Detecting subclinical atherosclerosis with coronary artery calcium (CAC) is promising for identifying individuals at risk for cardiovascular events and appears to be a robust tool for guiding initiation of appropriate and timely primary prevention strategies. However, how do we best determine its clinical value? It is clear that traditional risk prediction models based primarily on age, gender, and risk factors are insufficient for ideal personalization of risk estimation. It is now well established from epidemiologic studies that CAC adds to traditional risk scores for a more accurate risk prediction. However, such traditional epidemiology studies have limitations in establishing "clinical value," and they must be supplemented by additional data before being translated into strong recommendations in clinical practice guidelines. Fortunately, over the last few years, the research around CAC has matured to include data supporting enhanced clinician-patient risk discussions, shared decision-making, flexible risk factor treatment goals, specific clinical decision algorithms, as well as favorable cost-effectiveness analyses. We had moved from a time when we asked "if CAC adds to the risk score" to a time when we are asking "does CAC facilitate a shared decision-making model matching risk, treatment, and patient preferences?" A new risk calculator incorporating CAC into global risk scoring, and 2017 guidelines on the use of CAC published by the Society of Cardiovascular Computed Tomography (SCCT), reflect this new approach. In this article, we review the recent transition to this more clinically relevant CAC research that may support a stronger recommendation for its use in future prevention guidelines.
Keywords: Clinical decision-making; Coronary artery calcium; Cost-effectiveness; Risk prediction.