Race as a Component of Cardiovascular Disease Risk Prediction Algorithms

Clinicians' perspectives on race-specific guidelines for hypertensive treatment

Despite the general consensus that there is no biological basis to race, racial categorization is still used by clinicians to guide diagnosis and treatment plans for certain diseases. In medicine, race is commonly used as a rough proxy for unmeasured social, environmental, and genetic factors. The American College of Cardiology's Eighth Joint National Committee's (JNC 8) guidelines for the treatment of hypertension provide race-specific medication recommendations for Black versus non-Black patients, without strong evidence for race-specific physiological differences in drug response. Clinicians practicing family or geriatric medicine (n = 21) were shown a video of a mock hypertensive patient with genetic ancestry test results that could be viewed as discordant with their phenotype and self-identified race. After viewing the videos, we conducted in-depth interviews to examine how clinicians value and prioritize different cues about race -- namely genetic ancestry data, phenotypic appearance, and self-identified racial classifications - when making treatment decisions in the context of race-specific guidelines, particularly in situations when patients claim mixed-race or complex racial identities. Results indicate that clinicians inconsistently follow the race-specific guidelines for patients whose genetic ancestry test results do not match neatly with their self-identified race or phenotypic features. However, many clinicians also emphasized the importance of clinical experience, side effects, and other factors in their decision making. Clinicians' definitions of race, categorization of the patient's race, and prioritization of racial cues greatly varied. The existence of the race-specific guidelines clearly influences treatment decisions, even as clinicians' express uncertainty about how to incorporate consideration of a patient's genetic ancestry. In light of widespread debate about removal of race from medical diagnostics, researchers should revisit the clinical justification for maintaining these race-specific guidelines. Based on our findings and prior studies indicating a lack of convincing evidence for biological differences by race in medication response, we suggest removing race from the JNC 8 guidelines to avoid risk of perpetuating or exacerbating health disparities in hypertension.

A cross-sectional study exploring the relationship between oxidative balance score and 10-year atherosclerotic cardiovascular disease risk based on the National Health and Nutrition Examination Survey (2011-2020)

BACKGROUND

The intricate interaction between oxidative stress and atherosclerotic cardiovascular disease (ASCVD) is an essential area of research because of the potential role of oxidative homeostasis in regulating ASCVD risk. This study aimed to investigate the relationship between the oxidative balance score (OBS) and the 10-years risk of ASCVD to gain insight into how oxidative balance affects cardiovascular health.

METHODS

This cross-sectional study analyzed National Health and Nutrition Examination Survey (NHANES) 2011-2020 data (40-79 age group), exploring OBS's link to 10-years ASCVD risk. OBS categorized dietary and lifestyle factors. Multivariate logistic regression controlled for age, sex, race, and demographics. A restricted cubic spline examined linear relationships; robustness was ensured through subgroup analyses.

RESULTS

Analysis of 4955 participants reveals a negative association between OBS and 10-years ASCVD risk. Continuous OBS adjusted OR: 0.97 (95% CI: 0.95∼0.99, p < .001). Quartile analysis shows reduced risk in Q2 0.88 (95% CI: 0.63∼1.22, p = .43), Q3 0.92 (95% CI: 0.66∼1.28, p = .614), and Q4 0.59 (95% CI: 0.42∼0.83, p = .002) compare Q1. Quartile analysis indicated decreasing risk in higher OBS quartiles. Lifestyle OBS and Dietary OBS demonstrated similar trends. Stratified analyses highlight race and hypertension as effect modifiers (p < .05).

CONCLUSION

Our study suggests an association between higher OBS and a reduced 10-years ASCVD risk. However, causation should not be inferred, and in the future, more extensive clinical and fundamental research is required to delve deeper into this association.

Novel Prediction Equations for Absolute Risk Assessment of Total Cardiovascular Disease Incorporating Cardiovascular-Kidney-Metabolic Health: A Scientific Statement From the American Heart Association

Cardiovascular-kidney-metabolic (CKM) syndrome is a novel construct recently defined by the American Heart Association in response to the high prevalence of metabolic and kidney disease. Epidemiological data demonstrate higher absolute risk of both atherosclerotic cardiovascular disease (CVD) and heart failure as an individual progresses from CKM stage 0 to stage 3, but optimal strategies for risk assessment need to be refined. Absolute risk assessment with the goal to match type and intensity of interventions with predicted risk and expected treatment benefit remains the cornerstone of primary prevention. Given the growing number of therapies in our armamentarium that simultaneously address all 3 CKM axes, novel risk prediction equations are needed that incorporate predictors and outcomes relevant to the CKM context. This should also include social determinants of health, which are key upstream drivers of CVD, to more equitably estimate and address risk. This scientific statement summarizes the background, rationale, and clinical implications for the newly developed sex-specific, race-free risk equations: PREVENT (AHA Predicting Risk of CVD Events). The PREVENT equations enable 10- and 30-year risk estimates for total CVD (composite of atherosclerotic CVD and heart failure), include estimated glomerular filtration rate as a predictor, and adjust for competing risk of non-CVD death among adults 30 to 79 years of age. Additional models accommodate enhanced predictive utility with the addition of CKM factors when clinically indicated for measurement (urine albumin-to-creatinine ratio and hemoglobin A1c) or social determinants of health (social deprivation index) when available. Approaches to implement risk-based prevention using PREVENT across various settings are discussed.