Literature DB >> 24990825

Opportunity cost of funding drugs for rare diseases: the cost-effectiveness of eculizumab in paroxysmal nocturnal hemoglobinuria.

Doug Coyle1, Matthew C Cheung2, Gerald A Evans3.   

Abstract

BACKGROUND: Both ethical and economics concerns have been raised with respect to the funding of drugs for rare diseases. This article reports both the cost-effectiveness of eculizumab for the treatment of paroxysmal nocturnal hemoglobinuria (PNH) and its associated opportunity costs.
METHODS: Analysis compared eculizumab plus current standard of care v. current standard of care from a publicly funded health care system perspective. A Markov model covered the major consequences of PNH and treatment. Cost-effectiveness was assessed in terms of the incremental cost per life year and per quality-adjusted life year (QALY) gained. Opportunity costs were assessed by the health gains foregone and the alternative uses for the additional resources.
RESULTS: Eculizumab is associated with greater life years (1.13), QALYs (2.45), and costs (CAN$5.24 million). The incremental cost per life year and per QALY gained is CAN$4.62 million and CAN$2.13 million, respectively. Based on established thresholds, the opportunity cost of funding eculizumab is 102.3 discounted QALYs per patient funded. Sensitivity and subgroup analysis confirmed the robustness of the results. If the acquisition cost of eculizumab was reduced by 98.5%, it could be considered cost-effective. LIMITATIONS: The nature of rare diseases means that data are often sparse for the conduct of economic evaluations. When data were limited, assumptions were made that biased results in favor of eculizumab.
CONCLUSIONS: This study demonstrates the feasibility of conducting economic evaluations in the context of rare diseases. Eculizumab may provide substantive benefits to patients with PNH in terms of life expectancy and quality of life but at a high incremental cost and a substantial opportunity cost. Decision makers should fully consider the opportunity costs before making positive reimbursement decisions.
© The Author(s) 2014.

Entities:  

Keywords:  Markov models; cost utility analysis; probabilistic sensitivity analysis

Mesh:

Substances:

Year:  2014        PMID: 24990825     DOI: 10.1177/0272989X14539731

Source DB:  PubMed          Journal:  Med Decis Making        ISSN: 0272-989X            Impact factor:   2.583


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