Skip to main content
Log in

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

  • Systematic Review
  • Published:
Applied Health Economics and Health Policy Aims and scope Submit manuscript

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.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1

Similar content being viewed by others

References

  1. Zwibel H. Contribution to impaired mobility and general symptoms to the burden of multiple sclerosis. Adv Ther. 2009;26:1043–57.

    Article  PubMed  Google Scholar 

  2. Kobelt G, Berg J, Atherly D, et al. Costs and quality of life in multiple sclerosis: a cross-sectional study in the United States. Neurology. 2006;66:1696–702.

    Article  PubMed  Google Scholar 

  3. McCrone P, Heslin M, Knapp M, et al. Multiple sclerosis in the UK. Pharmacoeconomics. 2008;26:847–60.

    Article  PubMed  Google Scholar 

  4. Ryan M, Deno S, Zwibel H. Review of the clinical debate regarding interventions for multiple sclerosis. J Manag Care Pharm. 2009;15:S1–17.

    Google Scholar 

  5. Boggild M, Palace J, Barton P, et al. Multiple sclerosis risk sharing scheme: two year results of clinical cohort study with historical comparator. Br Med J. 2009;339:1359–63.

    Article  Google Scholar 

  6. Kobelt G, Berg J, Lindgren P, et al. Costs and quality of life of multiple sclerosis in the United Kingdom. Eur J Health Econ. 2006;7(Suppl 2):S96–104.

    Article  PubMed  Google Scholar 

  7. Orme M, Kerrigan J, Tyas D, et al. The effect of disease, functional status, and relapses on the utility of people with multiple sclerosis in the UK. Value Health. 2007;10:54–60.

    Article  PubMed  Google Scholar 

  8. Chilcott J, McCabe C, Tappenden P, et al. Modelling the cost effectiveness of interferon beta and glatiramer acetate in the management of multiple sclerosis. BMJ. 2003;326:522–8.

    Article  PubMed Central  PubMed  Google Scholar 

  9. Naci H, Fleurence R, Birt J, et al. The impact of increasing neurological disability of multiple sclerosis on health utilities: a systematic review of the literature. J Med Econ. 2010;13:78–89.

    Article  PubMed  Google Scholar 

  10. Phillips C, Humphreys I. Assessing cost-effectiveness in the management of multiple sclerosis. ClinicoEcon Outcomes Res. 2009;1:61–78.

    Article  PubMed Central  PubMed  Google Scholar 

  11. National Institute for Clinical Excellence. Beta interferon and glatiramer acetate for the treatment of multiple sclerosis. Guidance No. 32; 2002.

  12. National Institute for Health and Clinical Excellence. Natalizumab for the treatment of adults with highly active relapsing-remitting multiple sclerosis. Guidance No. TA127. London: National Institute for Health and Clinical Excellence; 2007.

  13. McCabe C, Chilcott J, Claxton K, et al. Continuing the multiple sclerosis risk sharing scheme is unjustified. BMJ (Clinical research ed). 2010;340:c1786.

    Article  Google Scholar 

  14. National Institute for Health and Clinical Excellence. Fingolimod for the treatment of highly active relapsing-remitting multiple sclerosis. TA254; 2012.

  15. Holmoy T, Gulowsen Celius E. Cost-effectiveness of natalizumab in multiple sclerosis. Expert Rev Pharmacoecon Outcomes Res. 2008;8:11–21.

    Article  PubMed  Google Scholar 

  16. Bryant J, Clegg A, Milne R. Systematic review of immunomodulatory drugs for the treatment of people with multiple sclerosis: Is there good quality evidence on effectiveness and cost? J Neurol Neurosurg Psychiatry. 2001;70:574–9.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  17. Phillips C. The cost of multiple sclerosis and the cost effectiveness of disease-modifying agents in its treatment. CNS Drugs. 2004;18:561–74.

    Article  PubMed  Google Scholar 

  18. Sharac J, McCrone P, Sabes-Figuera R. Pharmacoeconomic considerations in the treatment of multiple sclerosis. Drugs. 2010;70:1677–91.

