Presentation (CTI)

OBJECTIVES: Estimation of cardiovascular (CV) event risk is crucial for assessing the cost-effectiveness of interventions aimed at CV risk reduction. Cost-effectiveness models submitted to health technology assessment (HTA) bodies often estimate CV event risks based on an equation from Cholesterol Treatment Trialists’ (CTT) meta-analysis that links lowering of low-density lipoprotein-cholesterol (LDL-C) to CV event risk. However, clinicians rely on risk calculators such as Second manifestations of arterial disease (SMART), Framingham, and QRISK which incorporate multiple baseline characteristics. This research compares the risk estimations from the SMART risk calculator versus risks generated by linking LDL-C reduction with the event risk for similar patient groups (CTT meta-analysis-based approach).
METHODS: CV risk was estimated for atherosclerotic cardiovascular disease (ASCVD) patients on standard of care (maximally tolerated dose of statins) in a UK population. Demographic characteristics and clinical characteristics such as age, sex, baseline LDL-C, systolic blood pressure etc. were obtained from Clinical Practice Research Datalink (CPRD) and supplemented by supplementing literature. 10-year risk of CV events were then estimated using the published ‘Model A’ estimates of the SMART risk calculator. For the CTT meta-analysis-based approach, risk estimation over ten years was conducted using a cost-effectiveness model used for the UK HTA submission for ASCVD.
RESULTS: The risks were calculated for a cohort with mean age of 68 years (55% male, 16% diabetic). The 10-year risk for recurrent vascular events based on the SMART risk calculator was estimated to be 10.67%. Using the CTT meta-analysis-based approach in the cost-effectiveness model, the 10-year risk was estimated to be 6.76%.
CONCLUSIONS: Risk estimations using the approach used in the HTA submissions were found to be lower than the ones using the SMART risk calculator. The CV event predictions based on equation from CTT therefore yields conservative cost-effectiveness estimates compared with using SMART calculator-based approach.