Background: The European Scleroderma Trials and Research Group (EUSTAR) recently developed a preliminarily revised activity index (AI) that performed better than the European Scleroderma Study Group Activity Index (EScSG-AI) in systemic sclerosis (SSc).
Objective: To assess the predictive value for short-term disease severity accrual of the EUSTAR-AI, as compared with those of the EScSG-AI and of known adverse prognostic factors.
Methods: Patients with SSc from the EUSTAR database with a disease duration from the onset of the first non-Raynaud sign/symptom ≤5 years and a baseline visit between 2003 and 2014 were first extracted. To capture the disease activity variations over time, EUSTAR-AI and EScSG-AI adjusted means were calculated. The primary outcome was disease progression defined as a Δ≥1 in the Medsger's severity score and in distinct items at the 2-year follow-up visit. Logistic regression analysis was carried out to identify predictive factors.
Results: 549 patients were enrolled. At multivariate analysis, the EUSTAR-AI adjusted mean was the only predictor of any severity accrual and of that of lung and heart, skin and peripheral vascular disease over 2 years.
Conclusion: The adjusted mean EUSTAR-AI has the best predictive value for disease progression and development of severe organ involvement over time in SSc.
Keywords: autoimmune diseases; outcomes research; systemic sclerosis.
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