Cost-effectiveness of the non-laboratory based Framingham algorithm in primary prevention of cardiovascular disease: A simulated analysis of a cohort of African American adults.

The non-lab Framingham algorithm, which substitute body mass index for lipids in the laboratory based (lab-based) Framingham algorithm, has been validated among African Americans (AAs). However, its cost-effectiveness and economic tradeoffs have not been evaluated. This study examines the incremental cost-effectiveness ratio (ICER) of two cardiovascular disease (CVD) prevention programs guided by the non-lab versus lab-based Framingham algorithm. We simulated the World Health Organization CVD prevention guidelines on a cohort of 2690 AA participants in the Atherosclerosis Risk in Communities (ARIC) cohort. Costs were estimated using Medicare fee schedules (diagnostic tests, drugs & visits), Bureau of Labor Statistics (RN wages), and estimates for managing incident CVD events. Outcomes were assumed to be true positive cases detected at a data driven treatment threshold. Both algorithms had the best balance of sensitivity/specificity at the moderate risk threshold (>10% risk). Over 12years, 82% and 77% of 401 incident CVD events were accurately predicted via the non-lab and lab-based Framingham algorithms, respectively. There were 20 fewer false negative cases in the non-lab approach translating into over $900,000 in savings over 12years. The ICER was -$57,153 for every extra CVD event prevented when using the non-lab algorithm. The approach guided by the non-lab Framingham strategy dominated the lab-based approach with respect to both costs and predictive ability. Consequently, the non-lab Framingham algorithm could potentially provide a highly effective screening tool at lower cost to address the high burden of CVD especially among AA and in resource-constrained settings where lab tests are unavailable.

Vascular risk assessment in older adults without a history of cardiovascular disease.

Modern cardiovascular risk prediction tools, which have their genesis in the Framingham Heart Study, have allowed more accurate risk stratification and targeting of treatments worldwide over the last seven decades. Better cardiovascular risk factor control during this time has led to a reduction in cardiovascular mortality and, at least in part, to improved life expectancy. As a result, western societies as a whole have seen a steady increase in the proportion of older persons in their populations. Unfortunately, several studies have shown that the same tools which have contributed to this increase cannot be reliably extrapolated for use in older generations. Recent work has allowed recalibration of existing models for use in older populations but these modified tools still require external validation before they can be confidently applied in clinical practice. Another complication is emerging evidence that aggressive risk factor modification in older adults, particularly more frail individuals, may actually be harmful. This review looks at currently available cardiovascular risk prediction models and the specific challenges faced with their use in older adults, followed by analysis of recent attempts at recalibration for this cohort. We discuss the issue of frailty, looking at our evolving understanding of its constituent features and various tools for its assessment. We also review work to date on the impact of frailty on cardiovascular risk modification and outline its potentially central role in determining the most sensible approach in older patients. We summarise the most promising novel markers of cardiovascular risk which may be of use in improving risk prediction in older adults in the future. These include markers of vascular compliance (such as aortic pulse wave velocity and pulse wave analysis), of endothelial function (such as flow mediated dilation, carotid intima-media thickness and coronary artery calcium scores), and also biochemical and circulating cellular markers.