Evidence map›Paper›PMID 36050646›Full record

ArticleBMC neurology2022

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

Samuel W Terman, Joshua D Niznik, Geertruida Slinger, Willem M Otte, Kees P J Braun, Carole E Aubert, Wesley T Kerr, Cynthia M Boyd, James F Burke

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In one paragraph

Article in BMC neurology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed.

  1. Article
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  3. Observational
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  7. Predictors of high- versus low-intensity first-line multiple sclerosis treatments.Multiple sclerosis journal - experimental, translational and clinical
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Samuel W TermanDepartment of Neurology, University of Michigan, Ann Arbor, MI, 48109, USA.
Joshua D NiznikDivision of Geriatric Medicine, Center for Aging and Health, School of Medicine, University of North Carolina At Chapel Hill, Chapel Hill, NC, 27599, USA.
Geertruida SlingerDepartment of Child Neurology, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands.
Willem M OtteDepartment of Child Neurology, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands.
Kees P J BraunDepartment of Child Neurology, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands.
Carole E AubertDepartment of General Internal Medicine, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland. carole.aubert@biham.unibe.ch.
Wesley T KerrDepartment of Neurology, University of Michigan, Ann Arbor, MI, 48109, USA.
Cynthia M BoydDivision of Geriatric Medicine and Gerontology, Johns Hopkins University School of Medicine, Baltimore, MD, 21224, USA.
James F BurkeDepartment of Neurology, the Ohio State University, Columbus, OH, 43210, USA.

Funding

Deprescribing Bisphosphonates in Older Nursing Home Residents with DementiaK08AG071794 · NIA · UNIV OF NORTH CAROLINA CHAPEL HILL · PI NIZNIK, JOSHUA DAVID · 2021 to 2025
$724k
NIA NIH HHS K08 AG071794
6 · The paper itself

Abstract

backgroundFor 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.

methodsThis 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.

resultsAmong 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).

conclusionsSustained 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.

Indexed as

EpilepsyMedicareAgedAnticonvulsantsCohort StudiesHumansIncidenceRetrospective StudiesUnited StatesAnticonvulsantsAdministrative claimsAntiseizure medicationsDiscontinuationEpilepsy

Identifiers

PMID36050646
PMCPMC9434838

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.