• Khalid M Kamal, Lesley-Ann Miller, Jan Kavookjian, and Suresh Madhavan.
• Department of Clinical, Social, and Administrative Sciences, Mylan School of Pharmacy, Bayer Learning Center, Duquesne University, Pittsburgh, PA 15282, USA. kamalk@duq.edu
• Semin. Arthritis Rheum. 2006 Aug 1; 36 (1): 50-60.

ObjectivesTo 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.MethodsA 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.ResultsThe 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.ConclusionsBased 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.RelevanceThe 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.

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