Assuntos
Alérgenos/imunologia , Dessensibilização Imunológica , Doença Relacionada a Imunoglobulina G4/imunologia , Doença Relacionada a Imunoglobulina G4/terapia , Alérgenos/administração & dosagem , Dessensibilização Imunológica/métodos , Gerenciamento Clínico , Suscetibilidade a Doenças , Humanos , Doença Relacionada a Imunoglobulina G4/diagnóstico , Avaliação de SintomasRESUMO
BACKGROUND: The 2019 ACR/EULAR Classification Criteria for IgG4-related disease (IgG4-RD) represent a fundamental tool for patient enrollment in research studies and in clinical trials but their usefulness in daily clinical practice remains unknown. OBJECTIVE: To validate the 2019 ACR/EULAR Classification Criteria for IgG4-RD in a real-life setting and to anticipate their utility for orienting disease diagnosis and patient management. METHODS: Four experts were asked to classify 200 patients diagnosed with IgG4-RD according to the 2019 ACR/EULAR Classification Criteria for IgG4-RD. Agreement between experts was calculated and the Classification score of each patient was correlated with the following variables and outcomes: serum IgG4 and IgE; inflammatory markers; eosinophils; plasmablasts; IgG4-RD responder index; diabetes, osteoporosis, relapses; and use of rituximab. RESULTS: Among the 157/200 cases equally rated by at least three experts, 94 (59.9%) achieved IgG4-RD classification and 63 (40.1%) did not. Strong agreement among IgG4-RD experts was observed in classifying patients (k = 0.711, p<0.0001). Clinical presentations not included in the classification algorithm and lack of informative histology were the most common reasons for not achieving classification. In patients achieving classification, the Classification score did not correlate with variables of disease activity and was not associated with specific outcomes. CONCLUSIONS: The ACR/EULAR Classification Criteria represent a replicable instrument for classifying patients and a useful framework for orienting diagnosis but are of limited utility for assessing IgG4-RD activity, for predicting disease outcomes, and for defining personalized therapeutic approaches.