Performance of four current risk algorithms in predicting cardiovascular events in patients with early rheumatoid arthritis

Objective This study was undertaken to assess the predictive ability of 4 established cardiovascular (CV) risk models for the 10-year risk of fatal and non-fatal CV diseases in European patients with rheumatoid arthritis. Methods Prospectively collected data from the Nijmegen early rheumatoid arthritis (RA) inception cohort was used. Discriminatory ability for CV risk prediction was estimated by the area under the receiver operating characteristic curve. Calibration was assessed by comparing the observed versus expected number of events using Hosmer-Lemeshov tests and calibration plots. Sensitivity and specificity were calculated for the cut-off values of 10% and 20% predicted risk. Results Areas under the receiver operating characteristic curve were 0.78-0.80, indicating moderate to good discrimination between patients with and without a CV event. The CV risk models Systematic Coronary Risk Evaluation (SCORE), Framingham risk score (FRS) and Reynolds risk score (RRS) primarily underestimated CV risk at low and middle observed risk levels, and mostly overestimated CV risk at higher observed risk levels. The QRisk II primarily overestimated observed CV risk. For the 10% and 20% cut-off values used as indicators for CV preventive treatment, sensitivity ranged from 68-87% and 40-65%, respectively and specificity ranged from 55-76% and 77-88%, respectively. Depending on the model, up to 32% of observed CV events occurred in patients with RA who were classified as low risk (< 10%) for CV disease. Conclusions Established risk models generally underestimate (Systematic Coronary Risk Evaluation score, Framingham Risk Score, Reynolds risk score) or overestimate (QRisk II) CV risk in patients with RA.