Cardiovascular risk prediction tools in Rheumatic Diseases

Cardiovascular diseases (CVD, heart disease, stroke) are the leading cause of premature death and a major cause of disability. Doctors can use statistical models to predict people’s risk of developing CVD and decide whether to start preventative treatment.
Rheumatic diseases are diverse, including rheumatoid arthritis (RA), psoriatic arthritis, ankylosing spondylitis, for example. Inflammation is a key risk factor for CVDs, so these people have much higher risk. For example, people with psoriatic arthritis have 55% higher risk of CVD. The same is true for other rheumatic diseases.
In RA, existing prediction tools have been shown to under-predict CVD risk, meaning people at risk may miss out on treatment. Despite this, risk prediction tools have not been tested for other rheumatic diseases to see how accurate they are.
Our aim to test the accuracy of several existing general population risk prediction tools in people with rheumatic diseases. If these tools can be used for these people, their care will be improved by promoting use in clinical practice. If they are not valid for people with rheumatic diseases, our study will highlight the need for future research.