Cardiovascular risk estimation in older persons: SCORE O.P.

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Abstract

Estimation of cardiovascular disease risk, using SCORE (Systematic COronary Risk Evaluation) is recommended by European guidelines on cardiovascular disease prevention. Risk estimation is inaccurate in older people. We hypothesized that this may be due to the assumption, inherent in current risk estimation systems, that risk factors function similarly in all age groups. We aimed to derive and validate a risk estimation function, SCORE O.P., solely from data from individuals aged 65 years and older.

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Most cited references 15

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General cardiovascular risk profile for use in primary care: the Framingham Heart Study.

Ralph B. D’Agostino, Ramachandran S Vasan, Michael J Pencina … (2008)

Separate multivariable risk algorithms are commonly used to assess risk of specific atherosclerotic cardiovascular disease (CVD) events, ie, coronary heart disease, cerebrovascular disease, peripheral vascular disease, and heart failure. The present report presents a single multivariable risk function that predicts risk of developing all CVD and of its constituents. We used Cox proportional-hazards regression to evaluate the risk of developing a first CVD event in 8491 Framingham study participants (mean age, 49 years; 4522 women) who attended a routine examination between 30 and 74 years of age and were free of CVD. Sex-specific multivariable risk functions ("general CVD" algorithms) were derived that incorporated age, total and high-density lipoprotein cholesterol, systolic blood pressure, treatment for hypertension, smoking, and diabetes status. We assessed the performance of the general CVD algorithms for predicting individual CVD events (coronary heart disease, stroke, peripheral artery disease, or heart failure). Over 12 years of follow-up, 1174 participants (456 women) developed a first CVD event. All traditional risk factors evaluated predicted CVD risk (multivariable-adjusted P<0.0001). The general CVD algorithm demonstrated good discrimination (C statistic, 0.763 [men] and 0.793 [women]) and calibration. Simple adjustments to the general CVD risk algorithms allowed estimation of the risks of each CVD component. Two simple risk scores are presented, 1 based on all traditional risk factors and the other based on non-laboratory-based predictors. A sex-specific multivariable risk factor algorithm can be conveniently used to assess general CVD risk and risk of individual CVD events (coronary, cerebrovascular, and peripheral arterial disease and heart failure). The estimated absolute CVD event rates can be used to quantify risk and to guide preventive care.

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Use of multiple biomarkers to improve the prediction of death from cardiovascular causes.

Johan Ärnlöv, Erik Ingelsson, Samar Basu … (2008)

The incremental usefulness of adding multiple biomarkers from different disease pathways for predicting the risk of death from cardiovascular causes has not, to our knowledge, been evaluated among the elderly. We used data from the Uppsala Longitudinal Study of Adult Men (ULSAM), a community-based cohort of elderly men, to investigate whether a combination of biomarkers that reflect myocardial cell damage, left ventricular dysfunction, renal failure, and inflammation (troponin I, N-terminal pro-brain natriuretic peptide, cystatin C, and C-reactive protein, respectively) improved the risk stratification of a person beyond an assessment that was based on the established risk factors for cardiovascular disease (age, systolic blood pressure, use or nonuse of antihypertensive treatment, total cholesterol, high-density lipoprotein cholesterol, use or nonuse of lipid-lowering treatment, presence or absence of diabetes, smoking status, and body-mass index). During follow-up (median, 10.0 years), 315 of the 1135 participants in our study (mean age, 71 years at baseline) died; 136 deaths were the result of cardiovascular disease. In Cox proportional-hazards models adjusted for established risk factors, all of the biomarkers significantly predicted the risk of death from cardiovascular causes. The C statistic increased significantly when the four biomarkers were incorporated into a model with established risk factors, both in the whole cohort (C statistic with biomarkers vs. without biomarkers, 0.766 vs. 0.664; P<0.001) and in the group of 661 participants who did not have cardiovascular disease at baseline (0.748 vs. 0.688, P=0.03). The improvement in risk assessment remained strong when it was estimated by other statistical measures of model discrimination, calibration, and global fit. Our data suggest that in elderly men with or without prevalent cardiovascular disease, the simultaneous addition of several biomarkers of cardiovascular and renal abnormalities substantially improves the risk stratification for death from cardiovascular causes beyond that of a model that is based only on established risk factors. Copyright 2008 Massachusetts Medical Society.