Systemic Sclerosis-Specific Determinants of Major Adverse Cardiovascular Events: Development of an Exploratory Cardiovascular Risk Model Beyond Traditional Risk Factors

Background: Patients with systemic sclerosis (SSc) have an increased burden of cardiovascular disease, resulting from the combined effects of traditional cardiovascular risk factors, chronic inflammation, endothelial dysfunction, and disease-specific vascular involvement. Current cardiovascular risk prediction tools may not adequately capture the complex pathophysiological mechanisms contributing to cardiovascular complications in SSc. Objectives: This study aimed to evaluate the association between traditional cardiovascular risk factors and SSc-specific clinical characteristics with major adverse cardiovascular events (MACE) and to assess the incremental predictive value of disease-related variables beyond conventional cardiovascular risk factors. Methods: We conducted a retrospective observational cohort study including 272 SSc patients followed in a tertiary rheumatology center. The primary outcome was extended MACE, defined as the occurrence of cardiovascular death, myocardial infarction, ischemic stroke, hospitalization for heart failure, life-threatening arrhythmias, coronary or peripheral revascularization, and other major cardiovascular events. Logistic regression models were used to identify independent predictors of MACE. The incremental predictive value of SSc-specific variables was assessed by comparing model discrimination using receiver operating characteristic (ROC) curves, area under the curve (AUC), and Nagelkerke R2. Results: During a median follow-up period of 36 months (IQR 24–72), 77 patients (28.3%) experienced at least one extended MACE, while 21 patients (7.8%) fulfilled the restrictive definition of primary MACE. In univariable analysis, traditional cardiovascular factors associated with MACE included age at diagnosis (OR 1.03, 95% CI 1.01–1.05; p = 0.004), arterial hypertension (OR 2.33, 95% CI 1.35–4.00; p = 0.002), and dyslipidemia requiring statin therapy (OR 3.19, 95% CI 1.73–5.87; p < 0.001). Among SSc-specific variables, pulmonary hypertension showed the strongest association with MACE (OR 8.78, 95% CI 4.54–16.72; p < 0.001), followed by scleroderma renal crisis (OR 3.98, 95% CI 1.74–9.13; p = 0.001), digital ulcers (OR 3.71, 95% CI 1.94–7.07; p < 0.001), and interstitial lung disease (OR 3.43, 95% CI 1.80–6.53; p < 0.001). A conventional cardiovascular risk model demonstrated moderate predictive performance (Nagelkerke R2 = 0.149; AUC = 0.708). The sequential addition of SSc-specific variables resulted in a progressive improvement in model performance, with pulmonary hypertension producing the greatest incremental benefit (AUC = 0.811; Nagelkerke R2 = 0.326). An exploratory SSc-specific cardiovascular risk model including dyslipidemia treated with statins, diffuse cutaneous SSc, pulmonary hypertension, and C-reactive protein levels showed superior predictive performance (Nagelkerke R2 = 0.387; AUC = 0.821). Conclusions: Cardiovascular risk in SSc is not fully explained by traditional cardiovascular risk factors. Disease-specific characteristics, particularly pulmonary hypertension, diffuse cutaneous involvement, and inflammatory activity, provide significant incremental prognostic information. The integration of SSc-related variables into cardiovascular risk assessment models may improve identification of patients at increased risk of major cardiovascular events. The proposed model remains exploratory and requires external validation before clinical implementation.