OBJECTIVES:  There are a number of published cardiovascular (CV) risk equations (RE) suitable for use in type 2 diabetes mellitus (T2DM) cost effectiveness (CE) models. Their inclusion is complicated due to the inconsistency of CV endpoints for which risk is estimated. The QuintilesIMS CORE Diabetes Model (CDM) applies a United Kingdom Prospective Diabetes Study (UKPDS) weighting algorithm to five CV risk equations to enable consistency in modelled CV events. The objective of this study was to describe the impact of the weighting algorithm on predicted total and incremental CV risk for a number of CV RE. METHODS:  This study used the T2DM CV risk equations available in the CDM to estimate five-year risk of myocardial infarction (MI), stroke, ischemic heart disease (IHD) and congestive heart failure (CHF). The following risk equations were included: Swedish-National Diabetes Registry (S-NDR); ADVANCE (Global); FREMANTLE (Australian); ARIC (US) and PROCAM (Germany). A dynamic risk factor related weighting algorithm based on the five-year risk of MI, stroke, IHD and CHF derived from the UKPDS 68 RE was applied to standardize endpoints. Results were illustrated using a UKPDS baseline cohort profile. RESULTS:  Predicted five-year cumulative CV risk using UKPDS 68 RE was 0.075 (52.3% of this risk was attributable to MI; 5.8% to stroke; 39.1% to IHD and 2.8% to CHF). Five-year CV risk for S-NDR was 0.038; ADVANCE 0.028; FREMANTLE 0.071; ARIC 0.212 and PROCAM 0.08. A 1% increase in HbA1c was associated with an increase in cumulative CV risk of 12.8% (UKPDS 68); 11.6% (S-NDR); 10.8% (ADVANCE); 12.3% (FREMANTLE); 0.5% (ARIC) and 0.5% (PROCAM). CONCLUSIONS:  Approaches to standardizing endpoints predicted across CV RE facilitates their inclusion within T2DM economic models. This is particularly relevant given the appetite amongst health technology assessment groups to evaluate the sensitivity of predicted CE output to choice of RE.