Hostname: page-component-cd9895bd7-gbm5v Total loading time: 0 Render date: 2024-12-18T21:38:22.411Z Has data issue: false hasContentIssue false

COST-UTILITY ANALYSIS OF MULTIPLE SCLEROSIS TREATMENT IN THAILAND

Published online by Cambridge University Press:  18 December 2018

Chalakorn Chanatittarat
Affiliation:
Department of Pharmacy, Faculty of Pharmacy, Mahidol [email protected]
Usa Chaikledkaew
Affiliation:
Department of Pharmacy, Faculty of Pharmacy, Mahidol [email protected]
Naraporn Prayoonwiwat
Affiliation:
Division of Neurology, Faculty of Medicine, Siriraj Hospital
Sasitorn Siritho
Affiliation:
Division of Neurology, Faculty of Medicine, Siriraj Hospital, Bumrungrad International Hospital
Pakamas Pasogpakdee
Affiliation:
Sriphat Medical Center
Metha Apiwattanakul
Affiliation:
Division of Neurology, Prasat Neurological Institute
Arthorn Riewpaiboon
Affiliation:
Department of Pharmacy, Faculty of Pharmacy, Mahidol University
Montarat Thavorncharoensap
Affiliation:
Department of Pharmacy, Faculty of Pharmacy, Mahidol University

Abstract

Objectives:

Although interferon beta-1a (IFNß−1a), 1b (IFNß−1b), and fingolimod have been approved as multiple sclerosis (MS) treatments, they have not yet been included on the National List of Essential Medicines (NLEM) formulary in Thailand. This study aimed to evaluate the cost-utility of MS treatments compared with best supportive care (BSC) based on a societal perspective in Thailand.

Methods:

A Markov model with cost and health outcomes over a lifetime horizon with a 1-month cycle length was conducted for relapsing–remitting MS (RRMS) patients. Cost and outcome data were obtained from published studies, collected from major MS clinics in Thailand and a discount rate of 3 percent was applied. The incremental cost-effectiveness ratio (ICER) was calculated and univariate and probabilistic sensitivity analyses were performed.

Results:

When compared with BSC, the ICERs for patients with RRMS aged 35 years receiving fingolimod, IFNβ−1b, and IFNβ−1a were 33,000, 12,000, and 42,000 US dollars (USD) per quality-adjusted life-year (QALY) gained, respectively. At the Thai societal willingness to pay (WTP) threshold of USD 4,500 per QALY gained, BSC had the highest probability of being cost-effective (49 percent), whereas IFNβ−1b and fingolimod treatments showed lower chance being cost-effective at 25 percent and 18 percent, respectively.

Conclusions:

Compared with fingolimod and interferon treatments, BSC remains to be the most cost-effective treatment for RRMS in Thailand based on a WTP threshold of USD 4,500 per QALY gained. The results do not support the inclusion of fingolimod or interferon in the NLEM for the treatment of RRMS unless their prices are decreased or special schema arranged.

Type
Assessment
Copyright
Copyright © Cambridge University Press 2018 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Footnotes

We thank Dr. Chanchira Satukijchai for reviewing the medical records, and Ms. Duangrudee Sapprasert as well as all staff in the Division of Neurology at Siriraj Hospital for collecting data. We also thank the Social Administrative Pharmacy Excellence Research (SAPER) unit at the Faculty of Pharmacy, Mahidol University, for the research support as well as all the staff in the Division of Neurology at Chiang Mai University, Department of Medical Records and Statistic at Chiang Mai University, and Prasat Neurological Institute for collecting data. We acknowledge all MS patients and their caregivers who participated in this study and provided data.