    Article  CAS  PubMed  Google Scholar 

  19. Hoch J. Cost-effectiveness lessons from disease-modifying drugs in the treatment of multiple sclerosis. Expert Rev Pharmacoecon Outcomes Res. 2004;4:537–47.

    Article  PubMed  Google Scholar 

  20. Chiao E, Meyer K. Cost effectiveness and budget impact of natalizumab in patients with relapsing multiple sclerosis. Curr Med Res Opin. 2009;25:1445–54.

    Article  CAS  PubMed  Google Scholar 

  21. Bakhshai J, Bleu-Laine R, Jung M, et al. The cost effectiveness and budget impact of natalizumab for formulary inclusion. J Med Econ. 2010;13:63–9.

    Article  PubMed  Google Scholar 

  22. Earnshaw S, Graham J, Oleen-Burkey M, et al. Cost effectiveness of glatiramer acetate and natalizumab in relapsing-remitting multiple sclerosis. Appl Health Econ Health Policy. 2009;7:91–108.

    Article  PubMed  Google Scholar 

  23. Gani R, Giovannoni G, Bates D, et al. Cost-effectiveness analyses of natalizumab (Tysabri) compared with other disease-modifying therapies for people with highly active relapsing-remitting multiple sclerosis. Pharmacoeconomics. 2008;26:617–27.

    Article  PubMed  Google Scholar 

  24. Kobelt G, Berg J, Lindgren P, et al. Modeling the cost-effectiveness of a new treatment for MS (natalizumab) compared with current standard practice in Sweden. Mult Scler. 2008;14:679–90.

    Article  CAS  PubMed  Google Scholar 

  25. O’Day K, Meyer K, Miller R, et al. Cost-effectiveness of natalizumab versus fingolimod for the treatment of relapsing multiple sclerosis. J Med Econ. 2011;14:617–27.

    Article  PubMed  Google Scholar 

  26. Noyes K, Bajorska A, Chappel A, et al. Cost-effectiveness of disease-modifying therapy for multiple sclerosis: a population based study. Neurology. 2011;77:353–63.

    Article  Google Scholar 

  27. Becker R, Dembeck C. Effects of cohort selection on the results of cost-effectiveness analysis of disease-modifying drugs for relapsing-remitting multiple sclerosis. J Manag Care Pharm. 2011;17:377–81.

    PubMed  Google Scholar 

  28. Nuijten M, Mittendorf T. A health-economic evaluation of disease-modifying drugs for the treatment of relapsing-remitting multiple sclerosis from the German societal perspective. Clin Ther. 2010;32:717–28.

    Article  PubMed  Google Scholar 

  29. Tappenden P, McCabe C, Chilcott J, et al. Cost-effectiveness of disease-modifying therapies in the management of multiple sclerosis for the Medicare population. Value Health. 2009;12:657–65.

    Article  PubMed  Google Scholar 

  30. Goldberg L, Edwards N, Fincher C, et al. Comparing the cost-effectiveness of disease-modifying drugs for the first-line treatment of relapsing-remitting multiple sclerosis. J Manag Care Pharm. 2009;15:543–55.

    PubMed  Google Scholar 

  31. Castelli-Haley J, Oleen-Burkey M-KA, Lage M, et al. Glatiramer acetate versus interferon beta-1a for subcutaneous administration: comparison of outcomes among multiple sclerosis patients. Adv Ther. 2008;25:658–73.

    Article  PubMed  Google Scholar 

  32. Bell C, Graham J, Earnshaw S, et al. Cost-effectiveness of four immunomodulatory therapies for relapsing-remitting multiple sclerosis: a Markov model based on long-term clinical data. J Manag Care Pharm. 2007;13:245–61.

    PubMed  Google Scholar 

  33. Prosser L, Kuntz K, Bar-Or A, et al. Cost-effectiveness of interferon beta-1a, interferon beta-1b, and glatiramer acetate in newly diagnosed non-primary progressive multiple sclerosis. Value Health. 2004;7:554–68.

