BAFF System in Rheumatoid Arthritis: from Pathobiology to Therapeutic Targets

Recent advances in understanding the multifaceted pathobiology of rheumatoid arthritis have highlighted the pivotal role and continuing crosstalk between activated immune cells, pro-inflammatory cytokines, and matrix-degrading mediators, promoting chronic inflammation as well as irreversible tissue damage within an autoimmune background. B cells are widely recognized as leading players in immune-mediated pathology based on their ability to produce not only different patterns of autoantibodies and driving cytokine synthesis but also as independent antigen-presenting cells and by modulating the specific activation of T cells. Overwhelming evidence emphasized the role of BAFF, a B-cell-activating factor, and BAFF receptors (TACI, BCMA, BAFF-R) in promoting B-cell homeostasis, proliferation, and survival under normal and autoimmune systemic disorders. We systematically reviewed data from literature focusing on BAFF, its homolog molecule APRIL, and BAFF-binding receptors biology, dysregulation of BAFF/BAFF receptor signaling in autoimmune settings, and current status of targeting BAFF/BAFF receptor pathway for 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