PDB34 The PRIME Type 2 Diabetes MODEL: A New, Product-Independent MODEL to Evaluate LONG-TERM Clinical and Cost Outcomes in Type 2 Diabetes

Abstract

The growing burden of diabetes mellitus and recent progress in understanding cardiovascular outcomes in type 2 diabetes (T2D) patients continue to make the disease a priority for healthcare decision-makers around the world. Our objective was to develop a new, product-independent model capable of projecting long-term clinical and cost outcomes for populations with T2D to support health economic evaluation. Following a systematic literature review to identify longitudinal study data, existing T2D models and risk formulae for T2D populations, a model was developed (the PRIME Type 2 Diabetes Model [PRIME T2DM]) in line with good practice guidelines to simulate disease progression, diabetes-related complications and mortality. The model runs as a patient-level simulation and is capable of simulating treatment algorithms and risk factor progression, and projecting the cumulative incidence of macrovascular and microvascular complications as well as hypoglycemic events. The PRIME T2DM can report clinical outcomes, quality-adjusted life expectancy, direct and indirect costs, along with standard measures of cost-effectiveness and is capable of probabilistic sensitivity analysis. Several approaches novel to T2D modeling were utilized, such as combining risk formulae using a weighted model averaging approach that takes into account patient characteristics to evaluate complication risk. Validation analyses comparing modeled outcomes with published studies demonstrated that the PRIME T2DM projects long-term patient outcomes consistent with those reported for a number of long-term studies, including cardiovascular outcomes trials. Macrovascular endpoints were reliably reproduced across different populations and microvascular complication risk was accurately predicted based on comparisons with landmark studies and published registry data. The PRIME T2DM is a novel, product-independent analysis tool that offers new approaches to long-standing challenges in diabetes modeling and may become a useful tool for informing healthcare policy. Validation analysis has indicated that outcomes from long-term studies can be reliably reproduced.