    Article  PubMed  Google Scholar 

  34. Bose U, Kadkhani D, Burrell A, et al. Cost-effectiveness analysis of glatiramer acetate in the treatment of relapsing-remitting multiple sclerosis. J Drug Assess. 2002;5:67–79.

    Google Scholar 

  35. Guo S, Bozkaya D, Ward A, et al. Treating relapsing multiple sclerosis with subcutaneous versus intramuscular interferon beta-1a: modelling the clinical and economic implications. Pharmacoeconomics. 2009;27:39–53.

    Article  PubMed  Google Scholar 

  36. Iskedjian M, Walker J, Gray T, et al. Economic evaluation of Avonex (interferon beta-1a) in patients following a single demyelinating event. Mult Scler. 2005;11:542–51.

    Article  PubMed  Google Scholar 

  37. Lepen C, Coyle P, Vollmer T, et al. Long-term cost-effectiveness of interferon-β-1a in the treatment of relapsing-remitting multiple sclerosis. Clin Drug Investig. 2003;23:571–81.

    Article  CAS  PubMed  Google Scholar 

  38. Touchette D, Durgin T, Wanke L, et al. A cost-utility analysis of mitoxantrone hydrochloride and interferon beta-1b in the treatment of patients with secondary progressive or progressive relapsing multiple sclerosis. Clin Ther. 2003;25:611–34.

    Article  PubMed  Google Scholar 

  39. Kobelt G, Jönsson L, Fredrikson S. Cost-utility of interferon β1b in the treatment of patients with active relapsing-remitting or secondary progressive multiple sclerosis. Eur J Health Econ. 2003;4:50–9.

    Article  CAS  PubMed  Google Scholar 

  40. Lazzaro C, Bianchi C, Peracino L, et al. Economic evaluation of treating clinically isolated syndrome and subsequent multiple sclerosis with interferon beta-1b. Neurol Sci. 2009;30:21–31.

    Article  PubMed  Google Scholar 

  41. Kobelt G, Jönsson L, Miltenburger C, et al. Cost-utility analysis of interferon beta-1b in secondary progressive multiple sclerosis using natural history data. Int J Technol Assess Health Care. 2002;18:127–38.

    PubMed  Google Scholar 

  42. Nuijten M, Hutton J. Cost-effectiveness analysis of interferon beta in multiple sclerosis: a Markov process analysis. Value Health. 2002;5:44–54.

    Article  PubMed  Google Scholar 

  43. Phillips C, Gilmour L, Gale R, et al. A cost utility model of interferon beta-1b in the treatment of relapsing-remitting multiple sclerosis. J Med Econ. 2001;4:35–50.

    Article  Google Scholar 

  44. Brown M, Murray T, Sketris I, et al. Cost-effectiveness of interferon beta-1B in slowing multiple sclerosis disability progression. Int J Technol Assess Health Care. 2000;16:751–67.

    Article  CAS  PubMed  Google Scholar 

  45. Kendrick M, Johnson K. Long term treatment of multiple sclerosis with interferon-β may be cost effective. Pharmacoeconomics. 2000;18:45–53.

    Article  CAS  PubMed  Google Scholar 

  46. Kobelt G, Jönsson L, Henriksson F, et al. Cost-utility analysis of interferon beta-1B in secondary progressive multiple sclerosis. Int J Technol Assess Health Care. 2000;16:768–80.

    Article  CAS  PubMed  Google Scholar 

  47. Forbes R, Lees A, Waugh N, et al. Population based cost utility study of interferon beta-1b in secondary progressive multiple sclerosis. BMJ. 1999;319:1529–33.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  48. Parkin D, Jacoby A, McNamee P, et al. Treatment of multiple sclerosis with interferon-β: an appraisal of cost-effectiveness and quality of life. J Neurol Neurosurg Psychiatry. 2000;68:144–9.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  49. Tappenden P, Saccardi R, Confavreux C, et al. Autologous haematopoietic stem cell transplantation for secondary progressive multiple sclerosis: an exploratory cost-effectiveness analysis. Bone Marrow Transpl. 2010;45:1014–21.

