Multicenter Validation of the 2025 Classification Criteria for Axial Spondyloarthritis

This study aims to validate the 2025 ASAS-SPARTAN revised classification criteria for axial spondyloarthritis (axSpA) in the Chinese population through a multicenter, prospective, cross-sectional observational study. Axial spondyloarthritis is a chronic inflammatory disease primarily affecting the spine and sacroiliac joints, causing back pain and stiffness. Early and accurate diagnosis is essential for timely treatment and improved patient outcomes. The 2025 ASAS-SPARTAN revised classification criteria were recently developed by the Assessment of SpondyloArthritis International Society (ASAS) and the SpondyloArthritis Research and Treatment Network (SPARTAN) to improve diagnostic accuracy and reduce over-diagnosis, with preset targets of sensitivity ≥75% and specificity ≥90%. However, the original validation study included only 71 Chinese patients out of 1,015 total participants, and racial differences in susceptibility genes, living environments, and socioeconomic-cultural backgrounds may affect the criteria's performance in Chinese patients. This study will enroll patients with chronic back pain (CBP) lasting ≥3 months and onset age ≤45 years from multiple hospitals in China. All participants will undergo comprehensive diagnostic assessments including clinical history, physical examination, CRP testing, HLA-B27 testing, pelvic X-ray, and sacroiliac joint MRI. The 2025 ASAS-SPARTAN criteria will be applied to evaluate diagnostic performance, and results will be compared with the 2009 ASAS classification criteria and clinicians' gold-standard diagnoses. The primary objective is to validate the sensitivity, specificity, and internal scoring rationality of the 2025 ASAS-SPARTAN criteria in Chinese axSpA patients. The secondary objective is to assess the concordance between the 2025 and 2009 ASAS criteria and analyze reasons for any discrepancies. The findings will provide evidence for Chinese clinicians to select appropriate classification tools, reduce over-diag