Development and validation of a cost-utility model for Type 1 diabetes mellitus

A Systematic Review of Methodologies Used in Models of the Treatment of Diabetes Mellitus

BACKGROUND

Diabetes mellitus is a chronic and complex disease, increasing in prevalence and consequent health expenditure. Cost-effectiveness models with long time horizons are commonly used to perform economic evaluations of diabetes' treatments. As such, prediction accuracy and structural uncertainty are important features in cost-effectiveness models of chronic conditions.

OBJECTIVES

The aim of this systematic review is to identify and review published cost-effectiveness models of diabetes treatments developed between 2011 and 2022 regarding their methodological characteristics. Further, it also appraises the quality of the methods used, and discusses opportunities for further methodological research.

METHODS

A systematic literature review was conducted in MEDLINE and Embase to identify peer-reviewed papers reporting cost-effectiveness models of diabetes treatments, with time horizons of more than 5 years, published in English between 1 January 2011 and 31 of December 2022. Screening, full-text inclusion, data extraction, quality assessment and data synthesis using narrative synthesis were performed. The Philips checklist was used for quality assessment of the included studies. The study was registered in PROSPERO (CRD42021248999).

RESULTS

The literature search identified 30 studies presenting 29 unique cost-effectiveness models of type 1 and/or type 2 diabetes treatments. The review identified 26 type 2 diabetes mellitus (T2DM) models, 3 type 1 DM (T1DM) models and one model for both types of diabetes. Fifteen models were patient-level models, whereas 14 were at cohort level. Parameter uncertainty was assessed thoroughly in most of the models, whereas structural uncertainty was seldom addressed. All the models where validation was conducted performed well. The methodological quality of the models with respect to structure was high, whereas with respect to data modelling it was moderate.

CONCLUSIONS

Models developed in the past 12 years for health economic evaluations of diabetes treatments are of high-quality and make use of advanced methods. However, further developments are needed to improve the statistical modelling component of cost-effectiveness models and to provide better assessment of structural uncertainty.

A Patient-Level Model to Estimate Lifetime Health Outcomes of Patients With Type 1 Diabetes

OBJECTIVE

To develop a patient-level simulation model for predicting lifetime health outcomes of patients with type 1 diabetes and as a tool for economic evaluation of type 1 diabetes treatment based on data from a large, longitudinal cohort.

RESEARCH DESIGN AND METHODS

Data for model development were obtained from the Swedish National Diabetes Register. We derived parametric proportional hazards models predicting the absolute risk of diabetes complications and death based on a wide range of clinical variables and history of complications. We used linear regression models to predict risk factor progression. Internal validation was performed, estimates of life expectancies for different age-sex strata were computed, and the impact of key risk factors on life expectancy was assessed.

RESULTS

The study population consisted of 27,841 patients with type 1 diabetes with a mean duration of follow-up of 7 years. Internal validation showed good agreement between the predicted and observed cumulative incidence of death and 10 complications. Simulated life expectancy was ∼13 years lower than that of the sex- and age-matched general population, and patients with type 1 diabetes could expect to live with one or more complications for ∼40% of their remaining life. Sensitivity analysis showed the importance of preventing renal dysfunction, hypoglycemia, and hyperglycemia as well as lowering HbA_1c in reducing the risk of complications and death.

CONCLUSIONS

Our model was able to simulate risk factor progression and event histories that closely match the observed outcomes and to project events occurring over patients' lifetimes. The model can serve as a tool to estimate the impact of changing clinical risk factors on health outcomes to inform economic evaluations of interventions in type 1 diabetes.

Cost-effectiveness of Initiating an Insulin Pump in T1D Adults Using Continuous Glucose Monitoring Compared with Multiple Daily Insulin Injections: The DIAMOND Randomized Trial

BACKGROUND

The economic impact of both continuous glucose monitoring (CGM) and insulin pumps (continuous subcutaneous insulin infusion [CSII]) in type 1 diabetes (T1D) have been evaluated separately. However, the cost-effectiveness of adding CSII to existing CGM users has not yet been assessed.

OBJECTIVE

The aim of this study was to evaluate the societal cost-effectiveness of CSII versus continuing multiple daily injections (MDI) in adults with T1D already using CGM.

METHODS

In the second phase of the DIAMOND trial, 75 adults using CGM were randomized to either CGM+CSII or CGM+MDI (control) and surveyed at baseline and 28 weeks. We performed within-trial and lifetime cost-effectiveness analyses (CEAs) and estimated lifetime costs and quality-adjusted life-years (QALYs) via a modified Sheffield T1D model.

