↓ Skip to main content

Modeling Approaches in Cost-Effectiveness Analysis of Disease-Modifying Therapies for Relapsing–Remitting Multiple Sclerosis: An Updated Systematic Review and Recommendations for Future Economic…

Overview of attention for article published in PharmacoEconomics, July 2018
Altmetric Badge

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 (84th percentile)
  • Good Attention Score compared to outputs of the same age and source (78th percentile)

Mentioned by

policy
2 policy sources
twitter
12 X users
facebook
1 Facebook page

Citations

dimensions_citation
17 Dimensions

Readers on

mendeley
53 Mendeley
Title
Modeling Approaches in Cost-Effectiveness Analysis of Disease-Modifying Therapies for Relapsing–Remitting Multiple Sclerosis: An Updated Systematic Review and Recommendations for Future Economic Evaluations
Published in
PharmacoEconomics, July 2018
DOI 10.1007/s40273-018-0683-9
Pubmed ID
Authors

Luis Hernandez, Malinda O’Donnell, Maarten Postma

Abstract

Numerous cost-effectiveness analyses (CEAs) of disease-modifying therapies (DMTs) for relapsing-remitting multiple sclerosis (RRMS) have been published in the last three decades. Literature reviews of the modeling methods and results from these CEAs have also been published. The last literature review that focused on modeling methods, without country or time horizon in the inclusion criteria, included studies published up to 2012. Since then, new DMTs have become available, and new models and data sources have been used to assess their cost effectiveness. The aim of this systematic review was to provide a detailed and comprehensive description of the relevant aspects of economic models used in CEAs of DMTs for RRMS, to understand how these models have progressed from recommendations provided in past reviews, what new approaches have been developed, what issues remain, and how they could be addressed. EMBASE, MEDLINE, Cochrane Central Register of Controlled Trials (CENTRAL), the National Health System (NHS) Economic Evaluations Database, the Health Technology Assessment (HTA) Database, and EconLit were searched for cost-effectiveness studies of DMTs for RRMS that used decision-analytic models, published in English between 1 January 2012 and 24 December 2017. The inclusion criteria were as follows: being a full economic evaluation, a decision-analytic model was used, the target population concerned adult patients with RRMS, and being available in full-text format. Studies were not excluded based on the methodological quality. The background information of the included studies, as well as specific information on the components of the economic models related to the areas of recommendation from previous reviews were extracted. Twenty-three studies from ten countries were included. The model structure of these studies has converged over time, characterizing the course of disease progression in terms of changes in disability and the occurrence of relapses over time. Variations were found in model approach; data sources for the natural course of the disease and comparative efficacy between DMTs; number of lines of treatment modeled; long-term efficacy waning and treatment discontinuation assumptions; type of withdrawal; and criteria for selecting adverse events. Main areas for improvement include using long-term time horizons and societal perspective; reporting relevant health outcomes; conducting scenario analyses using different sources of natural history and utility values; and reporting how the model was validated. The structure of economic models used in CEAs of DMTs for RRMS has converged over time. However, variation remains in terms of model approach, inputs, and assumptions. Though some recommendations from previous reviews have been incorporated in later models, areas for improvement remain.

X Demographics

X Demographics

The data shown below were collected from the profiles of 12 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 53 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 53 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 9 17%
Student > Ph. D. Student 9 17%
Researcher 8 15%
Student > Bachelor 4 8%
Student > Doctoral Student 1 2%
Other 5 9%
Unknown 17 32%
Readers by discipline Count As %
Medicine and Dentistry 7 13%
Economics, Econometrics and Finance 6 11%
Neuroscience 5 9%
Nursing and Health Professions 4 8%
Pharmacology, Toxicology and Pharmaceutical Science 2 4%
Other 7 13%
Unknown 22 42%
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 30 January 2020.
All research outputs
#2,618,143
of 25,299,129 outputs
Outputs from PharmacoEconomics
#222
of 1,992 outputs
Outputs of similar age
#51,294
of 334,681 outputs
Outputs of similar age from PharmacoEconomics
#8
of 32 outputs
Altmetric has tracked 25,299,129 research outputs across all sources so far. Compared to these this one has done well and is in the 89th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,992 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.6. This one has done well, scoring higher than 88% 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 334,681 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 84% of its contemporaries.
We're also able to compare this research output to 32 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 78% of its contemporaries.