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Abstract: Aims: Insulin therapy is indicated for people with Type 1 diabetes mellitus; however, treatment‐related weight gain and hypoglycaemia represent barriers to optimal glycaemic management. This study assessed the health economic value of maintained reductions in HbA1c, BMI and hypoglycaemia incidence among the UK Type 1 diabetes population. Methods: The Cardiff Type 1 Diabetes Model was used to estimate lifetime costs, life‐years and quality‐adjusted life‐years (QALYs) for individuals with Type 1 diabetes at different baseline HbA1c, BMI and hypoglycaemic event rates. Results were discounted at 3.5%, and the net monetary benefit associated with improving Type 1 diabetes management was derived at £20 000/QALY gained. Per‐person outputs were inflated to national levels using UK Type 1 diabetes prevalence estimates. Results: Modelled subjects with an HbA1c of 86 mmol/mol (10.0%) were associated with discounted lifetime per‐person costs of £23 795; £12 649 of which may be avoided by maintaining an HbA1c of 42 mmol/mol (6.0%). Combined with estimated QALY gains of 2.80, an HbA1c of 42 mmol/mol (6.0%) vs. 86 mmol/mol (10.0%) was associated with a £68 621 per‐person net monetary benefit. Over 1 year, unit reductions in BMI produced £120 per‐person net monetary benefit, and up to £197 for the avoidance of one non‐severe hypoglyceamic event. Conclusions: Maintained reductions in HbA1c significantly alleviate the burden associated with Type 1 diabetes in the UK. Given the influence of weight and hypoglycaemia on health economic outcomes, they must also be key considerations when assessing the value of Type 1 diabetes technologies in clinical practice. [ABSTRACT FROM AUTHOR]

AimsThe efficacy and safety of sodium–glucose linked transporters (SGLT2s) plus metformin and a sulfonylurea (MET + SU) for the treatment of type 2 diabetes mellitus (T2DM) in patients who fail to achieve glycemic control with MET + SU, relative to other triple therapies licensed in the EU, were estimated. MethodsA systematic literature review and network meta-analysis (NMA) of randomized controlled trials (RCTs) involving anti-diabetes treatments added to MET + SU were conducted. Results:Of 2236 abstracts identified through a systematic literature review, 30 RCTs published between 2003 and 2013 were included. RCTs ranged from 12 to 52 weeks in duration, included 28 to 1274 patients, were of parallel design, and most were open-label. Comparators included placebo (reference treatment), SGLT2 inhibitors, dipeptidyl peptidase-4 (DPP-4) inhibitors, thiazolidinediones (TZDs), alpha-glucosidase inhibitors (AGIs), meglitinides, glucagon-like peptide 1 (GLP-1) analogues, and basal, bolus, and biphasic insulin, all added on to MET + SU, as well as basal and biphasic insulin added to MET and monotherapy. The mean change (%) in HbA1c levels compared to placebo was -0.86 for SGLT2 inhibitors, −0.68 for DPP-4 inhibitors, −0.93 for TZDs, and −1.07 for GLP-1 analogues, respectively. Only SGLT2 inhibitors and GLP-1 analogues led to a weight loss (−1.71 kg and −1.14 kg, respectively) and decrease in systolic blood pressure (SBP; −3.73 mmHg and −2.90 mmHg, respectively), while all other treatments showed either an increase or no changes in weight or SBP. ConclusionSGLT2 inhibitors are at least as effective as other classes of antidiabetic agents at controlling HbA1c levels, while providing the additional benefits of weight loss and reducing SBP. Additionally, since the risk of hypoglycemia is similar or reduced with SGLT2 inhibitors, patients do not have to trade off efficacy for tolerability. Similar findings were observed for GLP-1 analogues. [ABSTRACT FROM PUBLISHER]

Background: Type 2 diabetes mellitus (T2DM) is a chronic, progressive condition where the primary treatment goal is to maintain control of glycated haemoglobin (HbA1c). In order for healthcare decision makers to ensure patients receive the highest standard of care within the available budget, the clinical benefits of each treatment option must be balanced against the economic consequences. The aim of this study was to assess the cost-effectiveness of dapagliflozin, the first-in-class sodium-glucose co-transporter 2 (SGLT2) inhibitor, compared with a dipeptidyl peptidase-4 inhibitor (DPP-4i), when added to metformin for the treatment of patients with T2DM inadequately controlled on metformin alone.Methods: The previously published and validated Cardiff diabetes model was used as the basis for this economic evaluation, with treatment effect parameters sourced from a systematic review and network meta-analysis. Costs, derived from a UK healthcare system perspective, and quality-adjusted life years (QALYs), were used to present the final outcome as an incremental cost-effectiveness ratio (ICER) over a lifetime horizon. Univariate and probabilistic sensitivity analyses (PSA) were carried out to assess uncertainty in the model results.Results: Compared with DPP-4i, dapagliflozin was associated with a mean incremental benefit of 0.032 QALYs (95% confidence interval [CI]: -0.022, 0.140) and with an incremental cost of £216 (95% CI: £-258, £795). This resulted in an ICER point estimate of £6,761 per QALY gained. Sensitivity analysis determined incremental costs to be insensitive to variation in most parameters, with only the treatment effect on weight having a notable impact on the incremental QALYs; however, there were no scenarios which raised the ICER above £15,000 per QALY. The PSA estimated that dapagliflozin had an 85% probability of being cost-effective at a willingness-to-pay threshold of £20,000 per QALY gained.Conclusions: Dapagliflozin in combination with metformin was shown to be a cost-effective treatment option from a UK healthcare system perspective for patients with T2DM who are inadequately controlled on metformin alone. [ABSTRACT FROM AUTHOR]

