The cost-effectiveness of dapagliflozin in treating high-risk patients with type 2 diabetes mellitus: An economic evaluation using data from the DECLARE-TIMI 58 trial.

AIM: To undertake a cost-effectiveness analysis of dapagliflozin in treating high-risk patients with type 2 diabetes mellitus (T2DM), using both directly observed events in the DECLARE-TIMI 58 trial and surrogate risk factors to predict endpoints not captured within the trial. METHODS: An established T2DM model was adapted to integrate survival curves derived from the DECLARE-TIMI 58 trial, and extrapolated over a lifetime for all-cause mortality, hospitalization for heart failure, stroke, myocardial infarction, hospitalization for unstable angina, and end-stage kidney disease. The economic analysis considered the overall DECLARE trial population, as well as reported patient subgroups. Total and incremental costs, life-years and quality-adjusted life-years associated with dapagliflozin versus placebo were estimated from the perspective of the UK healthcare payer. RESULTS: In the UK setting, treatment with dapagliflozin compared to placebo was estimated to be dominant, with an expected increase in quality-adjusted life-years from 10.43 to 10.48 (+0.06) and a reduction in lifetime total costs from £39 451 to £36 899 (-£2552). Across all patient subgroups, dapagliflozin was estimated to be dominant, with the greatest absolute benefit in the prior heart failure subgroup (incremental lifetime costs -£4150 and quality-adjusted life-years +0.11). CONCLUSIONS: The results of this study demonstrate that dapagliflozin compared to placebo appears to be cost-effective, when considering evidence reported from the DECLARE-TIMI 58 trial, at established UK willingness-to-pay thresholds. The findings highlight the potential of dapagliflozin to have a meaningful impact in reducing the economic burden of T2DM and its associated complications across a broad T2DM population.

Cost-effectiveness of dapagliflozin as an adjunct to insulin for the treatment of type 1 diabetes mellitus in the United Kingdom.

AIMS: To assess the cost-effectiveness of dapagliflozin, a sodium-glucose co-transporter-2 (SGLT2) inhibitor, as an adjunct to insulin in adults with type 1 diabetes mellitus (T1DM) inadequately controlled by insulin alone in the UK setting. METHODS: A cost-utility analysis was conducted to compare dapagliflozin (5 mg or 10 mg) added to insulin versus insulin monotherapy (standard of care) over a lifetime horizon. Treatment efficacy and safety data were obtained from 52-week results of the DEPICT-1 and DEPICT-2 trials and a network meta-analysis of SGLT2 inhibitors in T1DM. Direct healthcare costs, life-years, and quality-adjusted life-years (QALYs) were estimated from a UK payer perspective and discounted at 3.5% annually, using the Cardiff T1DM Model. Sensitivity analyses assessed uncertainty in estimated incremental cost-effectiveness ratios (ICERs). RESULTS: Dapagliflozin 5 mg was associated with gains of 0.23 life-years and 0.42 QALYs, at an additional cost of £4240 per person; corresponding to an ICER of £10 143 versus standard of care. For dapagliflozin 10 mg, incremental life-years, QALYs and costs were 0.24, 0.49 and £2964, respectively; corresponding to an ICER of £6103 versus standard of care. In probabilistic sensitivity analysis, ICER estimates fell below £20 000/QALY in 78% to 90% of simulations. Cost-effectiveness results were sensitive to changes in baseline patient characteristics and treatment effects on glycated haemoglobin; however, ICERs remained below £20 000. CONCLUSIONS: At cost-effectiveness thresholds conventionally applied in the UK, dapagliflozin as an adjunct to insulin appears to be a cost-effective treatment option for people with T1DM inadequately controlled by insulin alone.

An alternative approach to modelling HbA1c trajectories in patients with type 2 diabetes mellitus.

