Abstract
BackgroundIn younger individuals, low absolute risk of cardiovascular disease (CVD) may conceal an increased risk age and relative risk of CVD. Calculation of risk age is proposed as an adjuvant to absolute CVD risk estimation in European guidelines. We aimed to compare the discriminative ability of available risk age models in prediction of CVD in rheumatoid arthritis (RA). Secondly, we also evaluated the performance of risk age models in subgroups based on RA disease characteristics.MethodsRA patients aged 30–70 years were included from an international consortium named A Trans-Atlantic Cardiovascular Consortium for Rheumatoid Arthritis (ATACC-RA). Prior CVD and diabetes mellitus were exclusion criteria. The discriminatory ability of specific risk age models was evaluated using c-statistics and their standard errors after calculating time until fatal or non-fatal CVD or last follow-up.ResultsA total of 1974 patients were included in the main analyses, and 144 events were observed during follow-up, the median follow-up being 5.0 years. The risk age models gave highly correlated results, demonstrating R2 values ranging from 0.87 to 0.97. However, risk age estimations differed > 5 years in 15–32% of patients. C-statistics ranged 0.68–0.72 with standard errors of approximately 0.03. Despite certain RA characteristics being associated with low c-indices, standard errors were high. Restricting analysis to European RA patients yielded similar results.ConclusionsThe cardiovascular risk age and vascular age models have comparable performance in predicting CVD in RA patients. The influence of RA disease characteristics on the predictive ability of these prediction models remains inconclusive.
Highlights
In younger individuals, low absolute risk of cardiovascular disease (CVD) may conceal an increased risk age and relative risk of CVD
The Systematic Coronary Risk Evaluation (SCORE) algorithm estimates CVD risk according to age, sex, and modifiable CVD risk factors (CVD-rheumatoid factor (RF)) including smoking status, systolic blood pressure, and total cholesterol (TC)
We aimed to evaluate the performance of these risk age models in subgroups of rheumatoid arthritis (RA) patients stratified according to rheumatic disease related characteristics
Summary
Low absolute risk of cardiovascular disease (CVD) may conceal an increased risk age and relative risk of CVD. Numerous CVD risk prediction models have been developed and differ in terms of CVD events (fatal or nonfatal), patient population of interest, and CVD risk factors (CVD-RFs) included [6]. Using the Systematic Coronary Risk Evaluation (SCORE) algorithm, the absolute 10-year risk of a fatal CVD event can be estimated separately for patients in countries with low and high risk of CVD [8]. The European League Against Rheumatism (EULAR) advises to adapt CVD risk prediction models with a 1.5 multiplication factor to the estimated risk of CVD for patients with RA [11]
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