title: Estimating the long-term cost-effectiveness of exenatide in the United States: an adjunctive treatment for type 2 diabetes mellitus.
abstract: OBJECTIVE
  This analysis provides an early estimate of the cost-effectiveness of adjunctive exenatide in treating type 2 diabetes mellitus in the United States. Data from pivotal phase III 30-week clinical trials and 52 weeks of their subsequent open-label extension studies (i.e., 82 weeks total) were used to project the effects of 30 years of adjunctive exenatide treatment.
  
  
  METHODS
  This analysis utilized a published and validated Markov model incorporating Monte Carlo simulation with tracker variables to estimate the clinical and cost outcomes of adding exenatide to a background of metformin and/or sulfonylurea treatment, with the effects of 30 years of adjunctive exenatide treatment (projected from data from 82 weeks of exenatide treatment) compared with no additional treatment beyond metformin and/or a sulfonylurea. Sensitivity analyses were performed on key clinical assumptions, discount rates, and shorter time horizons.
  
  
  RESULTS
  The base-case scenario (30 years of exenatide) yielded an incremental cost-effectiveness ratio (ICER) of $35,571. We found that shortening the time horizons and removing the lipid effects of exenatide had the greatest negative impact on ICERs when performing sensitivity analysis.
  
  
  CONCLUSIONS
  Our analysis demonstrated that exenatide used for 20 or 30 years compared with no additional treatment beyond metformin and/or a sulfonylurea is cost-effective in the adjunctive treatment of type 2 diabetes with an ICER less than $50,000 per life-year gained. Sensitivity analyses suggest that, in addition to sustained reduction in HbA(1c), the added clinical effects of improved lipid values, systolic blood pressure, and reduced body mass index all positively contributed to the cost-effectiveness of exenatide.
authors.affiliation: IMS-Health-Noblesville, IN, USA. mminshall@us.imshealth.com
authors.forename: Michael E
authors.initials: ME
authors.lastname: Minshall
authors.forename: Alan K
authors.initials: AK
authors.lastname: Oglesby
authors.forename: Matthew E
authors.initials: ME
authors.lastname: Wintle
authors.forename: William J
authors.initials: WJ
authors.lastname: Valentine
authors.forename: Stéphane
authors.initials: S
authors.lastname: Roze
authors.forename: Andrew J
authors.initials: AJ
authors.lastname: Palmer
mesh_terms: D003362:Cost-Benefit Analysis; D003924:Diabetes Mellitus, Type 2 / Q000188:drug therapy* / Q000191:economics; D016527:Drug Costs; D000077270:Exenatide; D006442:Glycated Hemoglobin / Q000187:drug effects; D017048:Health Care Costs; D006801:Humans; D007004:Hypoglycemic Agents / Q000191:economics* / Q000627:therapeutic use; D008687:Metformin; D017059:Models, Econometric; D009010:Monte Carlo Method; D010455:Peptides / Q000191:economics* / Q000627:therapeutic use; D013453:Sulfonylurea Compounds; D013997:Time Factors; D014481:United States; D014688:Venoms / Q000191:economics* / Q000627:therapeutic use
chemical_list: D000077270:Exenatide; D006442:Glycated Hemoglobin; D007004:Hypoglycemic Agents; D008687:Metformin; D010455:Peptides; D013453:Sulfonylurea Compounds; D014688:Venoms