AIMS: Time-dependent HbA1c trajectories in health economic models of type 2 diabetes mellitus (T2DM) are typically informed by the UK Prospective Diabetes Study (UKPDS). However, this approach may not accurately predict HbA1c progression in patients who do not conform to the demographic profile of the original UKPDS cohort. This study aimed to develop an alternative mathematical model (MM) to simulate HbA1c progression in T2DM. MATERIALS AND METHODS: A systematic literature review identified studies, published between 2005 and 2015, that reported HbA1c in adult T2DM patients over a minimum duration of 18 months. Pooled data from eligible studies were used to develop an alternative MM equation for HbA1c progression, which was then contrasted with the UKPDS 68 progression equation in illustrative scenarios. RESULTS: A total of 68 studies were eligible for data extraction (mean follow-up time 4.1 years). HbA1c progression was highly heterogeneous across studies, varying with baseline HbA1c, treatment group and patient age. The MM equation was fitted with parameters for mean baseline HbA1c (8.3%), initial change in HbA1c (-0.62%) and upper quartile of maximum observed HbA1c (9.3%). Differences in HbA1c trajectories between the MM and UKPDS approaches altered the timing of therapy escalation in illustrative scenarios. CONCLUSIONS: The MM represents an alternative approach to simulate HbA1c trajectories in T2DM models, as UKPDS data may not adequately reflect the heterogeneity of HbA1c profiles observed in clinical studies. However, the choice of approach should ultimately be determined by the characteristics of individual patients under consideration and the clinical face validity of the modelled trajectories.

Validation of the UKPDS 82 risk equations within the Cardiff Diabetes Model.

BACKGROUND: For end-users of diabetes models that include UKPDS 82 risk equations, an important question is how well these new equations perform. Consequently, the principal objective of this study was to validate the UKPDS 82 risk equations, embedded within an established type 2 diabetes mellitus (T2DM) model, the Cardiff Diabetes Model, to contemporary T2DM outcomes studies. METHODS: A total of 100 validation endpoints were simulated across treatment arms of twelve pivotal T2DM outcomes studies, simulation cohorts representing each validation study's cohort profile were generated and intensive and conventional treatment arms were defined in the Cardiff Diabetes Model. RESULTS: Overall the validation coefficient of determination was similar between both sets of risk equations: UKPDS 68, R(2) = 0.851; UKPDS 82, R(2) = 0.870. Results stratified by internal and external validation studies produced MAPE of 43.77 and 37.82%, respectively, when using UKPDS 82, and MAPE of 40.49 and 53.92%, respectively when using UKPDS 68. Areas of lack of fit, as measured by MAPE were inconsistent between sets of equations with ACCORD demonstrating a noteworthy lack of fit with UKPPDS 68 (MAPE = 170.88%) and the ADDITION study for UKPDS 82 (MAPE = 89.90%). CONCLUSIONS: This study has demonstrated that the UKPDS 82 equations exhibit similar levels of external validity to the UKPDS 68 equations with the additional benefit of enabling more diabetes related endpoints to be modeled.

Identification of an Optimal COVID-19 Booster Allocation Strategy to Minimize Hospital Bed-Days with a Fixed Healthcare Budget.

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: B1, costing US $1 per dose, B2, costing US $2, and no booster (NB), costing US $0. B1 and B2 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 B1, B2, or NB for all. Brazil was the base-case country. The model demonstrated that B1 for those aged <70 years and B2 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.

Cardiorenal disease in the United States: Future health care burden and potential impact of novel therapies.