RESULTS

Within the trial, the CGM+CSII group had a significant reduction in quality of life from baseline (-0.02 ± 0.05 difference in difference [DiD]) compared with controls. Total per-person 28-week costs were $8,272 (CGM+CSII) versus $5,623 (CGM+MDI); the difference in costs was primarily attributable to pump use ($2,644). Pump users reduced insulin intake (-12.8 units DiD) but increased the use of daily number of test strips (+1.2 DiD). Pump users also increased time with glucose in range of 70 to 180 mg/dL but had a higher HbA1c (+0.13 DiD) and more nonsevere hypoglycemic events. In the lifetime CEA, CGM+CSII would increase total costs by $112,045 DiD, decrease QALYs by 0.71, and decrease life expectancy by 0.48 years.

CONCLUSIONS

Based on this single trial, initiating an insulin pump in adults with T1D already using CGM was associated with higher costs and reduced quality of life. Additional evidence regarding the clinical effects of adopting combinations of new technologies from trials and real-world populations is needed to confirm these findings.

Projected long-term outcomes in patients with type 1 diabetes treated with fast-acting insulin aspart vs conventional insulin aspart in the UK setting

AIM

To assess the impact of faster aspart vs insulin aspart on long-term clinical outcomes and costs for patients with type 1 diabetes mellitus (T1DM) in the UK setting.

METHODS

The QuintilesIMS CORE Diabetes Model was used to project clinical outcomes and costs over patient lifetimes in a cohort with data on baseline characteristics from the "onset 1" trial. Treatment effects were taken from the 26-week main phase of the onset 1 trial, with costs and utilities based on literature review. Future costs and clinical benefits were discounted at 3.5% annually.

RESULTS

Projections indicated that faster aspart was associated with improved discounted quality-adjusted life expectancy (by 0.13 quality-adjusted life-years) vs insulin aspart. Improved clinical outcomes resulted from fewer diabetes-related complications and a delayed time to their onset with faster aspart. Faster aspart was found to be associated with reduced costs vs insulin aspart (cost savings of £1715), resulting from diabetes-related complications avoided and reduced treatment costs.

CONCLUSIONS

Faster aspart was associated with improved clinical outcomes and cost savings vs insulin aspart for patients with T1DM in the UK setting.

Cost-effectiveness of switching to insulin degludec from other basal insulins: evidence from Swedish real-world data

OBJECTIVES

Health economic analysis from a healthcare and societal point of view was conducted to assess the cost-effectiveness of insulin degludec (IDeg) after switching from other basal insulins in people with type 1 diabetes.

MATERIAL AND METHODS

This was a prospective, open-label, single arm, observational follow-up from August 2013 to October 2015 of 476 consecutive patients at Danderyd Hospital (Stockholm, Sweden) who switched to IDeg from other basal insulins (99% basal insulin analogs). The IMS CORE Diabetes Model (CDM) was used to predict the cost-effectiveness of life-long treatment with IDeg vs. other basal insulins, based on a Swedish setting.

RESULTS

Mean (SD) duration of follow-up was 21.7 (6.0) weeks. Mean HbA_1c decreased by 2.7 mmol/mol, mean basal insulin dose decreased by 13.1% (p < .0001), and mean bolus insulin dose decreased by 7.5% (p < .0001) after switching. Frequencies of non-severe daytime hypoglycemia and non-severe nocturnal hypoglycemia decreased by 12% (p = .0127) and 53% (p < .0001) respectively and severe hypoglycemia was reduced by 62% (p = .0225). The CDM predicted a gain in life expectancy of 0.33 years, a discounted gain in quality-adjusted life-years (QALYs) of 0.54, and lower estimated direct lifetime healthcare costs of SEK 22,757 for patients switching to IDeg. The incremental cost-effectiveness ratio (ICER) showed IDeg as dominant (i.e. higher effectiveness with a lower cost). Sensitivity analyses confirmed the results.

CONCLUSION

Based on this prospective, real-world, follow-up and using the CDM, it was estimated that switching to IDeg from other basal insulins translated into QALY gains including improved life expectancy and health-related quality of life, as well as dominant ICER, meaning cost-savings for the healthcare system. However, the study is limited by its observational design. Extrapolation into the future is only estimated since the actual treatment effect cannot be projected with certainty.

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.

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.