Background: Simulation techniques are well suited to modelling diseases yet can be computationally intensive. This study explores the relationship between modelled effect size, statistical precision, and efficiency gains achieved using variance reduction and an executable programming language.Methods: A published simulation model designed to model a population with type 2 diabetes mellitus based on the UKPDS 68 outcomes equations was coded in both Visual Basic for Applications (VBA) and C++. Efficiency gains due to the programming language were evaluated, as was the impact of antithetic variates to reduce variance, using predicted QALYs over a 40-year time horizon.Results: The use of C++ provided a 75- and 90-fold reduction in simulation run time when using mean and sampled input values, respectively. For a series of 50 one-way sensitivity analyses, this would yield a total run time of 2 minutes when using C++, compared with 155 minutes for VBA when using mean input values. The use of antithetic variates typically resulted in a 53% reduction in the number of simulation replications and run time required. When drawing all input values to the model from distributions, the use of C++ and variance reduction resulted in a 246-fold improvement in computation time compared with VBA - for which the evaluation of 50 scenarios would correspondingly require 3.8 hours (C++) and approximately 14.5 days (VBA).Conclusions: The choice of programming language used in an economic model, as well as the methods for improving precision of model output can have profound effects on computation time. When constructing complex models, more computationally efficient approaches such as C++ and variance reduction should be considered; concerns regarding model transparency using compiled languages are best addressed via thorough documentation and model validation. [ABSTRACT FROM AUTHOR]

Healthcare decision-makers face difficult decisions regarding COVID-19 booster selection given limited budgets and the need to maximize healthcare gain. A constrained optimization (CO) model was developed to identify booster allocation strategies that minimize bed-days by varying the proportion of the eligible population receiving different boosters, stratified by age, and given limited healthcare expenditure. Three booster options were included: B 1 , costing US $1 per dose, B 2 , costing US $2, and no booster (NB), costing US $0. B 1 and B 2 were assumed to be 55%/75% effective against mild/moderate COVID-19, respectively, and 90% effective against severe/critical COVID-19. Healthcare expenditure was limited to US$2.10 per person; the minimum expected expense using B 1, B 2, or NB for all. Brazil was the base-case country. The model demonstrated that B 1 for those aged <70 years and B 2 for those ≥70 years were optimal for minimizing bed-days. Compared with NB, bed-days were reduced by 75%, hospital admissions by 68%, and intensive care unit admissions by 90%. Total costs were reduced by 60% with medical resource use reduced by 81%. This illustrates that the CO model can be used by healthcare decision-makers to implement vaccine booster allocation strategies that provide the best healthcare outcomes in a broad range of contexts.

Background and Objectives: CKD imposes a significant burden on patients and health care providers, particularly upon reaching kidney failure when patients may require KRT. The Dapagliflozin and Prevention of Adverse Outcomes in CKD (DAPA-CKD) trial demonstrated that dapagliflozin, with standard therapy, reduced CKD progression and KRT requirement. The study objective was to estimate the cost-effectiveness of dapagliflozin for the treatment of CKD from payer perspectives in the United Kingdom, Germany, and Spain., Design, Setting, Participants, & Measurements: We constructed a lifetime Markov model to characterize outcomes in patients with CKD on the basis of the DAPA-CKD trial. Health states were defined by eGFR level and KRT type. Direct health care costs and utility values were sourced from published literature and the DAPA-CKD trial, respectively. Costs and benefits were discounted at 3.5% per annum in the United Kingdom and 3% in Germany and Spain., Results: In patients eligible for the DAPA-CKD trial, treatment with dapagliflozin was predicted to reduce rates of CKD progression, with patients predicted to spend 1.7 (95% credibility interval, 0.8 to 2.4) more years in the eGFR range 15-89 ml/min per 1.73 m 2 versus standard therapy alone (12.1; 95% credibility interval, 8.9 to 14.1 versus 10.4; 95% credibility interval, 7.7 to 12.4 years). Life expectancy (undiscounted) was correspondingly predicted to increase by 1.7 (95% credibility interval, 0.7 to 2.5) years (15.5; 95% credibility interval, 11.1 to 18.2 versus 13.8; 95% credibility interval, 9.9 to 16.5 years). This in addition to reduced incidence of adverse clinical outcomes, including hospitalization for heart failure, resulted in modeled quality-adjusted life year (discounted) gains between 0.82 (95% credibility interval, 0.38 to 1.18) and 1.00 (95% credibility interval, 0.46 to 1.41). These gains translated to incremental cost-effectiveness ratios of $8280, $17,623, and $11,687 in the United Kingdom, Germany, and Spain, respectively, indicating cost-effectiveness at willingness-to-pay thresholds (United Kingdom: $27,510 per quality-adjusted life year; Germany and Spain: $35,503 per quality-adjusted life year)., Conclusions: In patients meeting the eligibility requirements for the DAPA-CKD trial, dapagliflozin is likely to be a cost-effective treatment within the UK, German, and Spanish health care systems., Clinical Trial Registry Name and Registration Number: Dapagliflozin and Prevention of Adverse Outcomes in CKD (DAPA-CKD), NCT03036150., (Copyright © 2022 by the American Society of Nephrology.)