OBJECTIVES: As an example application of the CORE Diabetes Model in type 2 diabetes, we simulated the cost-effectiveness of repaglinide/metformin combination therapy versus nateglinide/metformin for treatment of individuals with type 2 diabetes with an inadequate response to sulphonylurea, metformin, or fixed dose glyburide/metformin. METHODS: The CORE Diabetes Model was used to simulate long-term outcomes for a cohort of individuals with type 2 diabetes treated with either repaglinide/metformin or nateglinide/metformin. HbA1c changes for each regimen were taken from a comparative study. At the end of the study, changes in HbA1c from baseline were -1.28% points and -0.67% points for repaglinide/metformin and nateglinide/metformin, respectively. Median final doses were 5.0 mg/day for repaglinide, 360 mg/day for nateglinide and 2000 mg/day metformin in each treatment arm. Costs were calculated as the annual costs for drugs plus costs of complications (US Medicare perspective) over a 30-year period. Life expectancy (LE) and quality-adjusted life expectancy (QALE) were calculated. Outcomes and costs were discounted at 3% annually. RESULTS: With repaglinide/metformin, improved glycaemic control led to projected decreases in complication rates, improvement of LE and QALE by 0.15 and 0.14 years respectively, and total cost savings of 3,662 dollars/person over the 30-year period. Repaglinide/metformin had a 96% probability that the incremental costs per quality-adjusted life year gained would be 20,000 dollars or less, and a 66% probability that repaglinide/metformin would be cost-saving compared to nateglinide/metformin. Sensitivity analyses supported the validity and reliability of the results. CONCLUSIONS: In the health economic context, repaglinide/metformin combination was dominant to nateglinide/metformin. The CORE Diabetes Model is a tool to help third-party reimbursement payers identify treatments for type 2 diabetes that are good value for money.
OBJECTIVES: As an example application of the CORE Diabetes Model in type 2 diabetes, we simulated the cost-effectiveness of repaglinide/metformin combination therapy versus nateglinide/metformin for treatment of individuals with type 2 diabetes with an inadequate response to sulphonylurea, metformin, or fixed dose glyburide/metformin. METHODS: The CORE Diabetes Model was used to simulate long-term outcomes for a cohort of individuals with type 2 diabetes treated with either repaglinide/metformin or nateglinide/metformin. HbA1c changes for each regimen were taken from a comparative study. At the end of the study, changes in HbA1c from baseline were -1.28% points and -0.67% points for repaglinide/metformin and nateglinide/metformin, respectively. Median final doses were 5.0 mg/day for repaglinide, 360 mg/day for nateglinide and 2000 mg/day metformin in each treatment arm. Costs were calculated as the annual costs for drugs plus costs of complications (US Medicare perspective) over a 30-year period. Life expectancy (LE) and quality-adjusted life expectancy (QALE) were calculated. Outcomes and costs were discounted at 3% annually. RESULTS: With repaglinide/metformin, improved glycaemic control led to projected decreases in complication rates, improvement of LE and QALE by 0.15 and 0.14 years respectively, and total cost savings of 3,662 dollars/person over the 30-year period. Repaglinide/metformin had a 96% probability that the incremental costs per quality-adjusted life year gained would be 20,000 dollars or less, and a 66% probability that repaglinide/metformin would be cost-saving compared to nateglinide/metformin. Sensitivity analyses supported the validity and reliability of the results. CONCLUSIONS: In the health economic context, repaglinide/metformin combination was dominant to nateglinide/metformin. The CORE Diabetes Model is a tool to help third-party reimbursement payers identify treatments for type 2 diabetes that are good value for money.
Authors: Todd P Gilmer; Stéphane Roze; William J Valentine; Katrina Emy-Albrecht; Joshua A Ray; David Cobden; Lars Nicklasson; Athena Philis-Tsimikas; Andrew J Palmer Journal: Health Serv Res Date: 2007-10 Impact factor: 3.402
Authors: Katherine Ogurtsova; Thomas L Heise; Ute Linnenkamp; Charalabos-Markos Dintsios; Stefan K Lhachimi; Andrea Icks Journal: Syst Rev Date: 2017-12-29
Authors: Xinyang Hua; Thomas Wai-Chun Lung; Andrew Palmer; Lei Si; William H Herman; Philip Clarke Journal: Pharmacoeconomics Date: 2017-03 Impact factor: 4.981