[ACR22] Spondyloarthritis I – Non-therapeutic

Author: Jean-Guillaume Letarouilly

Sieiro Santos  et al. (0373) developed a prognostic outcome score for patients with uveitis associated with SpA (SpA-U) and determine factors associated with adverse outcomes in uveitis associated to SpA-U. Smoking history, disease activity, HLA B27, axial and peripheral involvement and female sex were associated with more severe uveitis. 

Benavent et al. (0381) investigate the influence of gender on disease outcomes in 4,185patients with SpA, including axSpA, pSpA and PsA from the ASAS-PerSpA study. ASDAS was not associated with gender in axSpA (β=0.02; 95%CI -0.07, 0.11). These results suggest that ASDAS should be preferred in clinical practice both for females and males with axSpA.

Proft et al (0383) evaluated the performance of a trained artificial network in a cohort of patients previously evaluated as radiographic axSpA or non-radiographic axSpA by central readers. The neural network achieved an 0.89 (95% CI: 0.86, 0.93) positive predictive value (PPV) and a 0.70 (95% CI: 0.64, 0.77) negative one (NPV) in recognition of definite radiographic sacroiliitis with AUROC of 0.88.

Rauber et al. (1602) showed that Fibroblast Activation Protein (FAP) tracer-based PET-CT (68Ga-labelled FAP inhibitor [68Ga-FAPI-04]) correlated with DAPSA score. Increased FAPI uptake at baseline was associated with progression of joint damage 3-6 months later as assessed by PsAMRIS score.

Tilett et al. (1613) performed a nested matched cohort study from the 2018 National Early Inflammatory Arthritis Audit in England and Wales showed that PsA patients had a longer duration of symptoms prior to referral than patients with RA (P< 0.001). Fewer DMARDs were prescribed in PsA than RA at baseline (54.0% vs 69.0%; p< 0.001).

Poddubnyy  et al. (2254) assessed a deep learning framework for the detection of active inflammatory and structural changes indicative of axSpA on MRI of SI joints. MRIs of SI joints from 477 patients from 4 cohorts (comprising 266 patients with and 211 without axSpA) were used to develop a deep learning framework. MRIs from the ASAS cohort (n=116) were used as independent testing. The AUC was 0.89 (0.81−0.96) with an accuracy of 79%; the sensitivity and specificity were 85% and 78%, respectively. Overall, the model performed close to the individual human experts.

Sunzini et al. (2256) investigated objective neurobiological markers of nociplastic pain in PsA. PsA patients with higher fibromyalgia scores displayed increased functional brain connectivity between the middle-posterior insular cortices (IC) (right more than left) and brain areas involved in sensory (thalamus), learning/affective (parahippocampal gyrus), and cognitive (prefrontal cortex) pain modulation connectivity.

Poddubnyy et al. (1162) investigated the gut microbiota changes in patients with axSpA after receiving one year of treatment with bDMARDs (97.9% TNFi) compared to healthy controls. A qualitative normalization to healthy individuals after treatment  Increase in Prevotella and decrease in Bacteroides were strongly correlated with the change in ASDAS after one year. The unique enrichment of Collinsella in axSpA patients remained stable across time and treatment, suggesting it may be a disease biomarker.

About the Author

Jean-Guillaume Letarouilly


Jean-Guillaume is a fellow in the department of rheumatology at Lille University Hospital, Lille, France. He is also doing a PhD student in the MABLab at Lille University focused on the effect of tofacitinib on adipose and bone tissues in rheumatoid arthritis. Aside from his PhD, his major interests are spondyloarthritis and the crosstalk between spondyloarthritis, psoriasis and inflammatory bowel diseases. Jean-Guillaume is a member of the Social Media Sub-Committee.

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