Objectives: To compare two algorithms for cardiovascular (CV) risk estimation in systemic sclerosis (SSc) patients, investigating correlations with disease characteristics. Methods: Traditional CV risk factors and SSc-specific characteristics were assessed in a cohort of SSc patients. Framingham and QRISK3 algorithms were used to estimate the risk of developing a CV disease over the next 10 years. Results: Seventy-two SSc patients were enrolled. Among those 56 without previous CV events, Framingham reported a median risk score of 9.6%, classifying 24 (42.9%) subjects at high risk. QRISK3 showed a median risk score of 15.8%, with 36 (64.3%) patients considered at high risk. Both algorithms revealed a significant role of some traditional risk factors and a noteworthy potential protective role of endothelin receptor antagonists (p=.003). QRISK3 was also significantly influenced by some SSc-specific characteristics, such as limited cutaneous subset (p=.01), interstitial lung disease (p=.04), and non-ischemic heart involvement (p=.03), with the first two maintaining statistical significance in the multivariate analysis (p=.02). Conclusions: QRISK3 classifies more SSc patients at high risk to develop CV diseases than Framingham, reflecting the influence of some SScspecific characteristics. If its predictive accuracy were prospectively verified, the use of QRISK3 as a tool in the early detection of SSc patients at high CV risk should be recommended. [ABSTRACT FROM AUTHOR]