Evidence map›Paper›PMID 34462911›Full record

ArticleEpilepsia2021

Antiseizure medication adherence trajectories in Medicare beneficiaries with newly treated epilepsy.

Samuel W Terman, Wesley T Kerr, Zachary A Marcum, Lu Wang, James F Burke

Open access · bronzeAbstract read
In one paragraph

Article in Epilepsia, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed, 1 pooled it
6.0field-weighted citation impact, top 4% of its field
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

18 citing papers in PubMed, 1 synthesis or guideline pooled it, 26 citations in OpenAlex.

  1. Pooled it
  2. Trial
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
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

5 authors at 3 institutions in 1 country.

Samuel W TermanDepartment of Neurology, University of Michigan,, Ann Arbor, Michigan, USA.ORCID 0000-0001-6179-9467
Wesley T KerrDepartment of Neurology, University of Michigan,, Ann Arbor, Michigan, USA.ORCID 0000-0002-5546-5951
Zachary A MarcumDepartment of Pharmacy, School of Pharmacy, University of Washington, Seattle, Washington, USA.
Lu WangDepartment of Biostatistics, University of Michigan, Ann Arbor, Michigan, USA.
James F BurkeDepartment of Neurology, University of Michigan,, Ann Arbor, Michigan, USA.
University of Michigan · USUniversity of California, Los Angeles · USUniversity of Washington · US

Funding

Michigan Institute for Clinical and Health Research (MICHR)UL1TR002240 · NCATS · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI LUMENG, JULIE C, MASHOUR, GEORGE ALEXANDER · 2017 to 2022
$54.9M
TRAINING IN CLINICAL AND BASIC NEUROSCIENCET32NS007222 · NINDS · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI Henry L Paulson · 1985 to 2026
$8.0M
Translational Neuroscience Training GrantR25NS065723 · NINDS · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI CARMICHAEL, STANLEY THOMAS · 2009 to 2023
$2.8M
Reducing Racial Disparities in Post-Stroke Disability in the ElderlyR01MD008879 · NIMHD · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI BURKE, JAMES FRANCIS, SKOLARUS, LESLI ELIZABETH · 2014 to 2018
$1.9M
Antihypertensives and the Aging BrainK76AG059929 · NIA · UNIVERSITY OF WASHINGTON · PI MARCUM, ZACHARY ADAM · 2019 to 2021
$694k
NCATS NIH HHS UL1 TR002240NIA NIH HHS K76 AG059929NIMHD NIH HHS R01 MD008879NINDS NIH HHS R25 NS065723NINDS NIH HHS T32 NS007222
6 · The paper itself

Abstract

objectiveThis study was undertaken to characterize trajectories of antiseizure medication (ASM) adherence in adults with newly treated epilepsy and to determine predictors of trajectories.

methodsThis was a retrospective cohort study using Medicare. We included beneficiaries with newly treated epilepsy (one or more ASM and none in the preceding 2 years, plus International Classification of Diseases codes) in 2010-2013. We calculated the proportion of days covered (proportion of total days with any ASM pill supply) for 8 quarters or until death. Group-based trajectory models characterized and determined predictors of trajectories.

resultsWe included 24 923 beneficiaries. Models identified four groups: early adherent (60%), early nonadherent (18%), late adherent (11%), and late nonadherent (11%). Numerous predictors were associated with being in the early nonadherent versus early adherent group: non-White race (e.g., Black, odds ratio [OR] = 1.7, 95% confidence interval [CI] = 1.5-1.8), region (e.g., South vs. Northeast: OR = 1.2, 95% CI = 1.1-1.4), and once daily initial medication (OR = 1.1, 95% CI = 1.0-1.3). Predictors associated with decreased odds of being in the early nonadherent group included older age (OR = .9 per decade, 95% CI = .9-.9), female sex (OR = .9, 95% CI = .8-1.0), full Medicaid eligibility (OR = .6, 95% CI = .4-.8), neurologist visit (OR = .6, 95% CI = .6-.7), and initial older generation ASM (OR = .6, 95% CI = .6-.7). SIGNIFICANCE: We identified four ASM adherence trajectories in individuals with newly treated epilepsy. Whereas risk factors for early nonadherence such as race or geographic region are nonmodifiable, our work highlighted a modifiable risk factor for early nonadherence: lacking a neurologist. These data may guide future interventions aimed at improving ASM adherence, in terms of both timing and target populations.

Indexed as

EpilepsyMedicareAdultAgedFemaleHumansMedication AdherenceOdds RatioRetrospective StudiesUnited Statesadherenceantiseizure medicationsepilepsygroup-based trajectory modeling

Identifiers

PMID34462911
PMCPMC8563423
OpenAlexW3196804517

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

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.