Evidence map›Paper›PMID 34893556›Full record

ArticleNeurology2022

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

Samuel W Terman, Wesley T Kerr, Carole E Aubert, Chloe E Hill, Zachary A Marcum, James F Burke

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Neurology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

12 citing papers in PubMed.

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  8. Pre-stroke Adherence to Hypertension Medications in a Bi-racial United States Stroke Belt.High blood pressure & cardiovascular prevention : the official journal of the Italian Society of Hypertension · 2023
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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

6 authors.

Samuel W TermanFrom the Department of Neurology (S.W.T., W.T.K., C.E.H., J.F.B.), and Institute for Healthcare Policy and Innovation (S.W.T., C.E.H., J.F.B.), University of Michigan, Ann Arbor; Department of Neurology (W.T.K.), David Geffen School of Medicine at UCLA, Los Angeles, CA; Department of General Internal Medicine (C.E.A.), Bern University Hospital, and Institute of Primary Health Care (BIHAM) (C.E.A.), University of Bern, Switzerland; and Department of Pharmacy (Z.A.M.), School of Pharmacy, University of Washington, Seattle. sterman@umich.edu.
Wesley T KerrFrom the Department of Neurology (S.W.T., W.T.K., C.E.H., J.F.B.), and Institute for Healthcare Policy and Innovation (S.W.T., C.E.H., J.F.B.), University of Michigan, Ann Arbor; Department of Neurology (W.T.K.), David Geffen School of Medicine at UCLA, Los Angeles, CA; Department of General Internal Medicine (C.E.A.), Bern University Hospital, and Institute of Primary Health Care (BIHAM) (C.E.A.), University of Bern, Switzerland; and Department of Pharmacy (Z.A.M.), School of Pharmacy, University of Washington, Seattle.ORCID http://orcid.org/0000-0002-5546-5951
Carole E AubertFrom the Department of Neurology (S.W.T., W.T.K., C.E.H., J.F.B.), and Institute for Healthcare Policy and Innovation (S.W.T., C.E.H., J.F.B.), University of Michigan, Ann Arbor; Department of Neurology (W.T.K.), David Geffen School of Medicine at UCLA, Los Angeles, CA; Department of General Internal Medicine (C.E.A.), Bern University Hospital, and Institute of Primary Health Care (BIHAM) (C.E.A.), University of Bern, Switzerland; and Department of Pharmacy (Z.A.M.), School of Pharmacy, University of Washington, Seattle.
Chloe E HillFrom the Department of Neurology (S.W.T., W.T.K., C.E.H., J.F.B.), and Institute for Healthcare Policy and Innovation (S.W.T., C.E.H., J.F.B.), University of Michigan, Ann Arbor; Department of Neurology (W.T.K.), David Geffen School of Medicine at UCLA, Los Angeles, CA; Department of General Internal Medicine (C.E.A.), Bern University Hospital, and Institute of Primary Health Care (BIHAM) (C.E.A.), University of Bern, Switzerland; and Department of Pharmacy (Z.A.M.), School of Pharmacy, University of Washington, Seattle.
Zachary A MarcumFrom the Department of Neurology (S.W.T., W.T.K., C.E.H., J.F.B.), and Institute for Healthcare Policy and Innovation (S.W.T., C.E.H., J.F.B.), University of Michigan, Ann Arbor; Department of Neurology (W.T.K.), David Geffen School of Medicine at UCLA, Los Angeles, CA; Department of General Internal Medicine (C.E.A.), Bern University Hospital, and Institute of Primary Health Care (BIHAM) (C.E.A.), University of Bern, Switzerland; and Department of Pharmacy (Z.A.M.), School of Pharmacy, University of Washington, Seattle.
James F BurkeFrom the Department of Neurology (S.W.T., W.T.K., C.E.H., J.F.B.), and Institute for Healthcare Policy and Innovation (S.W.T., C.E.H., J.F.B.), University of Michigan, Ann Arbor; Department of Neurology (W.T.K.), David Geffen School of Medicine at UCLA, Los Angeles, CA; Department of General Internal Medicine (C.E.A.), Bern University Hospital, and Institute of Primary Health Care (BIHAM) (C.E.A.), University of Bern, Switzerland; and Department of Pharmacy (Z.A.M.), School of Pharmacy, University of Washington, Seattle.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUND AND

objectiveThe objectives of this study were to compare adherence to antiseizure medications (ASMs) vs non-ASMs among individuals with epilepsy, to assess the degree to which variation in adherence is due to differences between individuals vs between medication classes among individuals with epilepsy, and to compare adherence in individuals with vs without epilepsy.

methodsThis was a retrospective cohort study using Medicare. We included beneficiaries with epilepsy (≥1 ASM, plus ICD-9-CM diagnostic codes) and a 20% random sample without epilepsy. Adherence for each medication class was measured by the proportion of days covered (PDC) in 2013 to 2015. We used Spearman correlation coefficients, Cohen κ statistics, and multilevel logistic regressions.

resultsThere were 83,819 beneficiaries with epilepsy. Spearman correlation coefficients between ASM PDCs and each of the 5 non-ASM PDCs ranged from 0.44 to 0.50; Cohen κ ranged from 0.33 to 0.38; and within-person differences between the PDC of each ASM minus the PDC of each non-ASM were all statistically significant ( DISCUSSION: Among individuals with epilepsy, ASM adherence and non-ASM adherence were moderately correlated, half of the variation in adherence was due to between-person rather than between-medication differences, adjusted adherence was slightly lower for ASMs than several non-ASMs, and epilepsy was associated with a quite small increase in adherence to non-ASMs. Nonadherence to ASMs may provide an important cue to the clinician to inquire about adherence to other potentially life-prolonging medications as well. Although efforts should focus on improving ASM adherence, patient-level rather than purely medication-specific behaviors are also critical to consider when developing interventions to optimize adherence.

Identifiers

PMID34893556
PMCPMC8793102

What OpenQuestion holds

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Registered trials

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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.