Guidelines recommend calculation of global cardiovascular (CVD) risk in order to target effective prevention interventions such as aspirin and statins to those most likely to benefit and to limit adverse effects and costs by not treating those at low risk. Improving our ability to predict who will suffer future CVD events through use of novel biomarkers should help us improve targeting of preventive interventions and thereby improve health outcomes. Many such markers have been identified over recent years, and some have been studied extensively;however, a widely-acknowledged """"""""critical gap"""""""" in knowledge exists that has hindered effective decision-making about whether such biomarkers should be adopted in clinical practice. It is our view that this critical gap is the result of a lack of evidence about the net health and economic impact of biomarker targeting strategies. To address this gap, we propose to develop a decision analysis/cost-effectiveness modeling framework for evaluating any biomarker that could be used to target use of aspirin and statins for primary prevention of CVD (Aim 1). For this task, we will use the UNC/RTI CHD Prevention Model, an established model focusing on the cost-effectiveness of aspirin and statin prescribing for prevention of CHD and stroke. The model will be updated via a series of systematic reviews to incorporate the latest data on effectiveness and adverse effects of aspirin and statins, and then restructured to allow """"""""Test-and-Treat"""""""" strategies based on biomarker measurements (requiring parallel modeling of 4 different """"""""sub-scenarios"""""""" to allow for 3 possible Test-and-Treat treatment thresholds), and to facilitate comparison of Test-and-Treat strategies with Treat All and Treat None (strategies not incurring the cost and any adverse effects associated with the test itself). This framework will then be used to evaluate coronary calcium (Aim 2). This extremely controversial biomarker is a strong independent predictor of CHD risk, but it is expensive to measure and exposes the patient to ionizing radiation. We will undertake a systematic evaluation of different coronary calcium treatment thresholds in a comprehensive set of clinical scenarios varied in terms of age, sex, LDL level and CVD risk, and compared in terms of cost and health impact, and incremental cost-effectiveness. Finally, we will build an online interface allowing users to screen ANY biomarker for use in targeting aspirin and statin therapy (in a relatively ideal scenario) by inputting information commonly available in biomarker publications, and allowing users to vary key parameters such as the cost of statins (Aim 3). Our project would close the critical gap in knowledge on CVD biomarker use, produce key evidence for coronary calcium that could be used immediately to drive rational policy-making, an online tool allowing researchers and policymakers to screen other biomarkers for use in this setting, and a roadmap for evaluating use of biomarker targeted prevention in other settings.
Heart scans for coronary calcium and other newly discovered tests (biomarkers) can help identify persons at risk for heart attacks and stroke who should be treated with medications to lower their risk. By estimating how many heart attacks, strokes and deaths could be prevented by using these tests routinely in the U.S. and how much money this would cost, our study will help policymakers decide when doctors should order a heart scan or other biomarker test.
