Introduction
Biologic therapies have revolutionized the treatment of psoriasis; however, their use is limited by costs. Ixekizumab was more effective than etanercept in the UNCOVER trials, and the Food and Drug Administration (FDA) approved ixekizumab for treating psoriasis. Evaluating the cost-effectiveness of these therapies is crucial for medical decision making and our objective was to determine the cost-effectiveness of various ixekizumab dosing frequencies compared with etanercept.
Methods
We utilized published data from the UNCOVER comparative efficacy trials, including transitional probabilities and treatment response rates, to create a Markov model simulating the clinical course and cost-effectiveness of three treatment algorithms for patients with moderate to severe plaque psoriasis over 60-weeks: (1) ixekizumab every 2 weeks for 12 weeks then every 4 weeks, (2) ixekizumab every 4 weeks throughout the treatment period, (3) biweekly etanercept for 12 weeks then once weekly. We utilized a standard willingness-to-pay (WTP) threshold of $150,000 per quality adjusted life year (QALY) and Medicaid drug acquisition costs for our calculations.
Results
Ixekizumab every 4 weeks was $28,681 (USD) less expensive than biweekly etanercept, and $21,375 less expensive, and 0.006 QALY less effective, than ixekizumab every 2 weeks-- a savings of $28.7 and $21.4 million, respectively, per 1,000 patients. A 95.6% cost reduction to $197.83 per dose is required for ixekizumab every 2 weeks to be more cost-effective than every 4 weeks. Biweekly etanercept requires a 29.5% cost reduction ($743.82 per dose) to be competitive with ixekizumab every 4 weeks.
Discussion
This cost-effectiveness model utilizes strong input data but is a limited approximation of real-life scenarios. Treatment with ixekizumab every 2 weeks is unlikely to be cost-effective compared with ixekizumab every 4 weeks at current U.S. market prices. Yet, the U.S. FDA approval and manufacturer's recommendation are for ixekizumab every 2 weeks. Accordingly, we suggested selecting biologic therapies using cost-effectiveness analyses.
J Drugs Dermatol. 2017;16(10):964-970.
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