    Article  CAS  Google Scholar 

  50. Kobelt G, Texier-Richard B, Lindgren P. The long-term cost of multiple sclerosis in France and potential changes with disease-modifying interventions. Mult Scler. 2009;15:741–51.

    Article  CAS  PubMed  Google Scholar 

  51. Higginson I, McCrone P, Hart S, et al. Is short-term palliative care cost-effective in multiple sclerosis? A randomized phase II trial. J Pain Symptom Manag. 2009;38:816–26.

    Article  Google Scholar 

  52. Pozzilli C, Brunetti M, Amicosante A, et al. Home based management in multiple sclerosis: results of a randomised controlled trial. J Neurol Neurosurg Psychiatry. 2002;73(3):250–5.

    Google Scholar 

  53. Curkendall S, Wang C, Hohnson B, et al. Potential health care cost savings associated with early treatment of multiple sclerosis using disease modifying therapy. Clin Ther. 2011;33:914–25.

    Article  PubMed  Google Scholar 

  54. Tan H, Yu J, Tabby D, et al. Clinical and economic impact of a specialty care management program among patients with multiple sclerosis: a cohort study. Mult Scler. 2010;16:956–63.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  55. Rajagopalan K, Brook R, Beren I, et al. Comparing the costs and absences for multiple sclerosis among US employees: pre- and post-treatment initiation. Curr Med Res Opin. 2011;27:179–88.

    Article  PubMed  Google Scholar 

  56. Kurtzke J. Rating neurologic impairment in multiple sclerosis: an expanded disability status scale (EDSS). Neurology. 1983;33:1444–52.

    Article  CAS  PubMed  Google Scholar 

  57. Tappenden P, McCabe C, Simpson E, et al. The clinical effectiveness and cost-effectiveness of interferon-beta and glatiramer acetate in the management of relapsing/remitting and secondary-progressive multiple sclerosis. Maryland, USA: Agency for Healthcare Research and Quality, Department of Health and Human Services; 2006.

  58. Prosser L, Kuntz K, Bar-Or A, et al. Patient and community preferences for treatments and health states in multiple sclerosis. Mult Scler. 2003;9:311–9.

    Google Scholar 

  59. Henriksson F, Fredrikson S, Masterman T. Cost, quality of life and disease severity in multiple sclerosis: a cross-sectional study in Sweden. Eur J Neurol. 2001;8:27–35.

    Article  CAS  PubMed  Google Scholar 

  60. Berg J, Lindgren P, Fredrikson S, et al. Costs and quality of life of multiple sclerosis in Sweden. Eur J Health Econ. 2006;7:75–85.

    Article  Google Scholar 

  61. Grima DT, Torrance GW, Francis G, et al. Cost and health related quality of life consequences of multiple sclerosis. Mult Scler. 2000;6:91–8.

    CAS  PubMed  Google Scholar 

  62. Parkin D, McNamee P, Jacoby A, et al. A cost-utility analysis of interferon beta for multiple sclerosis. Health Technol Assess. 1998;2:1–45.

    Google Scholar 

  63. Kobelt G, Lindgren P, Parkin D, et al. Cost and quality of life in multiple sclerosis. A cross-sectional observational study in the UK. Working Paper Series in Economics and Finance. Stockholm: Stockholm School of Economics; 2000.

  64. EuroQol Group. EQ-5D user guide. Rotterdam: The EuroQol Group; 1996.

    Google Scholar 

  65. Dolan P. Modeling valuations for EuroQol health states. Med Care. 1997;35:1095–108.

    Article  CAS  PubMed  Google Scholar 

  66. Brazier J, Roberts J, Deverill M. The estimation of a preference-based measure of health from the SF-36. J Health Econ. 2002;21:271–92.

    Article  PubMed  Google Scholar 

  67. Brazier J, Roberts J. The estimation of a preference-based measure of health from the SF-12. Med Care. 2004;42:851–9.

    Article  PubMed  Google Scholar 

  68. Torrance G, Feeny D, Furlong W, et al. Multi-attribute preference functions for a comprehensive health status classification systems: Health Utilities Index Mark 2. Med Care. 1996;34:702.

