Objectives

Smoking is a major risk factor for the development of both cardiovascular disease (CVD) and RA and may cause attenuated responses to anti-rheumatic treatments. Our aim was to compare disease activity, CVD risk factors and CVD event rates across smoking status in RA patients.

Methods

Disease characteristics, CVD risk factors and relevant medications were recorded in RA patients without prior CVD from 10 countries (Norway, UK, Netherlands, USA, Sweden, Greece, South Africa, Spain, Canada and Mexico). Information on CVD events was collected. Adjusted analysis of variance, logistic regression and Cox models were applied to compare RA disease activity (DAS28), CVD risk factors and event rates across categories of smoking status.

Results

Of the 3311 RA patients (1012 former, 887 current and 1412 never smokers), 235 experienced CVD events during a median follow-up of 3.5 years (interquartile range 2.5-6.1). At enrolment, current smokers were more likely to have moderate or high disease activity compared with former and never smokers (P < 0.001 for both). There was a gradient of worsening CVD risk factor profiles (lipoproteins and blood pressure) from never to former to current smokers. Furthermore, former and never smokers had significantly lower CVD event rates compared with current smokers [hazard ratio 0.70 (95% CI 0.51, 0.95), P = 0.02 and 0.48 (0.34, 0.69), P < 0.001, respectively]. The CVD event rates for former and never smokers were comparable.

Conclusion

Smoking cessation in patients with RA was associated with lower disease activity and improved lipid profiles and was a predictor of reduced rates of CVD events.

OBJECTIVES: Chronic inflammation promotes cardiovascular risk in rheumatoid arthritis (RA). Biological disease-modifying antirheumatic drugs (bDMARDs) improve disease activity and cardiovascular disease outcomes. We explored whether bDMARDs influence the impact of disease activity and inflammatory markers on long-term cardiovascular risk in RA. METHODS: We studied 4370 participants without cardiovascular disease in a 10-country observational cohort of patients with RA. Endpoints were (1) major adverse cardiovascular events (MACE) encompassing myocardial infarction, stroke and cardiovascular death; and (2) any ischaemic cardiovascular events (iCVE) including MACE plus revascularisation, angina, transient ischaemic attack and peripheral arterial disease. RESULTS: Over 26 534 patient-years, 239 MACE and 362 iCVE occurred. The interaction between 28-joint Disease Activity Score with C-reactive protein (DAS28-CRP) and bDMARD use was significant for MACE (p=0.017), suggesting the effect of DAS28-CRP on MACE risk differed among bDMARD users (n=515) and non-users (n=3855). DAS28-CRP (per unit increase) is associated with MACE risk in bDMARD non-users (HR 1.21 (95% CI 1.07 to 1.37)) but not users (HR 0.69 (95% CI 0.40 to 1.20)). The interaction between CRP (per log unit increase) and bDMARD use was also significant for MACE (p=0.011). CRP associated with MACE risk in bDMARD non-users (HR 1.16 (95% CI 1.04 to 1.30)), but not users (HR 0.65 (95% CI 0.36 to 1.17)). No interaction was observed between bDMARD use and DAS28-CRP (p=0.167) or CRP (p=0.237) for iCVE risk. CONCLUSIONS: RA activity and inflammatory markers associated with risk of MACE in bDMARD non-users but not users suggesting the possibility of biological-specific benefits locally on arterial wall independently of effects on systemic inflammation.

Background

In 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.

Methods

RA 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.

Results

A 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.

Conclusions

The 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.

Objectives

Patients with rheumatoid arthritis (RA) have an excess risk of cardiovascular disease (CVD). We aimed to assess the impact of CVD risk factors, including potential sex differences, and RA-specific variables on CVD outcome in a large, international cohort of patients with RA.

Methods

In 13 rheumatology centres, data on CVD risk factors and RA characteristics were collected at baseline. CVD outcomes (myocardial infarction, angina, revascularisation, stroke, peripheral vascular disease and CVD death) were collected using standardised definitions.

Results

5638 patients with RA and no prior CVD were included (mean age: 55.3 (SD: 14.0) years, 76% women). During mean follow-up of 5.8 (SD: 4.4) years, 148 men and 241 women developed a CVD event (10-year cumulative incidence 20.9% and 11.1%, respectively). Men had a higher burden of CVD risk factors, including increased blood pressure, higher total cholesterol and smoking prevalence than women (all p<0.001). Among the traditional CVD risk factors, smoking and hypertension had the highest population attributable risk (PAR) overall and among both sexes, followed by total cholesterol. The PAR for Disease Activity Score and for seropositivity were comparable in magnitude to the PAR for lipids. A total of 70% of CVD events were attributable to all CVD risk factors and RA characteristics combined (separately 49% CVD risk factors and 30% RA characteristics).

Conclusions

In a large, international cohort of patients with RA, 30% of CVD events were attributable to RA characteristics. This finding indicates that RA characteristics play an important role in efforts to reduce CVD risk among patients with RA.

Objectives

Cardiovascular disease (CVD) risk calculators developed for the general population do not accurately predict CVD events in patients with RA. We sought to externally validate risk calculators recommended for use in patients with RA including the EULAR 1.5 multiplier, the Expanded Cardiovascular Risk Prediction Score for RA (ERS-RA) and QRISK2.

Methods

Seven RA cohorts from UK, Norway, Netherlands, USA, South Africa, Canada and Mexico were combined. Data on baseline CVD risk factors, RA characteristics and CVD outcomes (including myocardial infarction, ischaemic stroke and cardiovascular death) were collected using standardized definitions. Performance of QRISK2, EULAR multiplier and ERS-RA was compared with other risk calculators [American College of Cardiology/American Heart Association (ACC/AHA), Framingham Adult Treatment Panel III Framingham risk score-Adult Treatment Panel (FRS-ATP) and Reynolds Risk Score] using c-statistics and net reclassification index.

Results

Among 1796 RA patients without prior CVD [mean ( s . d .) age: 54.0 (14.0) years, 74% female], 100 developed CVD events during a mean follow-up of 6.9 years (12430 person-years). Estimated CVD risk by ERS-RA [mean ( s . d .) 8.8% (9.8%)] was comparable to FRS-ATP [mean ( s . d .) 9.1% (8.3%)] and Reynolds [mean ( s . d .) 9.2% (12.2%)], but lower than ACC/AHA [mean ( s . d .) 9.8% (12.1%)]. QRISK2 substantially overestimated risk [mean ( s . d .) 15.5% (13.9%)]. Discrimination was not improved for ERS-RA (c-statistic = 0.69), QRISK2 or EULAR multiplier applied to ACC/AHA compared with ACC/AHA (c-statistic = 0.72 for all) or for FRS-ATP (c-statistic = 0.75). The net reclassification index for ERS-RA was low (-0.8% vs ACC/AHA and 2.3% vs FRS-ATP).

Conclusion

The QRISK2, EULAR multiplier and ERS-RA algorithms did not predict CVD risk more accurately in patients with RA than CVD risk calculators developed for the general population.