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Abstract

Objective:

The aim of this study was to assess cost-effectiveness of the different Disease Modifying Drugs (DMD) used as first-line treatments (interferons IM IFNβ-1a, SC IFNβ-1a, SC IFNβ-1b, and glatiramer acetate, GA) in Remitting-Relapsing Multiple Sclerosis (RRMS) in Spain.

Methods:

A Markov model was developed to simulate the progression of a cohort of patients with RRMS, during a period of 10 years. Seven health states, defined by the Expanded Disability Status Scale (EDSS), were considered in the model. Patients with an EDSS score less than 6.0 were assumed to be treated with one of the DMD. In addition, all patients were assumed to receive symptomatic treatment. The monthly transition probabilities of the model were obtained from the literature. The analysis was performed from the societal perspective, in which both direct and indirect (losses in productivity) healthcare costs (€, 2010) were included. A discount rate of 3% was applied to both costs and efficacy results.

Results:

GA was the less costly strategy (€322,510), followed by IM IFNβ-1a (€329,595), SC IFNβ-1b (€ 333,925), and SC IFNβ-1a (€348,208). IM IFNβ-1a has shown the best efficacy results, with 4.176 quality-adjusted life years (QALY), followed by SC IFNβ-1a (4.158 QALY), SC IFNβ-1b (4.157 QALY), and GA (4.117 QALY). Incremental costs per QALY gained with IM IFNβ-1a were €?1,005,194/QALY, €?223,397/QALY, and €117,914/QALY in comparison to SC IFNβ-1a, SC IFNβ-1b, and GA, respectively.

Conclusions:

First-line treatment with GA is the less costly strategy for the treatment of patients with RRMS. Treatment with IM IFNβ-1a is a dominant strategy (lower cost and higher QALY) compared with SC IFNβ-1a and SC IFNβ-1b. However, IM IFNβ-1a is not a cost-effective strategy vs GA, because incremental cost per QALY gained with IM IFNβ-1a exceeds the €30,000 per QALY threshold commonly used in Spain.

Limitations:

The highly-restrictive inclusion criteria of clinical trials limits generalization of the results on efficacy to all patients with multiple sclerosis. Availability of data for head-to-head comparisons is associated with the use of information from clinical trials.  相似文献   
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Background: The safety and efficacy of disease-modifying therapies (DMTs) for relapsing-remitting multiple sclerosis (RRMS) has been established; however, it is not clear which provides optimal value, given benefit-risk profiles and costs.

Aims: To compare the cost-effectiveness of current DMTs for patients with RRMS in the US.

Materials and methods: A Markov model predicting RRMS course following initiation of a DMT was created comparing outcomes (e.g. relapses, disease progression) and costs of natalizumab (NTZ), dimethyl fumarate (DMF), and peginterferon beta-1a (PEG) with fingolimod (FIN), glatiramer acetate (GA, 20?mg daily), and subcutaneous interferon beta-1a (IFN, 44?mcg), respectively, over 10 years. RRMS and secondary-progressive MS (SPMS) EDSS state transitions were predicted in 3-month cycles in which patients were at risk of death, relapse, or discontinuation. Upon DMT discontinuation, natural history progression and relapse rates were applied. Incremental cost-effectiveness ratios (ICERs) were estimated for the cost per relapse avoided, relapse-free years gained, progression avoided, and progression-free years gained. The impact of model parameters on outcomes was evaluated via one-way sensitivity analyses.

Results: Costs ranged from $561,177 (NTZ) to $616,251 (GA). NTZ, DMF, and PEG were dominant (less costly and more effective) compared to FIN, GA, and IFN, respectively, for all ICERs. Variability in drug costs and parameters that affected drug cost accrual (e.g. discontinuation rates and the decision to drop out after SPMS conversion) had a considerable impact on ICERs.

Limitations: Several simplifying assumptions were made that may represent potential limitations of this analysis (e.g. a constant treatment effect over time was assumed).

Conclusions: The results from this analysis suggest that the NTZ, DMF, and PEG are cost-effective DMT choices compared to FIN, GA, and IFN, respectively. The actual impact on a particular plan will vary based on drug pricing and other factors affecting drug cost accrual.  相似文献   
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