American College of Rheumatology classification criteria for Sjögren's syndrome: A data‐driven, expert consensus approach in the Sjögren's International Collaborative Clinical Alliance Cohort

Abstract

OBJECTIVE: We propose new classification criteria for Sjögren's syndrome (SS), which are needed considering the emergence of biologic agents as potential treatments and their associated comorbidity. These criteria target individuals with signs/symptoms suggestive of SS. METHODS: Criteria are based on expert opinion elicited using the nominal group technique and analyses of data from the Sjögren's International Collaborative Clinical Alliance. Preliminary criteria validation included comparisons with classifications based on the American–European Consensus Group (AECG) criteria, a model-based “gold standard”obtained from latent class analysis (LCA) of data from a range of diagnostic tests, and a comparison with cases and controls collected from sources external to the population used for criteria development. RESULTS: Validation results indicate high levels of sensitivity and specificity for the criteria. Case definition requires at least 2 of the following 3: 1) positive serum anti-SSA and/or anti-SSB or (positive rheumatoid factor and antinuclear antibody titer >1:320), 2) ocular staining score >3, or 3) presence of focal lymphocytic sialadenitis with a focus score >1 focus/4 mm2 in labial salivary gland biopsy samples. Observed agreement with the AECG criteria is high when these are applied using all objective tests. However, AECG classification based on allowable substitutions of symptoms for objective tests results in poor agreement with the proposed and LCA-derived classifications. CONCLUSION: These classification criteria developed from registry data collected using standardized measures are based on objective tests. Validation indicates improved classification performance relative to existing alternatives, making them more suitable for application in situations where misclassification may present health risks.