Multicenter Validation of the 2025 Classification Criteria for Axial Spondyloarthritis

Overview

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-diagnosis of axSpA, and alleviate the burden on the healthcare system.

This is a multicenter, observational, cross-sectional study conducted across 4 hospitals in China, led by the Department of Rheumatology and Immunology at Chinese PLA General Hospital (First Medical Center). Study Design: * Prospective enrollment of eligible patients over 12 months * No intervention; all diagnostic and treatment decisions are made by clinicians based on clinical judgment * Data collection through standardized electronic case report forms (eCRF) using EpiData platform Study Population: * Adults with chronic back pain (CBP) duration ≥3 months * Back pain onset age ≤45 years * Patients presenting to rheumatologists without confirmed diagnosis of axSpA, AS, or other rheumatic diseases * Patients willing to complete full diagnostic assessments and provide informed consent Assessments: * Clinical history and physical examination * Laboratory tests: complete blood count, liver and renal function, HLA-B27, ESR, CRP * Imaging: pelvic and whole-spine X-ray, sacroiliac joint MRI, sacroiliac joint CT; additional imaging (hip/spine MRI or CT, joint ultrasound, bone scan) as clinically indicated Diagnostic Evaluation: * Clinicians will establish a gold-standard diagnosis based on comprehensive clinical, laboratory, and imaging findings * Both 2025 ASAS-SPARTAN and 2009 ASAS classification criteria will be applied to each patient * Statistical analysis will evaluate sensitivity, specificity, and concordance between criteria Sample Size: 247 patients (calculated using PASS 2021 software for one-sample sensitivity and specificity confidence intervals, based on expected sensitivity 75%, specificity 90%, and prevalence 0.7) Statistical Methods: * Continuous variables: mean ± standard deviation, independent sample t-test * Categorical variables: relative frequencies, Chi-square test * Multivariate logistic regression and Cox regression for prognostic factor analysis * P \< 0.05 considered statistically significant Data Management: * Standardized eCRF with defined variable definitions and coding rules * Password-protected online data entry platform * De-identification of personal information for publication and data sharing * Compliance with GCP, Declaration of Helsinki, and Chinese regulatory requirements