Younger age and female gender are determinants of underestimated cardiovascular risk in rheumatoid arthritis patients: a prospective cohort study

Background

Rheumatoid arthritis (RA) patients have an increased cardiovascular (CV) risk. Here, we aimed to investigate whether gender and age are contributing to the misclassification of CV risk in RA patients.

Methods

Prospectively collected data on cardiovascular risk factors and incident events from the Nijmegen inception cohort were analyzed, with up to 10 years follow-up. Original as well as the EULAR-modified (M)_SCORE algorithms were used to calculate CV risk. Patients were stratified in deciles according to predicted risk; the Hosmer-Lemeshow test was used to check concordance between observed and predicted risk, in subgroups of gender and age.

Results

There were 863 RA patients included with 128 incident CV events. When using SCORE in the whole group, there was evidence of a discrepancy between the predicted and observed CV risk (H-L test p < 0.003), mainly present in the female subgroup (H-L test p < 0.001). Interestingly, 36% of females who developed an event belonged to the low CV risk group, whereas this was just 10% in RA males. When analyzing the subgroups based on age, a discrepancy was present only in the youngest patients (H-L test p < 0.001 in patients < 55 years) consisting of an underestimation of CV risk (5.3% predicted vs. 8.0% observed). Similar results were obtained when the M_SCORE was applied.

Conclusion

CV risk is especially underestimated in female and younger RA patients. This suggests that modifying the weight for the female gender and/or younger age in currently used CV risk algorithms might improve their predictive value in RA, contributing to better CV risk management.

Prediction of cardiovascular events in rheumatoid arthritis using risk age calculations: evaluation of concordance across risk age models

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.

Cost-Effectiveness of Cardiovascular Screening in Patients With Rheumatoid Arthritis

OBJECTIVE

Early detection and preemptive treatment of patients at risk is of great importance in reducing the excess risk of cardiovascular (CV) disease in rheumatoid arthritis (RA). However, it is unclear how much screening is cost-effective in RA. The objective is to assess whether CV screening in RA proves to be cost-effective from a medical perspective, using different scenarios based on different guidelines.

METHODS

A Markov chain model was used with a time horizon of 10 years. Parameter values were mainly obtained from literature and from RA patients screened for CV diseases at the Radboud University Medical Centre, Nijmegen, The Netherlands. The primary outcome was incremental cost-effectiveness expressed as costs per quality-adjusted life year (QALY) gained. Probabilistic sensitivity analysis was performed and described in willingness-to-pay curves; several scenarios were built.

RESULTS

In the base case scenario, in 82% of the simulations, screening proved to be dominant compared to no screening. The mean QALY gain was 0.09 (95% percentile -0.07, 0.27), and the mean cost savings were €-1,057 (95% percentile -€2,825, €333). Different scenarios showed small differences in cost-effectiveness; the probability that screening is dominant remained high with the lowest probability being 50% for a very conservative scenario.

CONCLUSION

Screening for CV events in RA patients was estimated to be cost-effective with high chances of being less expensive and more effective. These results support endorsement of screening for CV risk in patients with RA.