    Article  CAS  PubMed  Google Scholar 

  69. Ebers GC. Outcome measures were flawed. BMJ. 2010;340:1286.

    Article  Google Scholar 

  70. Ebers GC, Heigenhauser L, Daumer M, et al. Disability as an outcome in MS clinical trials. Neurology. 2008;71:624–31.

    Article  CAS  PubMed  Google Scholar 

  71. Tyas D, Kerrigan J, Russell N, et al. The distribution of the cost of multiple sclerosis in the UK: How do costs vary by illness severity? Value Health. 2007;10:386–9.

    Article  PubMed  Google Scholar 

  72. Weinshenker B, Bass B, Rice G, et al. The natural history of multiple sclerosis: a geographically based study 1. Clinical course and disability. Brain. 1989;112:133–46.

    Article  PubMed  Google Scholar 

  73. Runmarker B, Andersen O. Prognostic factors in a multiple sclerosis incidence cohort with twenty-five years of follow-up. Brain. 1993;116:117–34.

    Article  PubMed  Google Scholar 

  74. Tremlett H, Paty DW, Devonshire V. Disability progression in multiple sclerosis is much slower than previously reported. Neurology. 2006;66:172–7.

    Article  PubMed  Google Scholar 

  75. Zajicek J, Freeman J, Porter B. Multiple sclerosis: a practical manual. Oxford: Oxford University Press; 2007.

    Book  Google Scholar 

  76. Zajicek J, Ingram W, Vickery J, et al. Patient-orientated longitudinal study of multiple sclerosis in south west England (The South West Impact of Multiple Sclerosis project, SWIMS) 1: Protocol and baseline characteristics of cohort. BMC Neurol. 2010;10:88.

    Article  PubMed Central  PubMed  Google Scholar 

  77. Oleen-Burkey M, Castelli-Haley J, Lage M, et al. Burden of a multiple sclerosis relapse. The patient’s perspective. Patient. 2012;5:57–69.

    Article  PubMed  Google Scholar 

  78. Parkin D, Jacoby A, McNamee P, et al. Treatment of multiple sclerosis with interferon-β: an appraisal of cost-effectiveness and quality of life. J Neurol Neurosurg Psychiatry. 2000;68:144–9.

    Google Scholar 

  79. Patwardhan M, Matchar D, Samsa G, et al. Cost of multiple sclerosis by level of disability: a review of literature. Mult Scler. 2005;11:232–9.

    Article  CAS  PubMed  Google Scholar 

  80. Claxton K, Walker S, Palmer S, et al. Appropriate perspectives for health care decisions. CHE Research Paper. York: Centre for Health Economics; 2010.

  81. Koopmanschap M, Rutten FFH, Vanineveld B, et al. The friction cost method for measuring indirect costs of disease. J Health Econ. 1995;14:171–89.

    Article  CAS  PubMed  Google Scholar 

  82. Anderson R. Systematic reviews of economic evaluations: utility or futility? Health Econ. 2010;19:350–64.

    Article  PubMed  Google Scholar 

  83. Saramago P, Manca A, Sutton A. Deriving input parameters for cost-effectiveness modeling: taxonomy of data types and approaches to their statistical synthesis. Value Health. 2012;15:639–49.

    Article  PubMed  Google Scholar 

  84. Ara R, Wailoo A. Using health state utility values in models exploring the cost-effectiveness of health technologies. Value Health. 2012;15(6):971–4.

    Google Scholar 

  85. Ford D, Jones K, Middleton R, et al. The feasibility of collecting information from people with Multiple Sclerosis for the UK MS Register via a web portal: characterising a cohort of people with MS. BMC Med Inf Decis Mak. 2012;12:73.

    Article  Google Scholar 

Download references

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.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Annie Hawton.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary material 1 (DOCX 169 kb)

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

Rights and permissions

Reprints and permissions

About this article

Cite this article

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

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s40258-013-0034-0

Keywords

Navigation