The cost-effectiveness of personalized genetic medicine: the case of genetic testing in neonatal diabetes

Diabetes Care. 2011 Mar;34(3):622-7. doi: 10.2337/dc10-1616. Epub 2011 Jan 27.

Abstract

Objective: Neonatal diabetes mellitus is a rare form of diabetes diagnosed in infancy. Nearly half of patients with permanent neonatal diabetes have mutations in the genes for the ATP-sensitive potassium channel (KCNJ11 and ABCC8) that allow switching from insulin to sulfonylurea therapy. Although treatment conversion has dramatic benefits, the cost-effectiveness of routine genetic testing is unknown.

Research design and methods: We conducted a societal cost-utility analysis comparing a policy of routine genetic testing to no testing among children with permanent neonatal diabetes. We used a simulation model of type 1 diabetic complications, with the outcome of interest being the incremental cost-effectiveness ratio (ICER, $/quality-adjusted life-year [QALY] gained) over 30 years of follow-up.

Results: In the base case, the testing policy dominated the no-testing policy. The testing policy was projected to bring about quality-of-life benefits that enlarged over time (0.32 QALYs at 10 years, 0.70 at 30 years) and produced savings in total costs that were present as early as 10 years ($12,528 at 10 years, $30,437 at 30 years). Sensitivity analyses indicated that the testing policy would remain cost-saving as long as the prevalence of the genetic defects remained >3% and would retain an ICER <$200,000/QALY at prevalences between 0.7 and 3%.

Conclusions: Genetic testing in neonatal diabetes improves quality of life and lowers costs. This paradigmatic case study highlights the potential economic impact of applying the concepts of personalized genetic medicine to other disorders in the future.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Cost-Benefit Analysis
  • Diabetes Mellitus / diagnosis*
  • Diabetes Mellitus / genetics
  • Genetic Testing / economics*
  • Humans
  • Infant
  • Infant, Newborn