General risk algorithms inaccurately predict CV risk in rheumatic patients
Cardiovascular (CV) risk prediction algorithms tend to be inaccurate, frequently underestimating and sometimes overestimating the risk of CV in patients with inflammatory rheumatic diseases, a recent study has shown.
The investigators systematically searched the databases of Embase, Medline, and Cochrane Central for studies that were originally published in English, included clinical CV events as outcomes, examined the predictive properties of at least one CV risk prediction algorithm, and included patients with rheumatoid arthritis (RA), ankylosing spondylitis (AS), systemic lupus erythematosus (SLE), psoriatic arthritis (PsA), or psoriasis. By design, only cohort studies following participants for CV events were included.
Of the 146 manuscripts identified, only 11 were included. Eligible studies assessed the predictive performance of the following: Framingham Risk Score, QRISK2, 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, and the Italian Progetto CUORE score.
Approaches, such as the use of multipliers, biomarkers, disease-specific variables, or a combination of these to modify or develop an algorithm, were applied to improve the predictive performance of general risk algorithms in RA patients. For instance, multipliers were employed in general risk algorithms in both SLE and PsA patients.
Additionally, efforts to include nontraditional risk factors, disease-related variables, multipliers, and biomarkers in studies of RA and SLE patients did not succeed in significantly improving risk estimate.
“We did not find studies that evaluated models for psoriasis or AS, which further demonstrates a need for research in these populations,” the investigators said.