BACKGROUND: Currently, concerted efforts to identify, prevent, and treat type 2 diabetes mellitus (T2DM), heart failure (HF), and chronic kidney disease (CKD) comorbidities are lacking at the institutional level, with emphasis placed on individual specialties. An integrated approach to tackle T2DM, HF, and CKD within the context of cardiorenal disease has the potential to improve outcomes and reduce costs at the system level. OBJECTIVE: To synthesize published evidence describing the burden of those diagnosed with T2DM, HF, and CKD in the United States as individual discrete chronic conditions, in order to evaluate the potential economic impact of novel therapies in this population. METHODS: We developed a compartmental Markov model with an annual time cycle to model an evolving prevalent US patient population with T2DM, HF, or CKD over the period 2021-2030 (either in isolation or combined). The model was used to explore the potential impact of novel therapies such as sodium-glucose cotransporter 2 inhibitors on future disease burden, by extrapolating the results of relevant clinical trials to representative patient populations. RESULTS: The model estimates that total prevalence across all disease states will have increased by 28% in 2030. Cumulatively, the direct health care cost of cardiorenal disease between 2021 and 2030 is estimated at $4.8 trillion. However, treatment with dapagliflozin has the potential to reduce disease prevalence by 8.0% and estimated cumulative service delivery costs by 3.6% by 2030. CONCLUSIONS: Considering a holistic approach when managing patients with cardiorenal disease offers an opportunity to reduce the disease burden over the next 10 years in the US population. DISCLOSURES: This work was funded by AstraZeneca, which provided support for data analysis. McEwan, Morgan, and Boyce are employees of Health Economics and Outcomes Research Ltd., Cardiff, UK, which received fees from AstraZeneca in relation to this study. Song and Huang are employees of AstraZeneca. Bergenheim is an employee of AstraZeneca and holds AstraZeneca stocks/stock options. Green has no conflicts of interest to declare.

Modeling Chronic Kidney Disease in Type 2 Diabetes Mellitus: A Systematic Literature Review of Models, Data Sources, and Derivation Cohorts.

INTRODUCTION: As novel therapies for chronic kidney disease (CKD) in type 2 diabetes mellitus (T2DM) become available, their long-term benefits should be evaluated using CKD progression models. Existing models offer different modeling approaches that could be reused, but it may be challenging for modelers to assess commonalities and differences between the many available models. Additionally, the data and underlying population characteristics informing model parameters may not always be evident. Therefore, this study reviewed and summarized existing modeling approaches and data sources for CKD in T2DM, as a reference for future model development. METHODS: This systematic literature review included computer simulation models of CKD in T2DM populations. Searches were implemented in PubMed (including MEDLINE), Embase, and the Cochrane Library, up to October 2021. Models were classified as cohort state-transition models (cSTM) or individual patient simulation (IPS) models. Information was extracted on modeled kidney disease states, risk equations for CKD, data sources, and baseline characteristics of derivation cohorts in primary data sources. RESULTS: The review identified 49 models (21 IPS, 28 cSTM). A five-state structure was standard among state-transition models, comprising one kidney disease-free state, three kidney disease states [frequently including albuminuria and end-stage kidney disease (ESKD)], and one death state. Five models captured CKD regression and three included cardiovascular disease (CVD). Risk equations most commonly predicted albuminuria and ESKD incidence, while the most predicted CKD sequelae were mortality and CVD. Most data sources were well-established registries, cohort studies, and clinical trials often initiated decades ago in predominantly White populations in high-income countries. Some recent models were developed from country-specific data, particularly for Asian countries, or from clinical outcomes trials. CONCLUSION: Modeling CKD in T2DM is an active research area, with a trend towards IPS models developed from non-Western data and single data sources, primarily recent outcomes trials of novel renoprotective treatments.

The clinical effects of new treatments and their costs are often evaluated over a longer time frame than is possible in clinical trials by using computer simulation models. As new treatments are becoming available to treat chronic kidney disease, including in patients with type 2 diabetes, chronic kidney disease models may be used to inform clinical and economic decisions regarding these new treatment options. In the present study, we identified 49 published simulation models of chronic kidney disease used in populations with type 2 diabetes, and reviewed their structures and the data sources they used. The models focused mostly on disease states and outcomes associated with albuminuria (a condition in which the protein albumin is found in the urine) and end-stage kidney disease. Model structures with five disease states, including a kidney disease-free state, three kidney disease states, and death, were the most common. Relatively few models used glomerular filtration rates (a common measure of kidney function) or captured the possibility of an improvement in chronic kidney disease. Important data sources for many models were patient registries, cohort studies, and clinical trials, most conducted several decades ago in high-income countries with a high proportion of White participants. Several models developed in the past 5 years, particularly for Asian countries, instead relied largely or exclusively on country-specific data. In parallel, several individual patient simulations were recently developed from large outcomes trials for new treatments, including from trial subgroups covering specific geographical settings or ethnicities, shortly after trial publication.

