Background Cardiovascular (CV) risk in RA is well-recognized, but detection of high risk patients and prevention of CV disease (CVD) are still major challenges.
Objectives To determine ability of the new ACC/AHA 10-year ASCVD risk algorithm in detecting high CV risk RA patients identified by carotid US, compared to SCORE and QRisk II and to determine the factors that may improve CV risk estimation in RA.
Methods RA patients (n=216) without CVD, DM or chronic kidney disease were assessed. SCORE, 2013 ACC/AHA 10-year ASCVD risk, QRisk II indices and their modified versions (mSCORE, mASCVD, mQRisk II) according to EULAR recommendations were calculated. All patients were evaluated with carotid ultrasonography (US). Carotid intima-media thickness (cIMT) >0.90 mm and/or carotid plaques were used as the gold standard test for subclinical atherosclerosis and high CV risk (US+). Retrospectively, along with disease characteristics, DAS28 scores, ESR and CRP values of each visit during the entire follow-up of RA patients were recorded and average DAS28, ESR and CRP were calculated.
Results Eleven (5.1%), 15 (6.9%) and 44 (20.4%) patients were defined as having high CV risk according to SCORE (≥5%), QRisk II (≥20%) and ACC/AHA 10-year ASCVD risk (≥7.5%), respectively. Concerning US results, 52 (24.1%) patients were US+. Of the US+ patients, 8 (15.4%), 7 (13.5%) and 23 (44.2%) patients were classified as high CV risk according to SCORE, QRisk II and ACC/AHA 10-year ASCVD risk. The ACC/AHA 10-year ASCVD risk index failed to identify 55.8% of US+ patients, but it better identified US+ patients than SCORE and QRisk II (P<0.0001). The EULAR multiplier factor was used in 98 (45.4%) patients. With this modification reclassification from moderate to high risk occurred only in 2, 5 and 7 patients according to mSCORE, mQriks II and mASCVD. When moderate CV risk patients (SCORE>1% and <5%, QRisk II>10% and <20%, ASCVD>5% and <7.5%) were included in the high risk category, detection of US+ patients, i.e. sensitivity, increased dramatically (up to ∼60% for all indices), with slight decrease in specificity (∼75%). In comparison of US+ and US-, US+ patients were older, had higher average DAS28 scores, average ESR and CRP levels than the US- patients (Table 1). US+ patients had significantly lower tumour necrosis factor-α inhibitor (TNFi) exposure (35.3% vs 52.8%; P=0.029) while other treatment modalities were comparable. In multivariable logistic regression analysis, age >45 years (OR=12.3, 95% CI [2.7-56.5], P=0.001), being ever-smoked (OR=2.2, 95% CI [1.1-4.6], P=0.031), elevated ESR (OR=2.7, 95% CI [1.3-5.5], P=0.008), average CRP (OR=1.05, 95% CI [1.01-1.1], P=0.008) and being never used TNFi (OR=0.42, 95% CI [0.20-0.86], P=0.018) were independently associated with subclinical atherosclerosis in RA patients.
Conclusions The 2013 ACC/AHA 10-year ASCVD risk estimator is better than SCORE and QRisk II indices in RA. Despite that, ACC/AHA 10-year ASCVD failed to identify 55% of high risk patients detected by carotid US. New RA-specific risk algorithms are required to identify high-risk patients who may benefit from preventive strategies. Till the development of a good RA-specific CV risk estimator, adjustment of the threshold may be a better modification than EULAR multiplier factor.
Disclosure of Interest None declared