OBJECTIVES: Long-term safety trials for new antidiabetic therapies are beginning to provide an alternative data source to inform the burden of patients with high cardiovascular (CV) risk who are of concern to payers, but are often excluded from efficacy trials. An economic model was used to anticipate the availability of CV safety outcome data from ongoing trials and assess the clinical, economic and quality of life impacts in patients with different high risk profiles.  METHODS: A discrete event simulation model was developed to capture 6 types of macrovascular events and 2 key treatment events among patients with diabetes at high CV risk due to coronary heart disease (CHD), stroke and/or peripheral artery disease (PAD). Risk of clinical events depended on demographics and event history per UKPDS equations. Costs and utility values were based on published literature. Model outputs included event rates, CV-related costs and quality-adjusted life-years (QALYs). RESULTS: Over a lifetime, in an example population with mean age of 60 years, mean HbA1C of 8.5%, 70% CHD history, 30% stroke history and 30% PAD history, the CV event rate was 25.1/100-patient-years and annual per-patient cost was $12,776. This translated into 10.5 QALYs overall, ranging from 9.3 (patients with stroke history) to 11.2 (patients with CHD only) QALYs. A new intervention that reduces all CV event risks by 20%, results in 12.2 QALYs and annual cost of $10,611 for the overall population. These burdens vary by up to 14% for plausible values of event risk after multiple events, with the burden among patients with stroke history being most sensitive. CONCLUSIONS: The clinical burden of CV events and the associated cost of care for patients with diabetes vary with baseline patient history and are subject to significant uncertainty. CV safety trials may provide clinical data to better quantify those burdens.