Cost-Effectiveness of Dapagliflozin as a Treatment for Chronic Kidney Disease: A Health-Economic Analysis of DAPA-CKD.

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 m2 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.

Cost-effectiveness of dapagliflozin as a treatment for heart failure with reduced ejection fraction: a multinational health-economic analysis of DAPA-HF.

AIM: To estimate the cost-effectiveness of dapagliflozin added to standard therapy, vs. standard therapy only, in patients with heart failure (HF) with reduced ejection fraction (HFrEF), from the perspective of UK, German, and Spanish payers. METHODS AND RESULTS: A lifetime Markov model was built to estimate outcomes in patients with HFrEF. Health states were defined by Kansas City Cardiomyopathy Questionnaire total symptom score, type 2 diabetes and worsening HF events. The incidence of worsening HF and all-cause mortality was estimated using negative binomial regression models and parametric survival analysis, respectively. Direct healthcare costs (2019 British pounds/Euro) and patient-reported outcomes (EQ-5D) were sourced from the existing literature and the Dapagliflozin And Prevention of Adverse-outcomes in Heart Failure trial (DAPA-HF), respectively; the median duration of follow-up in DAPA-HF was 18.2 months (range: 0-27.8). Future costs and effects were discounted at 3.0% for the Spanish and German analyses and 3.5% for the UK analysis. In the UK setting, treatment with dapagliflozin was estimated to increase life-years and quality-adjusted life-years (QALYs) from 5.62 to 6.20 (+0.58) and 4.13 to 4.61 (+0.48), respectively, and reduce lifetime hospitalizations for HF (925 and 820 events per 1000 patients for placebo and dapagliflozin, respectively). Similar results were obtained for Germany and Spain. The incremental cost-effectiveness ratios were £5822, €5379 and €9406/QALY in the UK, Germany and Spain, respectively. In probabilistic sensitivity analyses, more than 90% of simulations were cost-effective at a willingness-to-pay threshold of £20 000/QALY in UK and €20 000/QALY in Germany and Spain. CONCLUSION: Dapagliflozin is likely to be a cost-effective treatment for HFrEF in the UK, German and Spanish healthcare systems.

Health-related quality-of-life implications of cardiovascular events in individuals with type 2 diabetes mellitus: A subanalysis from the Saxagliptin Assessment of Vascular Outcomes Recorded in Patients with Diabetes Mellitus (SAVOR)-TIMI 53 trial.

BACKGROUND: The impact of cardiovascular complications on health-related quality-of-life (HRQoL) in type 2 diabetes mellitus has not been clearly established. Using EQ5D utility data from SAVOR-TIMI 53, a large phase IV trial of saxagliptin versus placebo, we quantified the impact of cardiovascular and other major events on HRQoL. METHODS: EQ5D utilities were recorded annually and following myocardial infarction (MI) or stroke. Utilities among patients experiencing major cardiovascular events were analyzed using linear mixed-effects regression, adjusting for baseline characteristics (including EQ5D utility), and compared to those not experiencing major cardiovascular events. Mean utility decrements with standard errors (SE) were estimated as the difference in utility before and after the event. FINDINGS: The mean EQ5D utility of the sample was 0.776 at all time points, and did not differ by treatment. However, mean baseline and month 12 utilities among those with a major cardiovascular event were 0.751 and 0.714. Mean utilities were 0.691 within 3months of, 0.691 3-6months after, and 0.714 6-12months after, a major cardiovascular event. Cardiovascular event-specific utility decrements were 0.05 (0.007) for major cardiovascular events over the same time periods. Decrements of 0.051 (0.012; myocardial infarction), 0.111 (0.022; stroke), 0.065 (0.014; hospitalization for heart failure) 0.019 (0.024; hospitalization for hypoglycemia) were estimated; all coefficients were statistically significant. INTERPRETATION: Consistent with clinical outcomes reported elsewhere, saxagliptin did not improve HRQoL. Cardiovascular complications were associated with significantly decreased HRQoL, most substantial earlier after the event. FUNDING: BMS/AZ.

Evaluation of the costs and outcomes from changes in risk factors in type 2 diabetes using the Cardiff stochastic simulation cost-utility model (DiabForecaster).

