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LONDON -- A combination of three factors -- high-sensitivity C-reactive protein (hsCRP), LDL cholesterol, and lipoprotein(a), or lp(a) -- independently predicted cardiovascular disease over 30 years in women who were initially healthy, according to an analysis of the Women's Health Study.

Each of the three factors predicted the 30-year risk for both coronary heart disease and stroke, and each contributed to overall risk prediction, but the greatest spread for risk was in models that incorporated all three biomarkers together.

Elevation in 30-year risk from being in the top versus bottom quintile was 70% for hsCRP, 36% for LDL cholesterol, and 33% for lp(a) after adjustment for covariates. While the point estimates attenuated with mutual adjustment, all remained statistically significant (HR 1.14, 1.08, and 1.06, respectively).

"Each biomarker provided additive information to the other two biomarkers, such that the combination of all three provided the greatest magnitude of spread for long-term risk stratification," Paul Ridker, of Brigham and Women's Hospital in Boston, reported at the European Society of Cardiology meeting in London and in the (NEJM).

"These data support efforts to extend strategies for the primary prevention of atherosclerotic events beyond traditional 10-year estimates of risk."

"Because atherosclerotic disease develops over decades, yet early-life interventions represent an important method for risk reduction, these long-term risks are a major concern particularly among women, for whom cardiovascular disease remains underdiagnosed and undertreated," the researchers wrote.

U.S. guidelines support once-in-a-lifetime measurement of lp(a) in most individuals with increased risk of atherosclerotic cardiovascular disease because levels are determined genetically and don't change much. Prevention acknowledge both elevated lp(a) and hs-CRP as risk-enhancing factors "in selected individuals if measured." Neither is included in the Pooled Cohort Equation 10-year risk prediction that forms the basis for statin and other prevention efforts.

However, there does seem to be momentum building for other risk measures.

"This innovative work that provides a long-term view of cardiovascular risk is aligned with the growing focus on cardiovascular-kidney-metabolic health and the emergence of the PREVENT tool for estimating 30-year risk," according to an by Roger S. Blumenthal, MD, and Seth S. Martin, MD, MHS, both of the Johns Hopkins Ciccarone Center for the Prevention of Cardiovascular Disease in Baltimore.

"A long-term view can enable earlier recognition of cardiovascular disease risk in women and proactive preventive efforts to mitigate risk," they wrote. "The best way to avoid cardiovascular disease in the future is to reduce risk factors today, because tomorrow will soon be here."

The researchers argued that their finding "that a single measure of high-sensitivity CRP strongly predicted risk over a 30-year period should provide reassurance for clinicians who do not routinely measure this inflammatory biomarker because of concerns with respect to variability over time."

The Women's Health Study included behavioral, lifestyle, and demographic risk factors on 39,876 healthy, female health professionals in the United States between 1992 and 1995, with blood samples assayed in 27,939. All the participants were followed systematically and prospectively for up to 30 years, through January 2023.

Mean age at enrollment was 54.7 years, and 94.0% were white. Notably, mean body-mass index was 25.9, and diabetes was reported by 2.5% of the participants, "both of which reflected better cardiometabolic health than the current general U.S. population," the editorialists pointed out.

The primary endpoint was the first event in a composite of myocardial infarction, coronary revascularization, stroke, or death from cardiovascular causes. The hazard ratios were adjusted for age, assignment of patients in the main treatment randomization to receive aspirin or vitamin E, smoking status, diabetes, and blood pressure. The correlation between biomarkers was minimal.