Over the past few decades, atherosclerotic CVD has become the leading cause of death worldwide. The rapid increase in the incidence and prevalence of CVD has led to a growing recognition of the need to develop and implement effective strategies for its prevention. While increasing the overall awareness about the menace of CVD, the reasons for its occurrence and the role of healthy life-style in its prevention appears to be the most effective strategy for CVD prevention, it is greatly limited by the widespread negligence and general apathy of the common public toward healthy life-style measures. A potentially more effective strategy is to identify “high-risk” individuals and then focus all efforts and resources to prevent the development of disease in them.

At present, CV risk assessment is generally performed using conventional CV risk factors and risk algorithms such as Framingham risk score. However, numerous studies have shown that although these risk algorithms perform reasonably well at the population level, their accuracy at the individual level is rather dismal (19–22). Consequently, often there are individuals with multiple CV risk factors and high estimated CV risk who do not develop clinical CVD even in the long term, whereas there are many other patients who present with acute CV event despite being free of all known major CV risk factors. To overcome this limitation, several diagnostic tools have been developed that have the ability to detect atherosclerotic vascular disease in its early, pre-clinical stage and therefore can provide direct evidence of ongoing atherosclerotic process, irrespective of the presence or absence of known CV risk factors. Numerous large-scale studies have unequivocally demonstrated the incremental value of such techniques over conventional CV risk factors in prediction of future CV risk (4,17,23). Although it is yet to be proven that incorporation of these diagnostic techniques into the standard risk assessment approach can improve clinical outcomes, the evidence so far suggests that such a strategy can be helpful in guiding nature, timing and aggressiveness of anti-atherosclerotic therapy, in improving patient compliance toward these measures and may also help in monitoring response to therapy (1,2,4–10).

CIMT, brachial artery flow-mediated dilatation, PWV assessment, ankle-brachial index and CCS are the most commonly used measures of preclinical atherosclerosis. All these tools aim to detect evidence of atherosclerosis in different vascular beds with the underlying rationale that atherosclerosis is a generalized disease and its presence in one vascular bed indirectly implies involvement, though not necessarily concurrently, of other vascular beds too. However, these techniques are methodologically vastly different from each other and therefore have significant differences in their availability, cost, ease of use, repeatability, radiation exposure, etc. As many of these techniques are already available for clinical use, it is important to determine their relative diagnostic accuracy to allow for their judicious, cost-effective and the most meaningful use in routine clinical practice.

Previous studies have shown CCS to have much greater predictive accuracy for future CV events and to have the greatest incremental value over conventional risk assessment algorithms (11,12). However, no study has compared CCS with the other modalities of preclinical atherosclerosis assessment in Indians; thus our study is the first one to provide such data. Similar to the western populations, we too found CCS to have the greatest predictive accuracy for the presence of CAD.

Although CCS is more accurate in predicting CAD as compared to CIMT or PWV, it is expensive, not readily available and is associated with radiation exposure, which limit its use in routine clinical practice. To this extent, our study has provided an important insight. We found that a combination of CIMT and baPWV could provide excellent diagnostic accuracy and could be used as a simpler, less-expensive and radiation-free approach to initial CV risk stratification of the individuals. If both CIMT and left baPWV are normal, CAD can be excluded with high degree of certainty and no further testing may be needed. In contrast, if both are increased, there is a high likelihood of the presence of coronary atherosclerosis and the patient can be subjected to CCS or stress testing based on their clinical presentation. In the remaining individuals with only one of the parameters being abnormal, further evaluation will have to be individualized according to the presence or absenceof other CV risk factors. Thus a hierarchical approach could be utilized to minimize cost, reduce radiation risk and to make it more suitable for wider clinical use, but at the same time retaining its diagnostic accuracy.