AIMS: The aim of this study was to determine the mean costs and outcomes associated with modifiable risk factors in patients with type 2 diabetes and to determine equivalent changes to these risk factors in terms of financial costs and health outcomes. METHODS: The Cardiff Stochastic Simulation Cost-Utility Model (DiabForecaster), which evolved from the Eastman model, was used to follow a cohort of 10 000 patients over 20 years. RESULTS: Costs were affected most significantly by changes in the total cholesterol to HDL cholesterol (Total-C:HDL-C) ratio and in HbA(1c). Unit increases in Total-C:HDL-C increased discounted costs by pound 200 per patient; for ratios > 8 units, unit increases led to cost increases of pound 300 per patient. Unit increases in HbA(1c) increased per patient discounted costs from pound 200 (5-6%) up to pound 2900 (10-11%). Similar patterns were observed for QALYs. Estimates of equivalence showed that a 1% reduction in HbA(1c) was equivalent to an 0.4 increment in QALYs, which was equivalent to a reduction of 44 mmHg in SBP, 18.2 mg/dL in HDL, 100 mg/dL in total cholesterol or 1.8 units of Total-C:HDL-C ratio. A 1% reduction in HbA(1c) was also equivalent to pound 108 less cost, which was equivalent to a 13.0 mmHg decrease in SBP or a 0.57 unit decrease in the Total-C:HDL-C ratio. CONCLUSIONS: This model provides reliable utility estimates for diabetic complications and may eliminate uncertainty in cost-effectiveness analyses of treatment. These data also provide a novel way of comparing the value of treatments that have multiple effects.

A Systematic Review of Cost-Effectiveness Models in Type 1 Diabetes Mellitus.

BACKGROUND: Critiques of cost-effectiveness modelling in type 1 diabetes mellitus (T1DM) are scarce and are often undertaken in combination with type 2 diabetes mellitus (T2DM) models. However, T1DM is a separate disease, and it is therefore important to appraise modelling methods in T1DM. OBJECTIVES: This review identified published economic models in T1DM and provided an overview of the characteristics and capabilities of available models, thus enabling a discussion of best-practice modelling approaches in T1DM. METHODS: A systematic review of Embase(®), MEDLINE(®), MEDLINE(®) In-Process, and NHS EED was conducted to identify available models in T1DM. Key conferences and health technology assessment (HTA) websites were also reviewed. The characteristics of each model (e.g. model structure, simulation method, handling of uncertainty, incorporation of treatment effect, data for risk equations, and validation procedures, based on information in the primary publication) were extracted, with a focus on model capabilities. RESULTS: We identified 13 unique models. Overall, the included studies varied greatly in scope as well as in the quality and quantity of information reported, but six of the models (Archimedes, CDM [Core Diabetes Model], CRC DES [Cardiff Research Consortium Discrete Event Simulation], DCCT [Diabetes Control and Complications Trial], Sheffield, and EAGLE [Economic Assessment of Glycaemic control and Long-term Effects of diabetes]) were the most rigorous and thoroughly reported. Most models were Markov based, and cohort and microsimulation methods were equally common. All of the more comprehensive models employed microsimulation methods. Model structure varied widely, with the more holistic models providing a comprehensive approach to microvascular and macrovascular events, as well as including adverse events. The majority of studies reported a lifetime horizon, used a payer perspective, and had the capability for sensitivity analysis. CONCLUSIONS: Several models have been developed that provide useful insight into T1DM modelling. Based on a review of the models identified in this study, we identified a set of 'best in class' methods for the different technical aspects of T1DM modelling.

The Health Economic Value of Changes in Glycaemic Control, Weight and Rates of Hypoglycaemia in Type 1 Diabetes Mellitus.

