“…1 ). The model has been validated for established effects of AHAs on parameters including glucose, body weight, BP, and renal function [ 19 , 34 , 35 ], and its application to cost-effectiveness evaluations of canagliflozin has been reported in detail elsewhere [ 21 , 23 ]. …”
IntroductionAgents that inhibit sodium glucose co-transporter 2 (SGLT2), including canagliflozin and dapagliflozin, are approved in the United States for the treatment of adults with type 2 diabetes mellitus (T2DM). SGLT2 inhibition lowers blood glucose by increasing urinary glucose excretion, which leads to a mild osmotic diuresis and a net loss of calories that are associated with reductions in body weight and blood pressure. This analysis evaluated the cost-effectiveness of canagliflozin 300 mg versus dapagliflozin 10 mg in patients with T2DM inadequately controlled with metformin in the United States.MethodsA 30-year cost-effectiveness analysis was performed using the validated Economic and Health Outcomes Model of T2DM (ECHO-T2DM) from the perspective of the third-party health care system in the United States. Patient demographics, biomarker values, and treatment effects for the ECHO-T2DM model were sourced primarily from a network meta-analysis (NMA) that included studies of canagliflozin and dapagliflozin in patients with T2DM on background metformin. Costs were derived from sources specific to the United States. Outcomes and costs were discounted at 3%. Sensitivity analyses that varied key model parameters were conducted.ResultsCanagliflozin 300 mg dominated dapagliflozin 10 mg as an add-on to metformin over 30 years, with an estimated cost offset of $13,991 and a quality-adjusted life-year gain of 0.08 versus dapagliflozin 10 mg. Results were driven by the better HbA1c lowering achieved with canagliflozin, which translated to less need for insulin rescue therapy. Findings from sensitivity analyses were consistent with the base case.ConclusionThese results suggest that canagliflozin 300 mg is likely to provide better health outcomes at a lower overall cost than dapagliflozin 10 mg in patients with T2DM inadequately controlled with metformin from the perspective of the United States health care system.FundingJanssen Scientific Affairs, LLC and Janssen Global Services, LLC.Electronic supplementary materialThe online version of this article (10.1007/s13300-018-0371-y) contains supplementary material, which is available to authorized users.
“…1 ). The model has been validated for established effects of AHAs on parameters including glucose, body weight, BP, and renal function [ 19 , 34 , 35 ], and its application to cost-effectiveness evaluations of canagliflozin has been reported in detail elsewhere [ 21 , 23 ]. …”
IntroductionAgents that inhibit sodium glucose co-transporter 2 (SGLT2), including canagliflozin and dapagliflozin, are approved in the United States for the treatment of adults with type 2 diabetes mellitus (T2DM). SGLT2 inhibition lowers blood glucose by increasing urinary glucose excretion, which leads to a mild osmotic diuresis and a net loss of calories that are associated with reductions in body weight and blood pressure. This analysis evaluated the cost-effectiveness of canagliflozin 300 mg versus dapagliflozin 10 mg in patients with T2DM inadequately controlled with metformin in the United States.MethodsA 30-year cost-effectiveness analysis was performed using the validated Economic and Health Outcomes Model of T2DM (ECHO-T2DM) from the perspective of the third-party health care system in the United States. Patient demographics, biomarker values, and treatment effects for the ECHO-T2DM model were sourced primarily from a network meta-analysis (NMA) that included studies of canagliflozin and dapagliflozin in patients with T2DM on background metformin. Costs were derived from sources specific to the United States. Outcomes and costs were discounted at 3%. Sensitivity analyses that varied key model parameters were conducted.ResultsCanagliflozin 300 mg dominated dapagliflozin 10 mg as an add-on to metformin over 30 years, with an estimated cost offset of $13,991 and a quality-adjusted life-year gain of 0.08 versus dapagliflozin 10 mg. Results were driven by the better HbA1c lowering achieved with canagliflozin, which translated to less need for insulin rescue therapy. Findings from sensitivity analyses were consistent with the base case.ConclusionThese results suggest that canagliflozin 300 mg is likely to provide better health outcomes at a lower overall cost than dapagliflozin 10 mg in patients with T2DM inadequately controlled with metformin from the perspective of the United States health care system.FundingJanssen Scientific Affairs, LLC and Janssen Global Services, LLC.Electronic supplementary materialThe online version of this article (10.1007/s13300-018-0371-y) contains supplementary material, which is available to authorized users.
“…They notice that diabetes-related hospitalisations were significantly higher among patients with uncontrolled diabetes. 2 For a broader overview on the relationship between diabetes and its related costs, see the United Kingdom Prospective Diabetes Study UKPDS Outcomes Model; the Economic and Health Outcomes Model of Type 2 Diabetes Mellitus (ECHO-T2DM); the Michigan Model for Diabetes (MMD); Cardiff Diabetes Model; the School of Public Health Research (SPHR) Diabetes Prevention Model and the Modelling Integrated Care for Diabetes based on Observational data (MICADO) model [25][26][27][28][29][30]. Although they do not specifically focus on uncontrolled diabetes, these are comprehensive models capable of simulating the progression of diabetes under different scenarios, including diabetes-related complications and estimating the cost-effectiveness of specific interventions.…”
Despite size and relevance of uncontrolled diabetes, robust evidence on its effects on health care utilisation is very limited, especially among European countries. We employed longitudinal administrative data from Spain (2004-2010) to explore the relationship between uncontrolled type 2 diabetes and health care utilisation. We used a biomarker (glycated haemoglobin, HbA1c) to detect the presence of uncontrolled diabetes and explore its effects on both primary and secondary health care. We estimated a range of panel count data models, including negative binomials with random effects, dynamic and hurdle specifications to account for unobserved heterogeneity, previous utilisation and selection. We found uncontrolled diabetes in between 27 and 30% of patients of both genders. Our estimates suggested that although women appeared to systematically consume more health care compared to men, their consumption levels did not seem to be influenced by uncontrolled diabetes. Conversely, among men uncontrolled diabetes increased the average number of GP visits per year by between 3 and 3.4%, specialist visits by 5.3-6.1%, depending on specifications, and also extended annual hospital length of stay by 15%. We also found some evidence of heterogeneity in utilisation based on the level of uncontrolled diabetes among male individuals. Overall, our results suggested the need for different diabetes management plans depending on gender and levels of glycaemic control.
“…Researchers should define statistical metrics to assess consistency of HE model results and empirical data [3,5]. Although there is no "gold standard" criterion [15][16][17][18][19][20][21][22][23][24], according to the systematic review by Goldhaber-Fiebert et al [25], the most frequently used metrics of consistency in HE are the relative or absolute difference in model and study point estimates, the overlap of model outcomes with study uncertainty ranges, and formal statistical tests.…”
Section: Using the Statistical Methods Rightmentioning
Current practice in HE model validation can be improved by using an alternative method based on assessing whether the model outcomes fit to empirical data at a predefined level of accuracy. This method has the advantage of assessing both model bias and parameter uncertainty and resulting in a quantitative measure of the degree of validity that penalizes models predicting the mean of an outcome correctly but with overly wide credible intervals.
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