Evaluation of novel cardiovascular risk calculators in patients with rheumatoid arthritis

Abstract Background Patients with rheumatoid arthritis (RA) have a higher cardiovascular risk (CVR) compared to the general population contributing to a decreased life expectancy. Systematic and periodic assessment of CVR is recommended in all patients with RA. The newly developed PREVENTTM calculator was designed to estimate the absolute risk of cardiovascular disease and provides an estimate of atherosclerotic cardiovascular disease and heart failure. Purpose This study aimed to evaluate the sensitivity and specificity of the new PREVENTTM algorithm to identify CP in RA patients without prior CVD and to compare these results with other CVR algorithms. Methods We performed a cross-sectional study that included patients with RA aged 40 to 79 who fulfilled the 2010 ACR/EULAR Classification Criteria for RA. Patients with previous CVD, pregnancy, or overlap syndrome were excluded. A B-mode carotid ultrasound was performed on all patients. The presence of CP was defined as diffuse carotid intima-media thickness (cIMT) ³1.2 mm or focal thickness ³0.5 mm. The CVR was evaluated using Globorisk, HEARTS, QRISK3, ERS-RA, SCORE2, and PREVENTTM algorithms. The result was multiplied by 1.5 in algorithms where RA is not included as a variable, according to EULAR 2015/2016 recommendations. ROC curve analysis was performed to evaluate the different CVR algorithms' performance to identify CP. Youden index was calculated to select the optimum cutoff point and posteriorly calculate sensitivity, specificity, and predictive values. A p-value of £0.05 was considered statistically significant. Statistical analysis was performed with SPSS version 29.0 (IBM Corp, Armonk, NY, USA). Results A total of 261 patients with RA were included, mostly women (n=244, 93.5%), with a mean age of 56±9.3 years, and a median disease duration of 7.7 (3.0-14.7) years. Dyslipidemia was the most prevalent CVR factor (n=104, 39.8%). The prevalence of CP was 38.0%. According to the ROC curves, the Globorisk, HEARTS, and QRISK3 algorithms showed a higher area under the curve (AUC) than the other algorithms. The HEARTS and QRISK3 algorithms showed the highest positive likelihood ratios, showing rates of 1.87 and 1.84, respectively, to identify RA patients with CP (Figure 1). Conclusion Our study showed that Globorisk, HEARTS, and QRISK3 calculators presented the best diagnostic accuracy to detect CP in patients with RA. The novel CVR calculator PREVENTTM did not show better performance than older calculators in our population. Imaging studies evaluating coronary artery calcium and CP may offer better alternatives in high-risk populations like patients with RA.