OMERACT 2023 Systemic Lupus Erythematosus Special Interest Group: Winnowing and Binning Preliminary Candidate Domains for the Core Outcome Set.

BACKGROUND: The Outcome Measures in Rheumatology (OMERACT) Systemic Lupus Erythematosus (SLE) Working Group held a Special Interest Group (SIG) at the OMERACT 2023 conference in Colorado Springs where SLE collaborators reviewed domain sub-themes generated through qualitative research and literature review. OBJECTIVE: The objective of the SIG and the subsequent meetings of the SLE Working Group was to begin the winnowing and binning of candidate domain sub-themes into a preliminary list of candidate domains that will proceed to the consensus Delphi exercise for the SLE COS. METHODS: Four breakout groups at the SLE SIG in Colorado Springs winnowed and binned 132 domain sub-themes into candidate domains, which was continued with a series of virtual meetings by an advisory group of SLE patient research partners (PRPs), members of the OMERACT SLE Working Group Steering Committee, and other collaborators. RESULTS: The 132 domain sub-themes were reduced to a preliminary list of 20 candidate domains based on their clinical and research relevance for clinical trials and research studies. CONCLUSION: A meaningful and substantial winnowing and binning of candidate domains for the SLE COS was achieved resulting in a preliminary list of 20 candidate domains.

Computer-Aided Assessment of Spinal Inflammation on Magnetic Resonance Images in Patients With Spondyloarthritis.

OBJECTIVE: To evaluate a computer-aided approach to the assessment of spinal inflammation on magnetic resonance imaging (MRI) in spondyloarthritis as compared to visual assessment. METHODS: Following institutional ethics approval, 32 patients (mean ± SD age 35.3 ± 10.2 years) with active ankylosing spondylitis underwent treatment with methotrexate and infliximab for 30 weeks. Spinal MRI examination (T1-weighted, T2-weighted fat-suppressed, and postcontrast T1-weighted fat-suppressed sagittal sequences using a 1.5T MRI system) was performed at baseline and at 30 weeks. Following manual identification of the vertebral corners, vertebral body segmentation was performed using a deformable model that automatically isolated the 4 vertebral corner areas, allowing automatic measurement of the relative mean corner intensity of each vertebral corner before and after treatment. Quantitative computer-aided assessment of spinal inflammation was compared with a semiquantitative visual assessment of spinal inflammation (the Berlin method). RESULTS: Computer-aided quantification was quick and highly reliable, and it identified increases in vertebral corner edema or enhancement that were significantly decreased following treatment (P < 0.5). For computer-aided analysis, there was excellent inter- and intrarater correlation of both corner edema and enhancement (intraclass correlation coefficients [ICCs] >0.99), and the correlations were better than those for visual analysis (ICCs 0.83-0.96). For computer-aided analysis, the standardized response mean was 1.67 for corner edema and 1.64 for enhancement, as compared to 1.20 and 1.18, respectively, for visual analysis. Computer-aided quantification of MRI data correlated better (r = 0.50-0.53, P < 0.01) with clinical features of spinal disease activity pre- and posttreatment than did visual analysis of spinal inflammation (r = 0.37-0.43, P > 0.02). CONCLUSION: Computer-aided assessment of spinal inflammation in spondyloarthritis is quick, reliable, and sensitive and correlates better with clinical disease activity than does visual assessment by the Berlin method.