Economic assessment of troglitazone as an adjunct to sulfonylurea therapy in the treatment of type 2 diabetes

Objective: To assess the economic efficiency of adding troglitazone to sulf onylurea therapy to improve glycemic control. Background: Despite the high prevalence of type 2 diabetes, existing treatm ent strategies often fail. New oral agents give a wider segment of the popu lation with type 2 diabetes hope of achieving near-normal blood-glucose lev els. Troglitazone, a novel chemical entity, is one promising new agent. Methods: We conducted an economic analysis based on glycemic-control data f rom a randomized clinical trial comparing troglitazone with placebo, each a dded to glyburide. A patient simulation model was used to translate these d ata to long-term outcomes associated with diabetes. Patients had poorly con trolled type 2 diabetes mellitus despite glyburide therapy. Risk functions of developing and progressing through nephropathy, retinopathy, neuropathy, hypoglycemia, and macrovascular disease were developed from the Diabetes C ontrol and Complications Trial and large epidemiologic studies. Cost estima tes were based on data from 5 states, all payor databases, surveys, and lit erature. The main outcomes of the model were cost-consequences, number of p atients developing each type of complication, mean time to development of t he complication, cost per life-year gained (LYG), and cost per quality-adju sted life-year. Results: The model predicts that for every 1000 patients treated with trogl itazone, the improved glycemic control could mean that 95 to 140 fewer pati ents would experience one of the most severe diabetic complications leg, bl indness, end-stage renal disease, amputation), which may increase life expe ctancy by 2.0 years. These benefits are obtained at an additional $2100 per LYG (undiscounted). The ratio remains <$50,000 per LYG for most variations in input. Conclusions: The clinical trial demonstrated that troglitazone + glyburide improves glycemic control compared with glyburide alone. Based on these res ults, the model estimates fewer diabetic complications at a cost well below accepted cost-effective thresholds.