INTRODUCTION: Adding pioglitazone or rosiglitazone to existing therapy are alternative treatment options for patients with type 2 diabetes mellitus who have insufficient glycaemic control while receiving the maximal tolerated dose of metformin monotherapy. Our objective was to develop a lifetime model of type 2 diabetes mellitus and its sequelae in order to compare the costs and benefits of pioglitazone versus rosiglitazone in combination with metformin. METHODS: A decision-analytic model employing a first order Monte Carlo simulation of a Markov process was constructed. The model incorporated surrogate outcome measures from a large randomised controlled trial (RCT) [n = 802] that compared the glycaemic and lipid control of pioglitazone and rosiglitazone monotherapy. These efficacy data were used with a recently validated and peer-reviewed UKPDS (UK Prospective Diabetes Study) algorithm to simulate the progression of these surrogate outcomes to final health outcomes, including quality of life (QOL) and mortality, and to calculate the risks of diabetic complications and death. The model perspective was of the UK NHS and included direct healthcare costs only (pounds, 2004/5 values). Patient outcomes measured in the model included life-expectancy (LE) and QALYs. The base-case analysis was run for 56-year-old male Caucasions with a haemoglobin A(1c) (HbA(1c)) of 7.57% and a body mass index of 33.14 kg/m(2). RESULTS: Patients treated with pioglitazone experienced a reduction in the total cholesterol to high-density lipoprotein-cholesterol (TC : HDL-C) ratio of 0.34, whereas the TC : HDL-C ratio increased by 0.65 in those receiving rosiglitazone (p < 0.001). The HbA(1c) profile was similar between the treatment groups (p = 0.13), as were other known risk factors for diabetes complications. The lifetime healthcare costs per patient estimated by the model were 9585 pounds for pioglitazone and 10,299 pounds for rosiglitazone. Patients treated with pioglitazone had a discounted LE of 8.83 years versus 8.79 years for those treated with rosiglitazone. Patients treated with pioglitazone also gained additional QALYs (6.8070 vs 6.7686). With improved health outcomes and lower costs, treatment with pioglitazone dominated rosiglitazone treatment. CONCLUSION: Evidence from the only large head-to-head RCT comparing rosiglitazone and pioglitazone suggests that more favourable changes in serum lipid profiles in patients treated with pioglitazone translate into improved health outcomes in terms of reduced morbidity and mortality and greater gains in QOL. In addition, this analysis indicates that treatment with pioglitazone is associated with lower costs than rosiglitazone. Therefore, in the UK, adjunctive pioglitazone may represent a cost-effective treatment choice for patients with type 2 diabetes who have insufficient glycaemic control while receiving the maximal tolerated dose of metformin monotherapy.
RCT Entities:
INTRODUCTION: Adding pioglitazone or rosiglitazone to existing therapy are alternative treatment options for patients with type 2 diabetes mellitus who have insufficient glycaemic control while receiving the maximal tolerated dose of metformin monotherapy. Our objective was to develop a lifetime model of type 2 diabetes mellitus and its sequelae in order to compare the costs and benefits of pioglitazone versus rosiglitazone in combination with metformin. METHODS: A decision-analytic model employing a first order Monte Carlo simulation of a Markov process was constructed. The model incorporated surrogate outcome measures from a large randomised controlled trial (RCT) [n = 802] that compared the glycaemic and lipid control of pioglitazone and rosiglitazone monotherapy. These efficacy data were used with a recently validated and peer-reviewed UKPDS (UK Prospective Diabetes Study) algorithm to simulate the progression of these surrogate outcomes to final health outcomes, including quality of life (QOL) and mortality, and to calculate the risks of diabetic complications and death. The model perspective was of the UK NHS and included direct healthcare costs only (pounds, 2004/5 values). Patient outcomes measured in the model included life-expectancy (LE) and QALYs. The base-case analysis was run for 56-year-old male Caucasions with a haemoglobin A(1c) (HbA(1c)) of 7.57% and a body mass index of 33.14 kg/m(2). RESULTS:Patients treated with pioglitazone experienced a reduction in the total cholesterol to high-density lipoprotein-cholesterol (TC : HDL-C) ratio of 0.34, whereas the TC : HDL-C ratio increased by 0.65 in those receiving rosiglitazone (p < 0.001). The HbA(1c) profile was similar between the treatment groups (p = 0.13), as were other known risk factors for diabetes complications. The lifetime healthcare costs per patient estimated by the model were 9585 pounds for pioglitazone and 10,299 pounds for rosiglitazone. Patients treated with pioglitazone had a discounted LE of 8.83 years versus 8.79 years for those treated with rosiglitazone. Patients treated with pioglitazone also gained additional QALYs (6.8070 vs 6.7686). With improved health outcomes and lower costs, treatment with pioglitazone dominated rosiglitazone treatment. CONCLUSION: Evidence from the only large head-to-head RCT comparing rosiglitazone and pioglitazone suggests that more favourable changes in serum lipid profiles in patients treated with pioglitazone translate into improved health outcomes in terms of reduced morbidity and mortality and greater gains in QOL. In addition, this analysis indicates that treatment with pioglitazone is associated with lower costs than rosiglitazone. Therefore, in the UK, adjunctive pioglitazone may represent a cost-effective treatment choice for patients with type 2 diabetes who have insufficient glycaemic control while receiving the maximal tolerated dose of metformin monotherapy.
Authors: S M Grundy; I J Benjamin; G L Burke; A Chait; R H Eckel; B V Howard; W Mitch; S C Smith; J R Sowers Journal: Circulation Date: 1999-09-07 Impact factor: 29.690
Authors: Karl Claxton; Mark Sculpher; Chris McCabe; Andrew Briggs; Ron Akehurst; Martin Buxton; John Brazier; Tony O'Hagan Journal: Health Econ Date: 2005-04 Impact factor: 3.046
Authors: P M Clarke; A M Gray; A Briggs; A J Farmer; P Fenn; R J Stevens; D R Matthews; I M Stratton; R R Holman Journal: Diabetologia Date: 2004-10-27 Impact factor: 10.122
Authors: Aliasghar Ahmad Kiadaliri; Ulf-G Gerdtham; Peter Nilsson; Björn Eliasson; Soffia Gudbjörnsdottir; Katarina Steen Carlsson Journal: PLoS One Date: 2013-05-09 Impact factor: 3.240