Cost utility of tumour necrosis factor-α inhibitors for rheumatoid arthritis: An application of bayesian methods for evidence synthesis in a markov model

Abstract

Rheumatoid arthritis (RA) is a chronic autoimmune disease that affects approximately 1.5 million people in the US. Tumour necrosis factor (TNF)α; inhibitors have been shown to effectively treat and maintain remission in patients with moderately to severely active RA compared with conventional agents. The high acquisition cost of TNFα; inhibitors prohibits access, which mandates economic investigations into their affordability. The lack of head-to-head comparisons between these agents makes it difficult to determine which agent is the most cost effective. Objective: This study aimed to determine which TNFα; inhibitor was the most cost-effective agent for the treatment of moderately to severely active RA from the US healthcare payer's perspective. Methods: A Markov model was constructed to analyse the cost utility of five TNFα; inhibitors (in combination with methotrexate [+MTX]) versus MTX monotherapy using Bayesian methods for evidence synthesis. The model had a cycle length of 3 months and an overall time horizon of 5 years. Transition probabilities and utility scores were based on published studies. Total direct costs were adjusted to year 2009 US using the medical component of the Consumer Price Index. All costs and QALYs were discounted at a rate of 3% per year. Patient response to the different strategies was determined by the American College of Rheumatology (ACR)50 criteria. One-way and probabilistic sensitivity analyses (PSAs) were performed to test the robustness of the base-case scenario. The base-case scenario was changed to ACR20 criteria (scenario 1) and ACR70 criteria (scenario 2) to determine the model's robustness. Cost-effectiveness acceptability curves and cost-effectiveness frontiers were used to estimate the cost-effectiveness probability of each treatment strategy. A willingness-to-pay (WTP) threshold was defined as three times the US GDP per capita (US139 143 per additional QALY gained). Primary results were presented as incremental cost-effective ratios (ICERs).Results: Etanercept+MTX was the most cost-effective treatment strategy in the base-case scenario up to a WTP threshold of US546 449 per QALY gained. At a WTP threshold of greater than US546 499 per QALY gained, certolizumab+MTX was the most cost-effective treatment strategy. One-way analyses showed that the base-case scenario was sensitive to the probability of achieving ACR50 criteria for MTX and each TNFα; inhibitor, and changes in the utility score for patients who achieved the ACR50 criteria. With the exception of infliximab, all of the TNFα; inhibitors were sensitive to drug cost per cycle. In the scenario analyses, certolizumab+MTX was a dominant treatment strategy using ACR20 criteria, but etanercept+MTX was a dominant treatment strategy using ACR70 criteria. Conclusions: Etanercept+MTX was a cost-effective treatment strategy in the base-case scenario; however, the model was sensitive to parameter uncertainties and ACR response criteria. Although Bayesian methods were used to determine transition probabilities, future studies will need to focus on head-tohead comparisons of multiple TNFα; inhibitors to provide valid comparisons. Adis © 2012 Springer International Publishing AG.