AIMS: Therapy-related consequences of treatment for type 1 diabetes mellitus (T1DM), such as weight gain and hypoglycaemia, act as a barrier to attaining optimal glycaemic control, indirectly influencing the incidence of vascular complications and associated morbidity and mortality. This study quantifies the individual and combined contribution of changes in hypoglycaemia frequency, weight and HbA1c to predicted quality-adjusted life-years (QALYs) within a T1DM population. MATERIALS AND METHODS: We describe the Cardiff Type 1 Diabetes (CT1DM) Model, originally informed by the Diabetes Control and Complications Trial (DCCT) and updated with the Epidemiology of Diabetes Interventions and Complications (EDIC) study and Swedish National Diabetes Registry for microvascular and cardiovascular complications respectively. We report model validation results and the QALY impact of HbA1c, weight and hypoglycaemia changes. RESULTS: Validation results demonstrated coefficients of determination for clinical endpoints of R2 = 0.863 (internal R2 = 0.999; external R2 = 0.823), costs R2 = 0.980 and QALYs R2 = 0.951. Achieving and maintaining a 1% HbA1c reduction was estimated to provide 0.61 additional discounted QALYs. Weight changes of ±1kg, ±2kg or ±3kg led to discounted QALY changes of ±0.03, ±0.07 and ±0.10 respectively, while modifying hypoglycaemia frequency by -10%, -20% or -30% resulted in changes of -0.05, -0.11 and -0.17. The differences in discounted costs, life-years and QALYs associated with HbA1c 6% versus 10% were -£19,037, 2.49 and 2.35 respectively. CONCLUSIONS: Using a model updated with contemporary epidemiological data, this study presents an outcome-focused perspective to assessing the health economic consequences of differing levels of glycaemic control in T1DM with and without weight and hypoglycaemia effects.

The Humanistic Burden of Type 1 Diabetes Mellitus in Europe: Examining Health Outcomes and the Role of Complications.

AIMS: Diagnoses of Type 1 Diabetes Mellitus (T1DM) in Europe appear to be on the rise. Therefore it is imperative that researchers understand the potential impact that increases in prevalence could have on the affected individuals as well as on society as a whole. Accordingly this study examined the humanistic and economic burden of T1DM in patients relative to those without the condition across a number of health outcomes including health status, work productivity loss, activity impairment, and healthcare resource use. METHODS: Survey data from a large, representative sample of EU adults (The EU National Health and Wellness Survey) were examined. RESULTS: Results suggest that overall burden is higher for those diagnosed with T1DM than respondents without diabetes and that burden increases as complications associated with T1DM increase. CONCLUSIONS: Taken together, these results suggest that treatment strategies for T1DM should balance clinical, humanistic, and economic burden and patients should be educated on the role of complications in disease outcomes.

Cost-effectiveness of dapagliflozin (Forxiga®) added to metformin compared with sulfonylurea added to metformin in type 2 diabetes in the Nordic countries.

AIMS: The aim of this study was to assess the long-term cost-effectiveness of dapagliflozin (Forxiga(®)) added to metformin, compared with sulfonylurea (SU) added to metformin, in Nordic Type 2 diabetes mellitus (T2DM) patients inadequately controlled on metformin. METHODS: Data from a 52-week clinical trial comparing dapagliflozin and SU in combination with metformin was used in a Cardiff simulation model to estimate long term diabetes-related complications in a cohort of T2DM patients. Costs and QALYs were calculated from a healthcare provider perspective and estimated over a patient's lifetime. RESULTS: Compared with metformin+SU, the cost per QALY gained with dapagliflozin+metformin was €7944 in Denmark, €5424 in Finland, €4769 in Norway, and €6093 in Sweden. Metformin+dapagliflozin was associated with QALY gains ranging from 0.236 in Norway to 0.278 in Sweden and incremental cost ranging from €1125 in Norway to €1962 in Denmark. Results were robust across both one-way and probabilistic sensitivity analyses. Results were driven by weight changes associated with each treatment. CONCLUSIONS: Results indicate that metformin+dapagliflozin is associated with gains in QALY compared with metformin+SU in Nordic T2DM patients inadequately controlled on metformin. Dapagliflozin treatment is a cost-effective treatment alternative for Type 2 diabetes in all four Nordic countries.

Estimating Cost-Effectiveness in Type 2 Diabetes: The Impact of Treatment Guidelines and Therapy Duration.

