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Impact on total population health and societal cost, and the implication on the actual cost-effectiveness of including tumour necrosis factor-α antagonists in management of ankylosing spondylitis: a…

Overview of attention for article published in Cost Effectiveness and Resource Allocation, October 2015
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Title
Impact on total population health and societal cost, and the implication on the actual cost-effectiveness of including tumour necrosis factor-α antagonists in management of ankylosing spondylitis: a dynamic population modelling study
Published in
Cost Effectiveness and Resource Allocation, October 2015
DOI 10.1186/s12962-015-0044-x
Pubmed ID
Authors

An Tran-Duy, Annelies Boonen, Mart A. F. J. van de Laar, Johan L. Severens

Abstract

Sequential treatment of ankylosing spondylitis (AS) that includes tumour necrosis factor-α antagonists (anti-TNF agents) has been applied in most of the Western countries. Existing cost-effectiveness (CE) models almost exclusively presented the incremental CE of anti-TNF agents using a closed cohort while budget impact studies are mainly lacking. Notwithstanding, information on impact on total population health and societal budget as well as on actual incremental CE for a given decision time span are important for decision makers. This study aimed at quantifying, for different decision time spans starting from January 1, 2014 in the Dutch society, (1) impact of sequential drug treatment strategies without and with inclusion of anti-TNF agents (Strategies 1 and 2, respectively) on total population health and societal cost, and (2) the actual incremental CE of Strategy 2 compared to Strategy 1. Dynamic population modelling was used to capture total population health and cost, and the actual incremental CE. Distinguishing the prevalent AS population on January 1, 2014 and the incident AS cohorts in the subsequent 20 years, the model tracked individually an actual number of AS patients until death or end of the simulation time. During the simulation, data on patient characteristics, history of drug use, costs and health at discrete time points were generated. In Strategy 1, five nonsteroidal anti-inflammatory drugs (NSAIDs) were available but anti-TNF agents withdrawn. In Strategy 2, five NSAIDs and two anti-TNF agents continued to be available. The predicted size of the prevalent AS population in the Dutch society varied within the range of 67,145-69,957 with 44-46 % of the patients receiving anti-TNF agents over the period 2014-2034. The use of anti-TNF agents resulted in an increase in the annual drug costs (168.54-205.28 million Euros), but at the same time caused a decrease in the annual productivity costs (12.58-31.21 million Euros) and in annual costs of healthcare categories other than drugs (7.23-11.90 million Euros). Incremental cost (Euros) per QALY gained in Strategy 2 compared to Strategy 1 corresponding to decision time spans of 5, 10, 15 and 20 years improved slightly from 75,379 to 67,268, 63,938 and 61,129, respectively. At willingness-to-pay thresholds of 118,656, 112,067, 110,188 and 110,512 Euros, it was 99 % certain that Strategy 2 was cost-effective for decision time spans of 5, 10, 15 and 20, respectively. Using the dynamic population approach, the present model can project real-time data to inform a healthcare system decision that affects all actual number of AS patients eligible for anti-TNF agents within different decision time spans. The predicted total population costs of different categories in the present study can help plan the organization of the healthcare resources based on the national budget for the disease.

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The data shown below were collected from the profile of 1 X user 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 36 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 3%
Unknown 35 97%

Demographic breakdown

Readers by professional status Count As %
Researcher 9 25%
Student > Master 7 19%
Student > Ph. D. Student 7 19%
Student > Bachelor 3 8%
Student > Doctoral Student 1 3%
Other 4 11%
Unknown 5 14%
Readers by discipline Count As %
Medicine and Dentistry 8 22%
Agricultural and Biological Sciences 5 14%
Pharmacology, Toxicology and Pharmaceutical Science 3 8%
Economics, Econometrics and Finance 3 8%
Computer Science 2 6%
Other 7 19%
Unknown 8 22%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 09 October 2015.
All research outputs
#18,800,225
of 23,299,593 outputs
Outputs from Cost Effectiveness and Resource Allocation
#360
of 433 outputs
Outputs of similar age
#201,476
of 279,239 outputs
Outputs of similar age from Cost Effectiveness and Resource Allocation
#4
of 5 outputs
Altmetric has tracked 23,299,593 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 433 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.1. This one is in the 7th percentile – i.e., 7% of its peers scored the same or lower than it.
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 279,239 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 15th percentile – i.e., 15% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 5 others from the same source and published within six weeks on either side of this one.