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Comparative Effectiveness Research of Disease-Modifying Therapies for the Management of Multiple Sclerosis: Analysis of a Large Health Insurance Claims Database

Overview of attention for article published in Neurology and Therapy, February 2017
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (85th percentile)
  • High Attention Score compared to outputs of the same age and source (83rd percentile)

Mentioned by

blogs
1 blog
policy
1 policy source
twitter
3 X users
facebook
1 Facebook page

Citations

dimensions_citation
65 Dimensions

Readers on

mendeley
77 Mendeley
Title
Comparative Effectiveness Research of Disease-Modifying Therapies for the Management of Multiple Sclerosis: Analysis of a Large Health Insurance Claims Database
Published in
Neurology and Therapy, February 2017
DOI 10.1007/s40120-017-0064-x
Pubmed ID
Authors

Aaron Boster, Jacqueline Nicholas, Ning Wu, Wei-Shi Yeh, Monica Fay, Michael Edwards, Ming-Yi Huang, Andrew Lee

Abstract

Limited data are available on the real-world effectiveness of newer oral disease-modifying therapies (DMTs) in multiple sclerosis. The purpose of this study was to retrospectively compare the real-world effectiveness of dimethyl fumarate (DMF), fingolimod, teriflunomide, and injectable DMTs in routine clinical practice based on US claims data. Patients newly-initiating DMF, interferon beta (IFNβ), glatiramer acetate (GA), teriflunomide, or fingolimod in 2013 were identified in the Truven MarketScan Commercial Claims Databases (N = 6372). Relapse episodes were identified based on a published claim-based algorithm and used to determine the annualized relapse rate (ARR) for the year before and after initiating therapy. Poisson and negative binomial regression was used to determine the adjusted incidence rate ratio (IRR) for each therapy relative to DMF. Significant ARR reductions in the year after initiating therapy were reported for DMF and fingolimod (P < 0.0001). Compared with DMF, the adjusted IRR (95% CI) for relapse in the year after initiating therapy was 1.27 (1.10-1.46) for IFNβ, 1.34 (1.17-1.53) for GA, 1.23 (1.05-1.45) for teriflunomide, and 1.03 (0.88-1.21) for fingolimod. Results were consistent across subgroup and sensitivity analyses. These real-world data suggest DMF and fingolimod have similar effectiveness and demonstrate superior effectiveness to IFNβ, GA, and teriflunomide. Biogen, Cambridge, MA, USA.

X Demographics

X Demographics

The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 77 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 77 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 16 21%
Student > Ph. D. Student 12 16%
Student > Master 12 16%
Student > Doctoral Student 5 6%
Other 5 6%
Other 11 14%
Unknown 16 21%
Readers by discipline Count As %
Medicine and Dentistry 21 27%
Neuroscience 8 10%
Agricultural and Biological Sciences 5 6%
Immunology and Microbiology 5 6%
Pharmacology, Toxicology and Pharmaceutical Science 5 6%
Other 12 16%
Unknown 21 27%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 14. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 27 August 2019.
All research outputs
#2,224,739
of 22,953,506 outputs
Outputs from Neurology and Therapy
#53
of 420 outputs
Outputs of similar age
#44,388
of 307,002 outputs
Outputs of similar age from Neurology and Therapy
#1
of 6 outputs
Altmetric has tracked 22,953,506 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 90th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 420 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 12.4. This one has done well, scoring higher than 87% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 307,002 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 85% of its contemporaries.
We're also able to compare this research output to 6 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them