Two new risk factors added to a traditional risk model improved prediction of a woman’s 10-year risk of cardiovascular disease or stroke, a US team of researchers found.
Two versions of the revised model, with validated risk algorithms, reclassified 40% to 50% of women at 10-year risk into higher- or lower-risk categories, according to a report in the 14 February issue of the Journal of the American Medical Association.
Two new risk variables; parental family history of premature coronary heart disease (before age 60) and high-sensitivity C-reactive protein (hsCRP), were added to existing variables in the standard Adult Treatment Panel-III risk (ATP-III) score, said Dr Paul Ridker, of Brigham of Women’s Hospital, and colleagues.
From 1956 through 1966 investigators on the Framington heart study defined what they named “coronary risk factors” (hypertension, smoking, diabetes, and hyperlipidemia). Risk classifications, to date, have been based on these factors. However, Dr Ridker argues, among women, up to 20% of all coronary events occur in the absence of these risk factors, whereas many women who have traditional risk factors do not then have a coronary event.
Dr Ridker and colleagues developed and validated cardiovascular risk algorithms for women based on a large set of traditional and new risk factors. The researchers assessed 35 risk factors among 24,558 initially healthy women (free of cardiovascular disease and cancer at the beginning of the study) 45 years or older from the US-wide Women’s Health Study. These women were followed up for a median of 10.2 years for incident cardiovascular events, such as myocardial infarction, ischemic stroke, coronary revascularization, and cardiovascular deaths.
The researchers used data among a randomly selected two-thirds of the women (n = 16,400) to develop new algorithms that were then tested to compare observed and predicted outcomes in the remaining one-third of women (n = 8,158). The new algorithms are termed the Reynolds Risk Score and the clinically simplified model for non-diabetic women includes age, systolic blood pressure, current smoking, total and HDL cholesterol, high sensitivity C-reactive protein (CRP) and parental history of myocardial infarction before age 60.
In the team’s analyses, large proportions of women with 10-year risk estimates of 5% to less than 10%, or of 10% to less than 20%, based on current ATP-III (Adult Treatment Panel III) risk scores were reclassified at either higher or lower risk of total cardiovascular disease when either of the new algorithms was used.
“As 8 to 10 million US women have an ATP-III estimated 10-year risk between 5% and 20 %, application of these data could have an immediate effect on cardiovascular prevention,” the authors conclude.
In an accompanying editorial Dr Roger Blumenthal, of Johns Hopkins in Baltimore, and colleagues called the study a “timely contribution to the cardiovascular-risk-prediction literature.”
These findings, they said, raise several critical questions including what is the impact in terms of new risk-prediction categories, altering the low-density lipoprotein cholesterol goal, and influencing the choice of whether to treat with life-long aspirin in individual patients.
The new model reclassified 5,400 women (5.4%) to high-risk with LDL-C goals of less than100 mg/dL and an optional goal of less than 70 mg/dL, Dr. Blumenthal said.
On the other hand, 13,400 (13.4%) of the women were reclassified as very low-risk women with a less than 5% risk of a major cardiovascular disease event and with an LDL goal of less than 160 mg/dL.
As a result, the editorialists said, approximately 20% of women will have different lipid treatment goals based on the Reynolds model, compared with the ATP-III guidelines, when considering a 5% to 20% 10-year risk as an intermediate risk.
“Future multivariable models to predict a woman’s long-term (20 to 30 years) risk of developing a major atherosclerotic vascular disease event are also needed. The Reynolds Risk Score is an important contribution to preventive cardiology and provides the framework for evaluating future emerging risk factors,” Dr. Blumenthal and his colleagues concluded.
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