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

Aims To develop a health economic model to evaluate the cost‐effectiveness of new interventions for Type 1 diabetes mellitus by their effects on long‐term complications (measured through mean HbA1c) while capturing the impact of treatment on hypoglycaemic events. Methods Through a systematic review, we identified complications associated with Type 1 diabetes mellitus and data describing the long‐term incidence of these complications. An individual patient simulation model was developed and included the following complications: cardiovascular disease, peripheral neuropathy, microalbuminuria, end‐stage renal disease, proliferative retinopathy, ketoacidosis, cataract, hypoglycemia and adverse birth outcomes. Risk equations were developed from published cumulative incidence data and hazard ratios for the effect of HbA1c, age and duration of diabetes. We validated the model by comparing model predictions with observed outcomes from studies used to build the model (internal validation) and from other published data (external validation). We performed illustrative analyses for typical patient cohorts and a hypothetical intervention. Results Model predictions were within 2% of expected values in the internal validation and within 8% of observed values in the external validation (percentages represent absolute differences in the cumulative incidence). Conclusions The model utilized high‐quality, recent data specific to people with Type 1 diabetes mellitus. In the model validation, results deviated less than 8% from expected values. What's new? A simple cost–utility model was developed to evaluate new interventions for Type 1 diabetes mellitus by assessing the association between the interventions' effects on mean HbA1c and long‐term complications and the risk of hypoglycaemic events. High‐quality, recently reported data specific to people with Type 1 diabetes mellitus were identified by a systematic review. Model validation included review by clinical and economic experts, verification of input data and formulae, and comparison of model predictions with observations from studies used to build the model and other published data.