Nihtyanova, SI;
Sari, A;
Harvey, JC;
Leslie, A;
Derrett-Smith, EC;
Fonseca, C;
Ong, VH;
(2020)
Using autoantibodies and cutaneous subset to develop outcome-based disease classification in systemic sclerosis.
Arthritis & Rheumatology
, 72
(3)
pp. 465-476.
10.1002/art.41153.
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Nihtyanova Denton 2019 in press A and R.pdf - Accepted Version Download (2MB) | Preview |
Abstract
OBJECTIVE: To describe the associations between autoantibodies, presentation and outcome among systemic sclerosis (SSc) patients. We propose a new SSc classification incorporating antibodies and cutaneous subset. METHODS: Survival analysis was used to assess the effect of antibodies on organ disease and death. RESULTS: The study included 1325 subjects. The ACA+ limited cutaneous (lc)SSc group (n=374) had the highest 20-year survival (65.3%), lowest incidence of clinically-significant pulmonary fibrosis (csPF, 8.5%) and scleroderma renal crisis (SRC, 0.3%), low cardiac SSc incidence (4.9%), while pulmonary hypertension (PH) frequency was similar to the cohort average. The anti-Scl70+ lcSSc (n=138) and diffuse cutaneous (dc)SSc groups (n=149) had the highest csPF incidence (86.1% and 84% at 15 years). The dcSSc group had the lowest survival (32.4%) and the second highest incidence of cardiac SSc (12.9%) at 20 years, while in the lcSSc group other complications were rare, demonstrating the lowest incidence of PH (6.9%) and second highest survival (61.8%). The anti-RNA polymerase+ group (n=147) had the highest incidence of SRC (28.1%). The anti-U3RNP+ group (n=56) had the highest PH (33.8%) and cardiac SSc incidence (13.2%). Among lcSSc patients with other autoantibodies (n=295), risk of SRC and cardiac SSc was low, while other outcomes were similar to the cohort average. DcSSc patients with other antibodies (n=166) had poor prognosis, with the second lowest survival (33.6%) and frequent organ complications. CONCLUSION: We highlight the importance of autoantibodies, cutaneous subset and disease duration when assessing SSc morbidity and mortality. Our classification may benefit disease monitoring and clinical trial design.
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