Evidence map›Paper›PMID 36578311›Full record

ArticleClinicoEconomics and outcomes research : CEOR2022

Medication Adherence and Healthcare Utilization in Relapsing-Remitting Multiple Sclerosis Patients Using Teriflunomide.

Nupur Greene, Keiko Higuchi, Katalin Bognar, Eunice Chang, Michael S Broder

Open access · goldAbstract read
In one paragraph

Article in ClinicoEconomics and outcomes research : CEOR, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.3field-weighted citation impact, top 42% 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

2 citing papers in PubMed, 3 citations in OpenAlex.

  1. Article
  2. 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 2 institutions in 1 country.

Nupur GreeneNeurology & Immunology (N&I), Sanofi, Cambridge, MA, USA.
Keiko HiguchiNeurology & Immunology (N&I), Sanofi, Cambridge, MA, USA.
Katalin BognarReal World Evidence, PHAR (Partnership for Health Analytic Research), Beverly Hills, CA, USA.ORCID 0000-0001-8357-8569
Eunice ChangReal World Evidence, PHAR (Partnership for Health Analytic Research), Beverly Hills, CA, USA.ORCID 0000-0003-0177-6153
Michael S BroderReal World Evidence, PHAR (Partnership for Health Analytic Research), Beverly Hills, CA, USA.ORCID 0000-0002-2049-5536
Partnership for Health Analytic Research · USSanofi (United States) · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: Multiple sclerosis (MS) is a costly, immune-mediated disease of the central nervous system. Most patients have relapsing-remitting MS (RRMS) for which disease-modifying therapies (DMTs) provide an effective treatment option by reducing relapse rates. However, adherence to DMTs is suboptimal. This study examines the association between adherence to teriflunomide and clinical and healthcare utilization outcomes. Patients and Methods: Patients with RRMS who started treatment with teriflunomide between 1/1/2018 and 12/31/2019 were analyzed using IQVIA PharMetrics Results: Among the 922 RRMS patients identified, 534 (57.9%) were highly adherent to teriflunomide, while 249 (27.0%) had PDC ≤0.5. The two groups were not statistically different in terms of demographic characteristics and comorbidities; however, poorly adherent patients were more likely to have emergency department (ED) or inpatient visits during baseline (36.9% versus 26.8%, Conclusion: High adherence to teriflunomide was found to be associated with fewer relapses and lower healthcare utilization among patients with RRMS.

Indexed as

administrative claims analysisdisease modifying therapiesmedication compliancepercent of days covered

Identifiers

PMID36578311
PMCPMC9791931
OpenAlexW4312188900

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.