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Squinting Through Layers of Fog: Assessing the Cost Effectiveness of Treatments for Multiple Sclerosis

Applied Health Economics and Health Policy volume 11, pages 331–341 (2013)Cite this article

Abstract

Background

Multiple sclerosis (MS) is a chronic neurological disorder, which can lead to a wide range of disabling symptoms. The condition has a significant negative impact on health-related quality of life, and the economic cost of the disease is substantial. Decision-making regarding treatments for MS, and particularly disease-modifying interventions, has been hampered by limitations in the data and evaluative framework for assessing their cost effectiveness. Whilst attention has been drawn to these weaknesses, the scope and extent of the challenges in this area have not been fully set out to date.

Aims

The aims of this review were to identify all published economic evaluations of MS treatments in order to provide a statement on the scope and characteristics of the cost-effectiveness literature in the area of MS and to provide a basis on which to suggest practical recommendations for future research to aid decision-making.

Method

A systematic search was undertaken to identify economic evaluations of treatments for people with MS published in English up to December 2011. Included studies were reviewed to provide a comprehensive description of the characteristics of the currently applied framework for cost effectiveness in MS, with the following key methodological components considered: methods for estimating disease progression, the impact of treatment and health outcomes and costs associated with MS.

Results

Thirty-seven papers were identified. Most studies (n = 32) were model-based evaluations of disease-modifying drugs. All models used disability stages defined by the Expanded Disability Status Scale (EDSS) to characterise disease progression, and the impact of treatment was based on data from clinical trials and epidemiological cohorts. Outcomes were primarily based on quality-adjusted life-years (n = 22) and/or related to relapse (n = 14). Estimates for health state utility values (HSUVs), costs and the impact of treatment on the course of MS varied considerably between studies, depending on the data sources used and the methods used to incorporate data into models. The scope of the studies was narrow, with a sparsity of economic evaluations of symptomatic and/or non-pharmacological interventions; exclusion of direct non-medical, indirect and informal care costs from analyses; and a narrow view of the potential impact of treatment, concentrating on disability, according to the EDSS, and relapses. In addition, there were issues concerning how to capture losses in HSUVs due to relapses in a way that reflects their salience to people with MS, the wide variation in costs and outcomes from different sources and from potentially unrepresentative samples and modelling disease progression from natural history data from over 30 years ago.

Conclusion

There are many complexities for those designing and reporting cost-effectiveness studies of treatments for MS. Analysts, and ultimately decision makers, face multiple data and methodological challenges. Policy makers, technology developers, clinicians, patients and researchers need to acknowledge and address these challenges and to consider recommendations that will improve the current scenario. There is a need for further research that can constructively inform decision-making regarding the funding of treatments for MS.

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Acknowledgments

This project has been supported through funding from the UK NIHR Comprehensive Clinical Research Network. This article presents independent research funded by the National Institute for Health Research (NIHR). AH and CG acknowledge funding from the PenCLAHRC National Institute for Health Research Collaborations for Leadership in Applied Health Research and Care. The views expressed in this publication are those of the authors and not necessarily those of the NHS, the NIHR or the Department of Health. AH would like to thank Prof Ken Stein for conversations that led to the paper’s title.

Author contributions

Annie Hawton drafted and revised the manuscript for content, was involved in conceptualisation and design of the work, analysed and interpreted the data, and is guarantor for overall content. James Shearer drafted and revised the manuscript for content, was involved in conceptualisation and design of the work and analysed and interpreted the data. Elizabeth Goodwin drafted and revised the manuscript for content, was involved in conceptualisation and design of the work and analysed and interpreted the data. Colin Green drafted and revised the manuscript for content, was involved in conceptualisation and design of the work and analysed and interpreted the data.

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  1. Health Economics Group, University of Exeter Medical School, University of Exeter, Exeter, UK

    Annie Hawton, James Shearer, Elizabeth Goodwin & Colin Green

  2. Peninsula Collaboration for Leadership in Applied Health Research and Care, University of Exeter Medical School, University of Exeter, Exeter, UK

    Annie Hawton & Colin Green

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  1. Annie Hawton
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Correspondence to Annie Hawton.

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Appendix: Example of Medline Search

Appendix: Example of Medline Search

Search strategy:
1 exp cost analysis/
2 exp cost-benefit analysis/
3 (cost$2 adj2 (benefit$ or consequence* or analys* or utilit$ or minim$ or effective$ or effective* or efficac*)).ti,ab.
4 1 or 2 or 3
5 exp Multiple Sclerosis/
6 Myelitis, Transverse/
7 Demyelinating Diseases/
8 Encephalomyelitis, Acute Disseminated/
9 exp Optic Neuritis/
10 multiple sclerosis.mp.
11 neuromyelitis optica.mp.
12 transverse myelitis.mp.
13 encephalomyelitis.mp.
14 devic.mp.
15 optic neuritis.mp.
16 demyelinating disease$.mp.
17 acute disseminated encephalomyelitis.mp.
18 5 or 6 or 7 or 8 or 9 or 10 or 11 or 12 or 13 or 14 or 15 or 16 or 17
19 4 and 18
20 letter.pt.
21 editorial.pt.
22 comment.pt.
23 20 or 21 or 22
24 19 not 23
25 limit 24 to english language

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Hawton, A., Shearer, J., Goodwin, E. et al. Squinting Through Layers of Fog: Assessing the Cost Effectiveness of Treatments for Multiple Sclerosis. Appl Health Econ Health Policy 11, 331–341 (2013). https://doi.org/10.1007/s40258-013-0034-0

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Keywords

  • Multiple Sclerosis
  • Economic Evaluation
  • Expand Disability Status Scale
  • Fingolimod
  • Health State Utility