BACKGROUND: Self-monitoring of blood glucose (SMBG) in type 2 diabetes patients has been shown in meta-analyses of randomized trials to improve HbA(1c) by approximately 0.4% when compared to no SMBG. However, the cost of testing supplies is high, improvements in health utility due to improved glycaemic control may be possible and cost-effectiveness has not been evaluated. METHODS: A peer-reviewed validated model projected improvements in lifetime quality-adjusted life years (QALYs), long-term costs and cost-effectiveness of SMBG versus no SMBG. Markov/Monte Carlo modelling simulated the progression of complications (cardiovascular, neuropathy, renal and eye disease). Transition probabilities and HbA(1c)-dependent adjustments came from the United Kingdom Prospective Diabetes Study (UKPDS) and other major studies. Effects of SMBG on HbA(1c) came from clinical studies, meta-analyses and population studies, but can only be considered 'moderate' levels of evidence. Costs of complications were retrieved from published sources. Direct costs of diabetes complications and SMBG were projected over patient lifetimes from a UK National Health Service perspective. Outcomes were discounted at 3.5% annually. Extensive sensitivity analyses were performed. RESULTS: Depending on the type of diabetes treatment (diet and exercise/oral medications/insulin), improvements in glycaemic control with SMBG improved discounted QALYs anywhere from 0.165 to 0.255 years, with increased total costs of 1013 pounds sterlings- 2564 pounds sterlings/patient, giving incremental cost-effectiveness ratios of 4508 pounds sterlings: 15,515 pounds sterlings/QALY gained, well within current UK willingness-to-pay limits. Results were robust under a wide range of plausible assumptions. CONCLUSIONS: Based on the moderate level of clinical evidence available to date, improvements in glycaemic control with interventions, including SMBG, can improve patient outcomes, with acceptable cost-effectiveness ratios in the UK setting.
BACKGROUND: Self-monitoring of blood glucose (SMBG) in type 2 diabetespatients has been shown in meta-analyses of randomized trials to improve HbA(1c) by approximately 0.4% when compared to no SMBG. However, the cost of testing supplies is high, improvements in health utility due to improved glycaemic control may be possible and cost-effectiveness has not been evaluated. METHODS: A peer-reviewed validated model projected improvements in lifetime quality-adjusted life years (QALYs), long-term costs and cost-effectiveness of SMBG versus no SMBG. Markov/Monte Carlo modelling simulated the progression of complications (cardiovascular, neuropathy, renal and eye disease). Transition probabilities and HbA(1c)-dependent adjustments came from the United Kingdom Prospective Diabetes Study (UKPDS) and other major studies. Effects of SMBG on HbA(1c) came from clinical studies, meta-analyses and population studies, but can only be considered 'moderate' levels of evidence. Costs of complications were retrieved from published sources. Direct costs of diabetes complications and SMBG were projected over patient lifetimes from a UK National Health Service perspective. Outcomes were discounted at 3.5% annually. Extensive sensitivity analyses were performed. RESULTS: Depending on the type of diabetes treatment (diet and exercise/oral medications/insulin), improvements in glycaemic control with SMBG improved discounted QALYs anywhere from 0.165 to 0.255 years, with increased total costs of 1013 pounds sterlings- 2564 pounds sterlings/patient, giving incremental cost-effectiveness ratios of 4508 pounds sterlings: 15,515 pounds sterlings/QALY gained, well within current UK willingness-to-pay limits. Results were robust under a wide range of plausible assumptions. CONCLUSIONS: Based on the moderate level of clinical evidence available to date, improvements in glycaemic control with interventions, including SMBG, can improve patient outcomes, with acceptable cost-effectiveness ratios in the UK setting.
Authors: Lisa M McAndrew; Carol R Horowitz; Kristie J Lancaster; Karen S Quigley; Leonard M Pogach; Pablo A Mora; Howard Leventhal Journal: J Diabetes Date: 2011-06 Impact factor: 4.006
Authors: Alberto de Leiva; María Elena Hernando; M Rigla; I Capel; E Brugués; B Pons; L Erdozain; A Prados; R Corcoy; E J Gómez; G García-Sáez; I Martínez-Sarriegui; A Rodríguez-Herrero; C Pérez-Gandía; F del Pozo Journal: Diabetes Care Date: 2009-11 Impact factor: 19.112