Cost-utility of different treatment strategies after the failure of tumour necrosis factor inhibitor in rheumatoid arthritis in the Finnish setting.

OBJECTIVE: To evaluate the cost-utility of different treatment strategies in severe RA after TNF-inhibitor failure. METHODS: The cost-effectiveness of treatment strategies was compared in a group of hypothetical Finnish RA patients. Initially, the patients received either best supportive care (BSC) or one of the following treatments before BSC: adalimumab (ADAL), abatacept (ABAT), etanercept (ETAN), infliximab (INFL) or rituximab (RTX). Further treatments were added to the most cost-effective strategy in a stepwise manner. The analysis was performed on an Excel-based Markov state transition model using the probabilistic approach. The clinical outcomes related to treatments were estimated from published clinical trials. The gained quality-adjusted life-years (QALYs) were estimated based on Health Utilities Index (HUI-3) and disease severity scores (HAQ). The resource use and costs were obtained from the Finnish treatment practice, one published study, the Finnish Unit Cost list and Finnish Medicine Tariffs. RESULTS: Treatment with RTX was more effective and less costly than treatment with ADAL, ABAT or ETAN after TNF-inhibitor failure. An additional QALY gained with RTX costs 30,248 euros compared with BSC. The incremental cost-effectiveness ratios (ICERs) are 50,941, 50,372, 36,121 and 67,003 euros per QALY gained for adding ADAL, ETAN, INFL and ABAT to the RTX strategy, respectively. According to the cost-effectiveness acceptability frontier (CEAF), only BSC or treatments with RTX or RTX followed by INFL should be considered after TNF-inhibitor failure, if willingness to pay is between 0 and 50,000 euros per QALY gained. CONCLUSIONS: Treatment with RTX is a cost-effective treatment strategy in RA patients in Finland.

Alternative decision analysis modeling in the economic evaluation of tumor necrosis factor inhibitors for rheumatoid arthritis.

OBJECTIVES: To provide a review of the studies that use decision models in the economic evaluation of tumor necrosis factor (TNF) inhibitors in rheumatoid arthritis (RA) and to address some important issues surrounding the choice of such modeling techniques in these economic evaluations. METHODS: A systematic literature search was conducted by 1 author from the literature published from January 1996 to March 2005 through Medline, Embase, and Cochrane library databases. RESULTS: The review yielded 29 studies that used decision models. Only 10 studies used a decision model in the economic analysis of the TNF inhibitors and were included in the final review. Decision model types included the following in the review articles: decision tree (2), Markov model (7), and discrete event simulation (1). These models vary in complexity and their choice depends on the course of disease, the impact of treatment, and the available data. CONCLUSIONS: Based on the results derived from alternative modeling techniques, it is safe to say that all methods can provide useful information with regard to economic evaluations of TNF inhibitors. Even though different modeling techniques provide an appropriate representation of available data, their results should be interpreted contingent on the input data, assumptions, sensitivity analyses, and other alternative scenario analyses. RELEVANCE: The transparency in the models will encourage end users such as policymakers and prescribers to make informed judgments regarding the appropriateness of the methods and the validity of the results.