References

REFERENCES

1.Weinshenker, BG, Bass, B, Rice, GP, et al. The natural history of multiple sclerosis: A geographically based study. I. Clinical course and disability. Brain. 1989;112(Pt 1):133146.Google Scholar
2.Cohen, JT. Walking speed and economic outcomes for walking-impaired patients with multiple sclerosis. Expert Rev Pharmacoecon Outcomes Res. 2010;10:595603.Google Scholar
3.Kurtzke, JF. MS epidemiology world wide. One view of current status. Acta Neurol Scand Suppl. 1995;161:2333.Google Scholar
4.Prayoonwiwat, N, Apiwattanakul, M, Pasogpakdee, P, et al. , editors. Prevalence of idiopathic inflammatory demyelinating central nervous system disorders in Thailand. Taipei, Taiwan: PACTRIM; 2014.Google Scholar
5.Browne, P, Chandraratna, D, Angood, C, et al. Atlas of multiple sclerosis 2013: A growing global problem with widespread inequity. Neurology. 2014;83:10221024.Google Scholar
6.Katz Sand, I. Classification, diagnosis, and differential diagnosis of multiple sclerosis. Curr Opin Neurol. 2015;28:193205.Google Scholar
7.Kurtzke, JF. Rating neurologic impairment in multiple sclerosis: An expanded disability status scale (EDSS). Neurology. 1983;33:14441452.Google Scholar
8.Working Group on the Guidelines for Health Technology Assessment in Thailand (2nd ed). Guidelines for health technology assessment in Thailand (2nd ed). Nonthaburi, Thailand: Vacharin P. P.; 2013.Google Scholar
9.Chanatittarat, C. Thai nationawide burden of disease of multiple sclerosis: An evidence-based care management policy. Bangkok, Thailand: Mahidol University; 2015.Google Scholar
10.Bank of Thailand. Thai's Macroeconomic Index Bank of Thailand; 2557 2015 [cited January 5, 2015]. http://www2.bot.or.th/statistics/ReportPage.aspx?reportID=409 (accessed November 11, 2018).Google Scholar
11.Drug and Medical Supply Information Center. Reference drug price April-June MInistry of Public Health 2014 [cited October 1, 2016]. http://dmsic.moph.go.th/dmsic/index.php?p=1&id=1 (accessed November 11, 2018).Google Scholar
12.Scalfari, A, Neuhaus, A, Degenhardt, A, et al. The natural history of multiple sclerosis: A geographically based study 10: Relapses and long-term disability. Brain. 2010;133(Pt 7):19141929. doi:10.1093/brain/awq118.Google Scholar
13.Goodkin, DE, Hertsgaard, D, Rudick, RA. Exacerbation rates and adherence to disease type in a prospectively followed-up population with multiple sclerosis. Implications for clinical trials. Arch Neurol. 1989;46:11071112.Google Scholar
14.The World Health Organization. Life tables by country: Thailand: The World Health Organization; 2014 [cited October 1, 2016]. http://apps.who.int/gho/data/?theme=main&vid=61640 (accessed November 11, 2018).Google Scholar
15.Tramacere, I, Del Giovane, C, Salanti, G, D'Amico, R, Filippini, G. Immunomodulators and immunosuppressants for relapsing-remitting multiple sclerosis: A network meta-analysis. Cochrane Database Syst Rev. 2015;18:CD011381. doi:10.1002/14651858.CD011381.pub2.Google Scholar
16.Fleurence, RL, Hollenbeak, CS. Rates and probabilities in economic modelling: Transformation, translation and appropriate application. Pharmacoeconomics. 2007;25:36.Google Scholar
17.Siritho, S, Thavorncharoensap M, Chanatittarat C, et al. Health utilities of patients with multiple sclerosis and neuromyelitis optica spectrum disorders in Thailand. Mult Scler Relat Disord. 2018;24:151156. doi:10.1016/j.msard.2018.07.004.Google Scholar
