A REDUCED NUMBER OF CAPILLARIES AND AN INCREASED NUMBER OF MEGACAPILLARIES PREDICT THE DEVELOPMENT OF SYSTEMIC SCLEROSIS IN RAYNAUD’S PHENOMENON PATIENTS AT RISK

Background: Undifferentiated connective tissue disease at risk for systemic sclerosis (UCTD-risk-SSc) is a condition characterised by Raynaud’s phenomenon and either SSc marker autoantibodies or typical capillaroscopic findings or both, unsatisfying classification criteria for SSc and evolving into definite SSc in about 30-50% of cases (1,2). Recently, we developed a weighted score based on a baseline IF-ANA titer ≥1:320, marker autoantibody positivity and presence of avascular areas at videocapillaroscopy identifying patients who will evolve with a 91.3% sensitivity and a 73.2% specificity (3). Objectives: To improve the predictivity of the score assessing the role of marker autoantibody ELISA titer and further capillaroscopic items. Methods: The 102 UCTD-risk-SSc patients investigated for the development of the previous score were reassessed for anti-Scl-70 and anti-centromere antibody titers detected by ELISA and for the mean number of capillaries observed in the same capillaroscopic field (Cs) and the total number of giant capillaries (GC) by videocapillaroscopy (4). Each patient was evaluated every 6 months to assess disease progression. Risk prediction was assessed by Cox regression analyses. The predictive value of the score was determined by receiver operating curve (ROC) analysis. Results: Table 1 shows the resulting predictive variables in multivariate Cox analysis and their relative weight in a 10-point scale. No increase in the predictivity was detected by adding the anti-Scl-70 and anti-centromere antibody ELISA titers. However, a mean number of Cs≤5/mm and GC>5 improved the score. At ROC analysis (Figure 1) a score >3.25 predicted evolution to SSc with a sensitivity of 93.5% and a 75% specificity (AUC=0.91). Table 1. Indipendent predictive variables in multivariate regression analysis and the resulting weighted prediction model * Variable β HR 95% CI P Weight Anti-Scl70 Cs≤5/mm 2.9553 1.9093 19.21 6.75 4.87-75.76 2.07-22.00 <0.001 0.001 3.25 2 ANA ≥ 1:320 1.7402 5.70 1.42-22.85 0.01 2 ACA 1.6740 5.33 1.51-1.90 0.01 1.75 GC>5 1.0049 2.73 1.44-5.17 0.002 1 *β: regression coefficients; HR: hazard ratio; 95% CI: 95% confidence interval; Cs: Capillaries; ANA: anti-nuclear antibodies; ACA: anti-centromere antibodies; GC: giant capillaries Conclusion: Assessing the mean number of capillaries/mm and the total number of giant capillaries instead of avascular areas at videocapillaroscopy, resulted in improving the sensitivity and specificity of the score recently developed to predict the evolution of UCTD-risk-SSc into definite SSc. REFERENCES: [1]Valentini G. Autoimmun Rev 2015; [2]Valentini G. et al. Arthritis Care Res (Hoboken). 2014; [3]Riccardi A. et al. Autoimmun Rev. 2019; [4]Sambataro et al. Arthritis Research & Therapy 2014, 16:462. Disclosure of Interests: Antonella Riccardi: None declared, Antonella Marcoccia: None declared, SERENA FASANO: None declared, Tiziana Guastafierro: None declared, Rosaria Irace: None declared, Valentina Messiniti: None declared, Francesco Bondanini: None declared, Alessandro Sanduzzi: None declared, Marialuisa Bocchino: None declared, Aldo Ciani: None declared, Michele D’Alto: None declared, Paola Argiento: None declared, Giovanni Maria De Matteis: None declared, Alberto Spanò: None declared, Gabriele Valentini Grant/research support from: BMS, MSD, NOVARTIS, LILLY, PFIZER, ABBVIE, CELGENE Citation: Ann Rheum Dis, volume 79, supplement 1, year 2020, page 1111Session: Scleroderma, myositis and related syndromes (Poster Presentations)