AB1226 PREDICTING CARDIOVASCULAR EVENTS IN PATIENTS WITH SPONDYLOARTHRITIS AND PSORIATIC ARTHRITIS: THREE RISK ALGORITHMS

Abstract

Background:Inflammatory joint disorders have an increased cardiovascular (CV) risk when compared with general population. In 2009, the EULAR task force advocated the use of a 1.5 multiplication factor for these risk prediction models in Rheumatoid Arthritis patients with specific characteristics. The SCORE was not modified in patients with Psoriatic Arthritis (PsA) and Spondyloarthritis (SpA) in accordance with the present EULAR recommendations.Objectives:To assess the accuracy of several CV risk algorithms to predict an event and determine its sensibility and specificity.Methods:A retrospective analysis of PsA and SpA patients, followed in our department in Local Health Unit of Guarda during one year (2019) was done. We determined CV risk profile of our patients using the following data: gender, age, smoking status, blood pressure, lipid values and diabetes mellitus status. These variables were used to calculate risk prediction algorithms such as Framingham, the American College of Cardiology/American Heart Association (ACC/AHA) risk score and the Systematic Coronary Risk Evaluation (SCORE). Discriminatory ability for CV risk prediction was evaluated by the area under the ROC curves. Sensibility and specificity were calculated for low-to-intermediate and intermediate-to-high risk cut-offs. Cut-off values that mark the high risk were defined in 5% for SCORE, 20% for Framingham and ACC/AHA.Results:112 caucasic patients were included, 61% female with a mean age of 52.15±14.18 years and mean BMI of 27.11±4.81kg/m2. 7 patients weren´t eligible to apply these cardiovascular scores. 8 patients were identified with non-fatal cardiovascular events (2 cases of stroke, 5 cases of myocardial infarction and 1 case of thrombophlebitis). 69 patients diagnosed with SpA and 43 with PsA, five CV events identified in SpA patients and three in PsA patients. Area under the ROC in SpA were 0.729 (95% CI 0.461 to 0.996) for SCORE, 0.839 (95% CI 0.735 to 0.943) for Framingham and 0.804 (95% CI 0.683 to 0.925) for ACC/AHA. Area under the ROC in PsA patients were 0.603 (95% CI 0.327 to 0.879) for SCORE, 0.660 (95% CI 0.326 to 0.995) for Framingham and 0.804 (95% CI 0683 to 0.925) for ACC/AHA. Sensibility and specificity were discriminated in table 1.Table 1.Sensibility, specificity, positive predictive value (PPV) and negative predictive value (NPV) of CV risk algorithmsSensibility (%)Specificity (%)PPV (%)NPV (%)SCORE > 1%SpA75631896PsA100415100SCORE > 5%SpANANANANAPsA093097Framingham >10%SpA83782898PsA5051595Framingham >20%SpA33862093PsA5069896ACC/AHA >5%SpA67772994PsA100449100ACC/AHA >20%SpA17861488PsA50831497Conclusion:A good discrimination between patients with or without CV events has been demonstrated by area under the ROC curve, particularly to SpA patients. In PsA, the sample was smaller, which represents a limitation in this study. SCORE >5% did not identify CV events, therefore sensibility couldn’t be calculated. Overall, the algorithms studied presented a low sensibility, underestimating CV risk. This could be explained since disease-related factors are not reflected in these scores. In our opinion, better algorithms are needed to correctly assess cardiovascular risk algorithms for SpA and PsA, since the majority of the events occur in patients with low-intermediate risk.