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

Prev Med. 2018 Jun:111:415-422. doi: 10.1016/j.ypmed.2017.12.001. Epub 2017 Dec 7.

Abstract

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.

Keywords: Absolute cardiovascular risk assessment; Cardiovascular disease; Cardiovascular risk prediction; Cost-effectiveness; Non-laboratory based risk assessment algorithms; Primary prevention.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms*
  • Black or African American / statistics & numerical data*
  • Body Mass Index
  • Cardiovascular Diseases / diagnosis
  • Cardiovascular Diseases / prevention & control*
  • Cohort Studies*
  • Cost-Benefit Analysis / statistics & numerical data*
  • Female
  • Humans
  • Longitudinal Studies
  • Male
  • Mass Screening
  • Middle Aged
  • Primary Prevention / statistics & numerical data*
  • Risk Assessment / methods