Evidence map›Paper›PMID 33550262›Full record

ArticleBMJ open2021

Medication adherence in multiple sclerosis as a potential model for other chronic diseases: a population-based cohort study.

Charity Evans, Ruth Ann Marrie, Shenzhen Yao, Feng Zhu, Randy Walld, Helen Tremlett, David Blackburn, Elaine Kingwell

Open access · goldAbstract read
In one paragraph

Article in BMJ open, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
2.1field-weighted citation impact, top 13% 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

13 citing papers in PubMed, 15 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Review
  6. Article
  7. Article
  8. Disease-Modifying Drugs for Multiple Sclerosis and Association With Survival.Neurology(R) neuroimmunology & neuroinflammation · 2022
    Article
  9. Adherence to Therapy in Patients with Multiple Sclerosis-Review.International journal of environmental research and public health · 2022
    Review
  10. Article
  11. No consensus about consensus?Neurological research and practice · 2021
    Article
  12. Characterizing the diversity of the multiple sclerosis population in Canada: A scoping review.Multiple sclerosis journal - experimental, translational and clinical
    Review
  13. 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

8 authors at 5 institutions in 1 country.

Charity EvansCollege of Pharmacy and Nutrition, University of Saskatchewan, Saskatoon, Saskatchewan, Canada charity.evans@usask.ca.ORCID 0000-0003-1409-0214
Ruth Ann MarrieInternal Medicine, University of Manitoba, Winnipeg, Manitoba, Canada.
Shenzhen YaoSaskatchewan Health Quality Council, Saskatoon, Saskatchewan, Canada.ORCID 0000-0002-7631-3404
Feng ZhuNeurology, The University of British Columbia Faculty of Medicine, Vancouver, British Columbia, Canada.
Randy WalldManitoba Centre for Health Policy, University of Manitoba, Winnipeg, Manitoba, Canada.
Helen TremlettNeurology, The University of British Columbia Faculty of Medicine, Vancouver, British Columbia, Canada.ORCID 0000-0001-5804-2535
David BlackburnCollege of Pharmacy and Nutrition, University of Saskatchewan, Saskatoon, Saskatchewan, Canada.
Elaine KingwellNeurology, The University of British Columbia Faculty of Medicine, Vancouver, British Columbia, Canada.
University of British Columbia · CAUniversity of Saskatchewan · CAManitoba Health · CASaskatchewan Health Quality Council · CAUniversity of Manitoba · CA

Funding

CIHR 363635
6 · The paper itself

Abstract

objectiveTo determine whether better medication adherence in multiple sclerosis (MS) might be due to specialised disease-modifying drug (DMD) support programmes by: (1) establishing higher adherence in MS than in other chronic diseases and (2) determining if higher adherence is associated with patient-specific or treatment-specific factors.

designRetrospective cohort study with data from 1 January 1996 to 31 December 2015.

settingPopulation-based health administrative data from three Canadian provinces.

participantsIndividual cohorts were created using validated case definitions for MS, epilepsy, Parkinson's disease (PD) and rheumatoid arthritis (RA). Subjects were included if they received ≥1 dispensation for a disease-related drug between 1 January 1997 and 31 December 2014.

main outcome measuresProportion of subjects with optimal adherence (≥80%) measured by the medication possession ratio 1 year after the index date (first dispensation of disease-related drug).

results126 478 subjects were included in the primary analysis (MS, n=6271; epilepsy, n=55 739; PD, n=21 304; RA, n=43 164). Subjects with epilepsy (adjusted OR, aOR 0.29; 95% CI 0.19 to 0.45), PD (aOR 0.42; 95% CI 0.29 to 0.63) or RA (aOR 0.26; 95% CI 0.19 to 0.35) were less likely to have optimal 1-year adherence compared with subjects with MS. Within the MS cohort, adherence was higher for DMD than for chronic-use non-MS medications, and no consistent patient-related predictors of adherence were observed across all four non-MS medication classes, including having optimal adherence to DMD.

conclusionsSubjects with MS were significantly more likely to have optimal 1-year adherence than subjects with epilepsy, RA and PD, and optimal adherence appears related to treatment-specific factors rather than patient-related factors. This supports the hypothesis that higher adherence to the MS DMDs could be due to the specialised support programmes; these programmes may serve as a model for use in other chronic conditions.

Indexed as

Multiple SclerosisCanadaChronic DiseaseCohort StudiesHumansMedication AdherenceRetrospective Studiesepidemiologygeneral medicine (see internal medicine)multiple sclerosis

Identifiers

PMID33550262
PMCPMC7925877
OpenAlexW3126716594

What OpenQuestion holds

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LicenceCC BY-NC
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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.