Abstract
Introduction: Patients with rheumatoid arthritis (RA) have an increased risk of cardiovascular disease (CVD), which is not accurately predicted by risk calculators designed for the general population. Hypothesis: To develop a RA specific CVD risk calculator. Methods: The study population included RA patient cohorts from 8 centres in 7 countries. In all cases, data had been collected prospectively on CV outcomes (MI, revascularization, angina, stroke, TIA, PAD and CV death). At baseline RA characteristics (duration, seropositivity, disease activity (DAS28) and CRP/ESR) were collected in addition to traditional CV risk factors. Cox models stratified by centre were used to develop a CVD risk calculator considering traditional CV risk factors and RA characteristics. Model performance was assessed using measures of discrimination and calibration. Results: In total 3176 RA patients who did not have prior CVD were included (mean age: 55 [SD: 14] years, 73% female). During a mean follow-up of 7.8 years (24733 person years), 314 had a CVD event. The multivariable risk score modelling revealed 2 models including either seropositivity or DAS28 along with age, sex, current smoking, presence of hypertension, and ratio of total cholesterol to high-density lipoprotein (table). Both 10-fold cross validation and multiple imputation analyses confirmed these findings with little change to the estimated coefficients. Both models demonstrated good discrimination (c-statistic: 0.76 and 0.74) and calibration (observed/predicted ratio: 1.00; 95% confidence interval: 0.89, 1.12). The ATACC-RA (mean: 11.5%, SD 14.1%) showed significantly improved discrimination compared to either Framingham (c-statistic: 0.71, p<0.001) or SCORE (c-statistic: 0.72, p<0.001) risk algorithms. Conclusions: Development of an RA-specific CVD risk calculator is feasible by pooling resources from many centres. Further development including external validation is underway.
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