Effects of anti-SSA antibodies on the response to methotrexate in rheumatoid arthritis: A retrospective multicenter observational study

Comparison of clinical response to methotrexate between anti-SSA antibody-positive and -negative patients with methotrexate-naïve rheumatoid arthritis and investigate the reasons for the differences in the response. For this multicenter retrospective cohort study, a total of 210 consecutive patients with rheumatoid arthritis who newly initiated methotrexate were recruited. The effects of anti-SSA antibody positivity on achieving a low disease activity according to the 28-joint Disease Activity Score based on C-reactive protein after 6 months of methotrexate administration were investigated using a logistic regression analysis. This study involved 32 and 178 anti-SSA antibody-positive and -negative patients, respectively. The rate of achieving low disease activity according to the 28-joint Disease Activity Score based on C-reactive protein at 6 months was significantly lower in the anti-SSA antibody-positive group than in the anti-SSA antibody-negative group (56.2% vs. 75.8%, P = 0.030). After 6 months, anti-SSA antibody-positive patients had significantly higher scores on the visual analogue scale (median [interquartile range]: 22 [15–41] vs. 19 [5–30], P = 0.038) and were frequently prescribed nonsteroidal anti-inflammatory drugs (37.5% vs. 18.0%, P = 0.018). In conclusion, the presence of anti-SSA antibodies might be a predictive factor for insufficient responses to treat-to-target strategy in rheumatoid arthritis. Residual pain might contribute to the reduced clinical response to methotrexate in anti-SSA antibody-positive patients with rheumatoid arthritis

Fast Track Algorithm: How To Differentiate A “Scleroderma Pattern” From A “Non-Scleroderma Pattern”

Objectives: This study was designed to propose a simple “Fast Track algorithm” for capillaroscopists of any level of experience to differentiate “scleroderma patterns” from “non-scleroderma patterns” on capillaroscopy and to assess its inter-rater reliability. Methods: Based on existing definitions to categorise capillaroscopic images as “scleroderma patterns” and taking into account the real life variability of capillaroscopic images described standardly according to the European League Against Rheumatism (EULAR) Study Group on Microcirculation in Rheumatic Diseases, a fast track decision tree, the “Fast Track algorithm” was created by the principal expert (VS) to facilitate swift categorisation of an image as “non-scleroderma pattern (category 1)” or “scleroderma pattern (category 2)”. Mean inter-rater reliability between all raters (experts/attendees) of the 8th EULAR course on capillaroscopy in Rheumatic Diseases (Genoa, 2018) and, as external validation, of the 8th European Scleroderma Trials and Research group (EUSTAR) course on systemic sclerosis (SSc) (Nijmegen, 2019) versus the principal expert, as well as reliability between the rater pairs themselves was assessed by mean Cohen's and Light's kappa coefficients. Results: Mean Cohen's kappa was 1/0.96 (95% CI 0.95-0.98) for the 6 experts/135 attendees of the 8th EULAR capillaroscopy course and 1/0.94 (95% CI 0.92-0.96) for the 3 experts/85 attendees of the 8th EUSTAR SSc course. Light's kappa was 1/0.92 at the 8th EULAR capillaroscopy course, and 1/0.87 at the 8th EUSTAR SSc course. C Conclusion: For the first time, a clinical expert based fast track decision algorithm has been developed to differentiate a “non-scleroderma” from a “scleroderma pattern” on capillaroscopic images, demonstrating excellent reliability when applied by capillaroscopists with varying levels of expertise versus the principal expert and corroborated with external validation.Wo