Cardiovascular Risk Assessment: Are We Using the Right Tools?

Abstract

It is in this regard that accurate cardiovascular risk assessment would play a significant role in guiding preventive strategies and optimizing patient outcomes. However, traditional risk factors remain the basis of current risk assessment tools, with their limitations in terms of predictive accuracy, particularly for certain populations. This article examines the limitations of established risk scores, introduces new approaches including genetic risk scores and biomarkers, and stresses the critical need to incorporate social determinants of health in the assessment process. Moving beyond the traditional models into a more inclusive approach, can improve risk stratification and provide a personalized preventive intervention for better cardiovascular health.   

Introduction

Accurate estimation of an individual's risk for developing atherosclerotic cardiovascular disease, which includes coronary heart disease, stroke, and peripheral artery disease among others, is the underlying foundation for preventive cardiology. Risk estimation focuses on decisions about lifestyle interventions, pharmacotherapy, and other treatments aimed at preventing such future cardiovascular events. Traditionally, the mainstay in practice for years has been through tools and scoring from large population studies: for instance, the Framingham Risk Score and Pooled Cohort Equations. It relies more heavily on age, sex, blood pressure, cholesterol level, smoking, and diabetes to compute its scoring. Such traditional scores are quite instrumental for raising individuals who may have risk elevation. These include limitations related to suboptimal predictive accuracy in some populations, the failure to fully capture the complex interplay of risk factors, and an inability to adequately account for emerging risk factors and social determinants of health. This article will discuss the limitations of existing risk assessment tools, explore new promising approaches, such as genetic risk scores and biomarkers, and highlight the role of social determinants of health in refining cardiovascular risk prediction.  

Literature Review

There is a rich literature on cardiovascular risk assessment. There are several studies assessing the performance of existing risk scores and new approaches. Among the earliest and most influential tools for risk assessment was the Framingham Risk Score, developed from the Framingham Heart Study. It provided a framework for estimating the 10-year risk of coronary heart disease based on traditional risk factors. Later, additional risk scores, including the Reynolds Risk Score and the Pooled Cohort Equations (PCE), were developed to enhance the accuracy of risk prediction, especially in women and diverse populations. Yet, research studies have repeatedly shown that these traditional risk scores lack sufficient predictive ability and tend to underestimate risk in some individuals while overestimating it in others.   Research has focused on identifying novel risk factors and developing more sophisticated risk assessment methods.

Genetic risk scores, derived from genome-wide association studies, have become a promising tool for capturing inherited susceptibility to cardiovascular disease. There is evidence that GRS can improve the prediction of risks beyond traditional risk factors, particularly in younger patients and those with a family history of premature ASCVD. Biomarkers, which include high-sensitivity C-reactive protein, lipoprotein(a) [Lp(a)], and even the coronary artery calcium (CAC) score, have been studied as supplementary tools to help in traditional risk assessment. More recent studies reveal that these biomarkers add another layer of insight into cardiovascular risk and improve its stratification. SDOH includes numerous social, economic, and environmental factors influencing a person's risk for a better health outcome or poorer health, for instance, the SES, educational levels, health insurance, access to healthcare services, food insecurity, and living space. For many years, this group has realized that social and economic disadvantages tend to affect poor people in disproportionately large ways by greatly increasing the possibility of acquiring heart diseases even with control measures implemented for classic factors.  

Limitations of Current Risk Assessment Tools

Current risk assessment tools, primarily based on traditional risk factors, have several limitations:

• Limited predictive accuracy: These tools often underestimate risk in some individuals, particularly women, younger individuals, and certain racial and ethnic groups, and overestimate it in others.

• Inability to capture the complex interplay of risk factors: These tools typically consider risk factors independently, failing to account for their complex interactions.

• Failure to adequately account for emerging risk factors: These tools do not fully incorporate emerging risk factors such as chronic inflammation, genetic predisposition, and environmental exposures.

• Lack of consideration of social determinants of health: These tools largely ignore the significant impact of social, economic, and environmental factors on cardiovascular risk.

Emerging Approaches to Cardiovascular Risk Assessment

Several emerging approaches aim to improve cardiovascular risk prediction:

• Genetic Risk Scores (GRS): GRS aggregates the effects of multiple genetic variants associated with cardiovascular disease. They can provide a more comprehensive assessment of inherited susceptibility and improve risk prediction, particularly in younger individuals and those with a family history of premature ASCVD.

• Biomarkers: Biomarkers such as hs-CRP, Lp(a), and CAC score can provide additional information about cardiovascular risk beyond traditional risk factors. Hs-CRP measures systemic inflammation, Lp(a) is a genetically determined lipoprotein associated with increased risk of thrombosis, and CAC score quantifies the amount of calcium in the coronary arteries, a marker of atherosclerotic plaque burden.  

• Integrating SDOH into Risk Assessment: Incorporating SDOH into risk assessment is crucial for capturing the full spectrum of factors that influence cardiovascular risk. This can involve collecting data on socioeconomic status, education, access to healthcare, and other relevant social factors.  

The Importance of Social Determinants of Health

Social determinants of health have a critical impact on cardiovascular risk. They impact health behaviors, access to health care, and exposure to environmental stressors that determine cardiovascular health. The approach is necessary to meet the requirements for health equity in reducing disparities related to cardiovascular outcomes.

Moving Beyond Traditional Risk Assessment

Moving beyond traditional risk assessment requires a more comprehensive and personalized approach. This involves:

• Integrating traditional risk factors with emerging risk factors: Combining traditional risk factors with GRS, biomarkers, and SDOH can improve risk prediction.

• Utilizing advanced statistical modeling: Employing more sophisticated statistical methods, such as machine learning algorithms, can help to capture the complex interplay of risk factors. 

• Personalizing preventive interventions: Tailoring preventive strategies based on individual risk profiles can improve effectiveness and patient outcomes.  

Clinical Implications and Future Directions

The evolving landscape of cardiovascular risk assessment has important implications for clinical practice. Clinicians should be aware of the limitations of current risk scores and consider incorporating emerging approaches, such as GRS and biomarkers, into their assessment process. Furthermore, it is crucial to address SDOH and implement strategies to reduce disparities in cardiovascular outcomes.  

Future research should focus on:

• Developing and validating new risk assessment tools that incorporate emerging risk factors and SDOH.

• Evaluating the clinical utility of GRS and biomarkers in different patient populations.

• Developing and implementing interventions to address SDOH and improve cardiovascular health equity.

Conclusion

Accurate cardiovascular risk assessment is important for the effective prevention and management of ASCVD. Traditional risk scores have been useful, but they are far from perfect. New strategies, such as GRS and biomarkers, and the integration of SDOH into risk assessment, may be able to significantly enhance the ability to predict risk and tailor interventions in prevention. By moving beyond traditional models toward more holistic and sophisticated approaches, we can better identify populations at risk, implement targeted strategies, and ultimately improve cardiovascular health outcomes for all.