumulative incidence functions and identified predictors using Cox regressions.

RESULTS

Among 21,819 beneficiaries, 5191 (24%) had a 30-day gap, 1753 (8%) had a 90-day gap, 803 (4%) had a 180-day gap, and 381 (2%) had a 360-day gap. Predictors increasing the chance of a 180-day gap included number of unique medications in 2015 (hazard ratio [HR] 1.03 per medication, 95% confidence interval [CI] 1.01-1.05) and epileptologist prescribing physician (≥25% of that physician's visits for epilepsy; HR 2.37, 95% CI 1.39-4.03). Predictors decreasing the chance of a 180-day gap included Medicaid dual eligibility (HR 0.75, 95% CI 0.60-0.95), number of unique ASMs in 2015 (e.g., 2 versus 1: HR 0.37, 95% CI 0.30-0.45), and greater baseline adherence (> 80% versus ≤80% of days in 2015 with ASM pill supply: HR 0.38, 95% CI 0.32-0.44).

CONCLUSIONS

Sustained ASM gaps were rarer than current guidelines may suggest. Future work should further explore barriers and enablers of ASM discontinuation to understand the optimal discontinuation rate.

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

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 vs generic, first vs newer generation, and enzyme inducers vs 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 vs generic ∼$800; 2018: brand ∼$10,700 vs 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.

Antiseizure medication treatment pathways in US Medicare beneficiaries with newly treated epilepsy

Objective

This study was undertaken to characterize antiseizure medication (ASM) treatment pathways in Medicare beneficiaries with newly treated epilepsy.

Methods

This was a retrospective cohort study using Medicare claims. Medicare is the United States' federal health insurance program for people aged 65 years and older plus younger people with disabilities or end‐stage renal disease. We included beneficiaries with newly treated epilepsy (International Classification of Diseases codes for epilepsy/convulsions 2014–2017, no ASM in the previous 2 years). We displayed the sequence of ASM fills using sunburst plots overall, then stratified by mood disorder, age, and neurologist prescriber. We tabulated drug costs for each pathway.

Results

We included 21 458 beneficiaries. Levetiracetam comprised the greatest number of pill days (56%), followed by gabapentin (11%) and valproate (8%). There were 22 288 unique treatment pathways. The most common pathways were levetiracetam monotherapy (43%), gabapentin monotherapy (10%), and valproate monotherapy (5%). Gabapentin was the most common second‐ and third‐line ASM. Whereas only 2% of pathways involved first‐line lacosamide, those pathways accounted for 19% of cost. Gabapentin and valproate use was increased and levetiracetam use was decreased in beneficiaries with mood disorders compared to beneficiaries without mood disorders. Levetiracetam use was increased and gabapentin, valproate, lamotrigine, and topiramate use was decreased in beneficiaries aged >65 years compared with those aged 65 years or less. Lamotrigine, levetiracetam, and lacosamide use was increased and gabapentin use was decreased in beneficiaries whose initial prescriber was a neurologist compared to those whose prescriber was not a neurologist.

Significance

Levetiracetam monotherapy was the most common pathway, although substantial heterogeneity existed. Lacosamide accounted for a small percentage of ASMs but a disproportionately large share of cost. Neurologists were more likely to prescribe lamotrigine compared with nonneurologists, and lamotrigine was prescribed far less frequently than may be endorsed by guidelines. Future work may explore patient‐ and physician‐driven factors underlying ASM choices.