18.Tongsiri, S, Cairns, J. Estimating population-based values for EQ-5D health states in Thailand. Value Health. 2011;14:11421145.Google Scholar
19.Nuijten, MJ, Hutton, J. Cost-effectiveness analysis of interferon beta in multiple sclerosis: A Markov process analysis. Value Health. 2002;5:4454. doi:10.1046/j.1524-4733.2002.51052.x.Google Scholar
20.Chilcott, J, McCabe, C, Tappenden, P, et al. Modelling the cost effectiveness of interferon beta and glatiramer acetate in the management of multiple sclerosis. Commentary: Evaluating disease modifying treatments in multiple sclerosis. BMJ. 2003;326:522; discussion doi:10.1136/bmj.326.7388.522.Google Scholar
21.[TA254] Ntag. Fingolimod for the treatment of highly active relapsing–remitting multiple sclerosis. The National Institute for Health and Care Excellence 2012 [cited April 1, 2015]. http://www.nice.org.uk/Guidance/TA254 (accessed November 11, 2018).Google Scholar
22.Dembek, C, White, LA, Quach, J, et al. Cost-effectiveness of injectable disease-modifying therapies for the treatment of relapsing forms of multiple sclerosis in Spain. Eur J Health Econ. 2014;15:353362.Google Scholar
23.Fredrikson, S, McLeod, E, Henry, N, et al. A cost-effectiveness analysis of subcutaneous interferon beta-1a 44mcg 3-times a week vs no treatment for patients with clinically isolated syndrome in Sweden. J Med Econ. 2013;16:756762.Google Scholar
24.Bergvall, N, Costa-Scharplatz, M, Hettle, R, et al. Cost-effectiveness of fingolimod compared to interferon (beta) 1a based on patient transitions in TRANSFORMS. Mult Scler. 2013;19(Suppl 1):276277.Google Scholar
25.Goldberg, LD, Edwards, NC, 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 Spec Pharm. 2009;15:543555.Google Scholar
26.Teerawattananon, Y, Tritasavit, N, Suchonwanich, N, Kingkaew, P. The use of economic evaluation for guiding the pharmaceutical reimbursement list in Thailand. Z Evid Fortbild Qual Gesundhwes. 2014;108:397404. doi:10.1016/j.zefq.2014.06.017.Google Scholar
27.Cohen, JA, Tenenbaum, S, Bhat, R, Pimentel, R, Kappos, L. Long-term efficacy and safety of fingolimod in patients with RRMS: 10-year experience from LONGTERMS study. Mult Scler. 2017;23(Suppl).Google Scholar
28.Moccia, M, Palladino, R, Carotenuto, A, et al. A 8-year retrospective cohort study comparing Interferon-beta formulations for relapsing-remitting multiple sclerosis. Mult Scler Relat Disord. 2018;19:5054. doi:10.1016/j.msard.2017.11.006.Google Scholar
29.Szende, A, Janssen, B, Cabases, J. Self-reported population health: An international perspective based on EQ-5D. Springer Dordrecht, Heidelberg, New York, London: Springer Open; 2014.Google Scholar
30.Alroughani, R, Akhtar, S, Ahmed, S, Behbehani, R, Al-Hashel, J. Is time to reach EDSS 6.0 faster in patients with late-onset versus young-onset multiple sclerosis? PLoS One. 2016;11:e0165846. doi:10.1371/journal.pone.0165846.Google Scholar
31.Grossberg, SE, Oger, J, Grossberg, LD, Gehchan, A, Klein, JP. Frequency and magnitude of interferon beta neutralizing antibodies in the evaluation of interferon beta immunogenicity in patients with multiple sclerosis. J Interferon Cytokine Res. 2011;31:337344. doi:10.1089/jir.2010.0038.Google Scholar
32.Jarernsook, B, Siritho, S, Prayoonwiwat, N. Efficacy and safety of beta-interferon in Thai patients with demyelinating diseases. Mult Scler. 2013;19:585592. doi:10.1177/1352458512459290.Google Scholar
Supplementary material: File

Chanatittarat et al. supplementary material

Figures S1-S4

Download Chanatittarat et al. supplementary material(File)
File 594.7 KB