Is it Time to Redefine Criteria for Coronary Artery Calcification Significance for South-Asian Women?

Coronary artery calcification (CAC) is considered a marker of subclinical atherosclerotic disease and computed tomography (CT) CAC score has emerged as a valuable parameter for cardiovascular (CV) risk assessment in asymptomatic individuals beyond the traditional risk factors. It is a safe, non-invasive, affordable test that is widely available, making it a powerful screening tool in large asymptomatic populations. American heart association (2019) has endorsed its role to guide physicians to decide on statin therapy as primary prevention in intermediate risk groups (7.5–20% 10-year atherosclerotic CV disease [ASCVD] risk). In those with diabetes, age more than 55 years, family history of premature coronary heart disease or cigarette smoking, CAC can further support the recommendation for initiation of statin therapy and can guide the aggressiveness of statin therapy on long-term follow-up of diabetic and high-risk patients.^[1]

There are several studies and meta-analyses which showed positive correlation of degree of CAC and major adverse cardiac events.^[2,3] Like any other test, there have been limitations to use of CAC, these have been discussed in literature. The old generation CT CAC predicted a significant angiographic disease with sensitivity of 95% but low (44% specificity).^[4] However, with the use of electron beam tomography, it was endorsed for excellent negative predictive value. A score zero excludes significant CV disease (CVD).^[5] CAC can vary in its incidence and distribution by race and lifestyle. The guidelines from major international societies have nuanced recommendations based on its population characteristics and their CV risks.^[6]

Concerns have been raised about the variations in the usefulness of CAC in the South Asian population in whom data is still lacking. Age, sex, diabetes, and presence of other coronary risk factors and atypical symptoms in the population could make it difficult to define the same cut-offs as currently being used. An interesting small observational study by Chandran et al.,^[7] published in this issue is commendable for putting forth suggestions such as women especially below 50 years should be routinely advised to have CAC assessment, especially if they have diabetes or multiple risk factors. Incorporating specific data in younger patients under 50 with multiple risk factors would strengthen any such recommendations. Similarly, how diabetes may influence the CAC score especially in those with <100 could have been attempted.

The important lacuna of the study is a small number included, and women were under-represented (only 30%). It is obvious that standard statistical analyses cannot be meaningfully applied, and strong conclusions cannot be derived at. Key confounding variables such as lipid profile, statin therapy, and smoking were not commented in this study. A brief discussion on how CAC score compares with established CV risk tools such as Framingham risk score and Atherosclerotic cardiovascular disease (ASCVD) could have clarified the clinical relevance of this study. Although the authors suggested a lower threshold in patients with scores 1–100 to pursue invasive testing with coronary angiogram, this perspective needs a larger clinical trial in the South Asian population. This small, interesting study also questioned the current practice of not doing CAC test in women <50 years. It has been suggested in some studies that breast artery calcification (BAC) in women can be an alternate tool useful to predict coronary artery disease (CAD) or indicate risk for future CVD or CV mortality.^[8]

A few studies have proposed that BAC in women may serve as an alternative tool for predicting CAD or indicating the risk of future CVD or CV mortality.^[8] Beyond the predictability of presence of atherosclerotic CAD and chance for major CV adverse events, CAC has a role for guiding the therapy based on value of CAC (avoiding over-treatment as well as under-treatment).^[9] Looking forward, it is exciting to learn that CAC can be easily evaluated from chest CT using artificial intelligence.