The Prevalence of Atopy in Biologically Treated Spondyloarthropathies: A Retrospective Study of 200 Patients

(1) Background: Recent data shed light on the association between atopic disorders (ADs) (atopic dermatitis, allergic asthma, allergic rhinitis) and spondyloarthropathies (SpAs), underpinning the critical role of T helper (Th)1-Th17/Th2-T regulatory cells disbalance. We evaluated the prevalence of AD in axial SpAs (axSpAs) and psoriatic arthritis (PsA) and explored the potential association between atopic status, disease-related parameters, and biological therapy. (2) Methods: A monocentric, retrospective study was conducted that enrolled 200 patients taking biologics. Demographics, disease, and drug-related variables, along with a screening questionnaire focused on Ads, were systematically collected. (3) Results: Overall, 51 patients (25.5%) had atopy—namely, 24.4% of axSpA and 28% of PsA, with a higher frequency of rhinitis (43%) vs. atopic dermatitis (37.2%) or asthma (21.5%). We failed to demonstrate any statistically significant difference in demographics, SpA-related parameters excepting concomitant inflammatory bowel disease, and biologic drug exposure in patients with and without atopy (p > 0.05). However, significantly more non-atopic patients need only one TNF inhibitor (54%) vs. atopic patients (28%) (p < 0.05) to control active SpA. (4) Conclusions: We successfully demonstrated that AD is associated with one out of four SpA. Irrespective of the SpA subtype, atopic patients require more frequent switching among biologics, as significantly more non-atopic patients remain on their first anti-TNF

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