CV Risk Is “Mostly Underestimated” in Patients With Rheumatic Diseases
Risk-prediction tools “mostly underestimate” cardiovascular (CV) disease risk among patients with rheumatic diseases, according to a new literature review. Some tools can overestimate CV risk as well.
Patients with rheumatic diseases have a higher risk of CV disease. Although the reasons for this increased risk are not fully understood, chronic inflammation is a suspected factor for the increased risk of myocardial infarction and stroke among patients with rheumatoid arthritis (RA) and systemic lupus erythematosus (SLE), in particular.
For their review, the researchers searched the MEDLINE, EMBASE, and Cochrane Central databases for studies published in English that included patients with RA, SLE, psoriatic arthritis (PsA), psoriasis, or ankylosing spondylitis (AS); included CV events as study outcomes; and evaluated at least one risk-prediction algorithm for CV risk.
The analysis included 11 of the 146 identified studies that assessed the accuracy of the following risk scores:
- Framingham Risk Score
- Systematic Coronary Risk Evaluation
- Reynolds Risk Score
- American College of Cardiology/American Heart Association Pooled Cohort Equations
- Expanded Cardiovascular Risk Prediction Score for Rheumatoid Arthritis
- Italian Progetto CUORE score
The analysis showed that multipliers were applied to general risk-prediction algorithms for patients with SLE and PsA. However, the review found that using multipliers, along with other risk factors such as biomarkers and variables related to specific rheumatic diseases, did not significantly improve the risk estimates resulting from these approaches.
“Our study confirmed that general risk algorithms mostly underestimate and at times overestimate CV risk in rheumatic patients,” the researchers concluded. “We did not find studies that evaluated models for psoriasis or AS, which further demonstrates a need for research in these populations.”
Colaco K, Ocampo V, Ayala AP, et al. Predictive utility of cardiovascular risk prediction algorithms in inflammatory rheumatic diseases: a systematic review. J Rheumatol. 2020;47(6):928-938. https://doi.org/10.3899/jrheum.190261