OBJECTIVES: Type 2 diabetes mellitus (T2DM) clinical guidelines focus on optimizing glucose control, with therapy escalation classically initiated within a "failure-based" regimen. Within many diabetes models, HbA1c therapy escalation thresholds play a pivotal role, controlling duration of therapy and, consequently, incremental costs and benefits. The objective of this study was to assess the relationship between therapy escalation threshold and time to therapy escalation on predicted cost-effectiveness of T2DM treatments. METHODS: This study used the Cardiff Diabetes Model to illustrate the relationship between costs and health outcomes associated with first-, second-, and third-line therapy as a function of time on each. Data from routine clinical practice were used to contrast predicted costs and health outcomes associated with guideline therapy escalation thresholds compared with clinical practice. The impact of baseline HbA1c and therapy escalation thresholds on cost-effectiveness was investigated, comparing a sodium/glucose cotransporter 2 inhibitor v. sulfonylurea added to metformin monotherapy. RESULTS: Lower thresholds are associated with a shorter time spent on monotherapy, ranging from 1.1 years (escalation at 6.5%) to 13 years (escalation at 9.0%) and an increase in total lifetime cost of therapy. Treatment-related disutility is minimized with higher thresholds because progression to insulin is delayed. Using metformin combined with either dapagliflozin or a sulfonylurea to illustrate lower baseline HbA1c and/or higher therapy escalation thresholds was associated with increased cost-effectiveness ratios, driven by a longer duration of therapy. DISCUSSION: A marked difference in treatment cost-effectiveness was demonstrated when comparing routine clinical practice with guideline-advocated therapy escalation. This is important to both health care professionals and the wider health economic community with respect to understanding the true cost-effectiveness profile of any particular T2DM therapy option.

Assessment of Unmet Clinical Need in Type 2 Diabetic Patients on Conventional Therapy in the UK.

INTRODUCTION: Type 2 diabetes mellitus (T2DM) is an increasing problem worldwide and a leading risk factor for cardiovascular disease. As beta cell function declines, the management of T2DM typically comprises of escalations in treatment from diet and exercise to oral therapies and eventually insulin. Treatment algorithms based on the attainment of blood glucose targets may not account for changes in other cardiovascular risk factors. The objective of this study is to describe unmet clinical need, defined as failure to reduce weight or meet targets for blood pressure, total cholesterol or glycated hemoglobin (HbA1c) levels. METHODS: Anonymized UK patient data for those (1) initiating oral antidiabetic drug (OAD) monotherapy, (2) escalating to dual therapy, (3) escalating to triple therapy, and (4) escalating to insulin therapy over the study period (01/01/2005-31/12/2009) were obtained from The Health Improvement Network (THIN). Changes in risk factors were evaluated before and after therapy escalation, and the attainment of targets, assessed at the last recorded measurement, as follows: HbA1c <7.5%, systolic blood pressure (SBP) <140 mmHg, total cholesterol (TC) <5 mmol/L, and reduction in weight. RESULTS: Prior to therapy escalation, mean HbA1c in each subgroup exceeded 7.5% and was higher respective to the number of OADs being used (monotherapy: 8.03%; double: 8.48%; triple: 8.71%). Insulin users displayed the highest HbA1c prior to treatment escalation (9.78%). Following escalation, a decline in HbA1c was observed in all subgroups. By contrast, mean SBP and TC levels decreased prior to the addition of a second and third oral therapy. Consistent improvements following treatment escalation were not observed across the other risk factors following therapy escalation. Overall, the proportion of subjects that attained all four targets ranged from 3% (monotherapy and insulin) to 6% (dual therapy). CONCLUSION: The potential unmet clinical need among conventionally treated T2DM patients is significant, with respect to the control of blood glucose and other cardiovascular risk factors: SBP, TC, and weight. There clearly remains the need for new therapeutic approaches to alleviate the burden associated with T2DM.

Cost effectiveness of adding dapagliflozin to insulin for the treatment of type 2 diabetes mellitus in the Netherlands.

BACKGROUND AND OBJECTIVE: Many patients with type 2 diabetes mellitus (T2DM) on insulin therapy have inadequate glycaemic control. In such cases, Dutch guidelines recommend unlimited up-titration of insulin, yet in practice many patients never reach their glycaemic target. Clinical evidence shows that dapagliflozin-a highly selective sodium-glucose cotransporter 2 inhibitor-meets a need for these patients, i.e. by reducing glycated haemoglobin levels and bodyweight. We estimated the cost effectiveness and cost utility of adding dapagliflozin to insulin compared with not adding dapagliflozin in patients with T2DM who have inadequate glycaemic control while on insulin. METHODS: The cost effectiveness of dapagliflozin was estimated using the Cardiff Diabetes Model, using direct comparative efficacy data from a randomized placebo-controlled trial (ClinicalTrials.gov identifier NCT00673231). In this trial, up-titration of insulin was allowed in case of severe glycaemic imbalance. Risk factor progression and the occurrence of future vascular events were estimated using the United Kingdom Prospective Diabetes Study 68 risk equations. Costs and utilities were derived from the literature. The analysis was conducted from the societal perspective, simulating the remaining lifetime of the patients. RESULTS: The overall incidence of macro- and microvascular complications was lower, and life expectancy was greater (19.43 versus 19.35 life-years [LYs]) in patients receiving dapagliflozin than in those not receiving dapagliflozin. Patients in the dapagliflozin arm obtained an incremental benefit of 0.42 quality-adjusted life-years (QALYs). The lifetime incremental cost per patient in the dapagliflozin arm was €2,293, resulting in an incremental cost-effectiveness ratio of €27,779 per LY gained and an incremental cost-utility ratio of €5,502 per QALY gained. Sensitivity and scenario analyses showed that the results were insensitive to variations in modelling assumptions and input variables. CONCLUSION: Dapagliflozin in combination with insulin was estimated to be a cost-effective treatment option for patients with T2DM whose insulin treatment regimen does not provide adequate glycaemic control in a Dutch healthcare setting.

Optimizing Drug Development Programs: Type 2 Diabetes Case Study.

Recently, consideration was given to the impact of dose selection strategies in phase IIb on the overall success of drug development programs. A natural next step is to simultaneously optimize design aspects of both phase IIB and phase III. We used type 2 diabetes as an example, including realistic regulatory and commercial scenarios for this indication. The expected net present value (eNPV) has been selected as the primary outcome because it naturally accommodates optimization, providing an explicit trade-off between the probability of success (PoS) and time delays and trial costs. Our findings are that larger studies and/or implementation of an adaptive design over a fixed design in phase IIb provide more precise dose selection and reduce the bias of treatment effects and uncertainty in the estimated eNPV within the range of sample sizes that we examined. Developers also have to ensure that dose selection criteria are consistent with development strategy and objectives.

Cost-effectiveness of saxagliptin (Onglyza®) in type 2 diabetes in Sweden.

AIM: The objective of this study was to investigate the cost-effectiveness of saxagliptin (Onglyza(®)), a DPP-4 inhibitor, plus metformin compared with a sulphonylurea (SU) (Glipizide) plus metformin in Swedish patients not well controlled on metformin alone. METHODS: Data from a 52-week clinical trial comparing saxagliptin and glipizide in combination with metformin was used in a simulation model to estimate long term complications in a cohort of type 2 diabetes patients. The model estimates the incidence of microvascular and macrovascular complications, diabetes-specific mortality, all-cause mortality, and ultimately, costs and quality-adjusted life years (QALYs) associated with the investigated treatment strategies. Costs and QALYs were estimated for a lifetime time horizon. RESULTS: Compared with SU+metformin, the cost per QALY gained with saxagliptin+metformin is approximately SEK 91,000. Patients on saxagliptin+metformin gain 0.10 QALYs on average, at an incremental cost of around SEK 9500. The cost-effectiveness results were robust to various sensitivity analyses. CONCLUSIONS: This study demonstrates that, over a patient's lifetime, the addition of saxagliptin to metformin is associated with improvements in quality-adjusted life years compared with SU in patients with type 2 diabetes. Saxagliptin treatment is a cost-effective treatment alternative for type 2 diabetes in patients not well-controlled on metformin alone.