Diagnostic algorithm for antineutrophil cytoplasmic antibody-associated systemic vasculitis.

Abstract

Antineutrophil cytoplasm antibody (ANCA)-associated vasculitis (AAV) are rare autoimmune disorders and characterized by severe multiple organ lesions with a potential fatal outcome. AAV comprises granulomatosis with polyangiitis (GPA), microscopic polyangiitis (MPA) and eosinophilic granulomatosis with polyangiitis (EGPA). Early diagnosis and treatment can significantly improve the AAV prognosis, but there are can be difficult, largely due to the lack of criteria for the classification MPA, whose main difference is the absence of granulomatous inflammation. The presented paper deals with the results of the analysis of 251 patients with AAV (mean age 43.1 ± 15.9 years, men 40%, disease duration 3 (0,2-28,5) years, ANCA 100%), based on which the diagnostic algorithm was developed. The algorithm steps include classification criteria of EGPA as well as surrogate markers for granulomatous inflammation (SG) and vasculitis (SV). MPA confirmed by the absence of criteria for EGPA, the presence of SV and the absence of SG. Due to the algorithm usage, nosological affiliation of AAV was determined in 99% patients. Both GPA and MPA were the most common (53% and 37%), while EGPA was rare (9%). In MPA group the overall mortality was higher (18%) than GPA and EGPA (7-5%), p=0.003. In MPA with anti- proteinase 3 antibody the two-year survival rate was lower than those with anti-myeloperoxidase antibody (p=0.04), mainly because of the high risk for alveolar hemorrhage and rapidly progressive glomerulonephritis. Relapses occurred more frequently in EGPA (80%) and in GPA (64%) and less frequently in MPA (49%). The group differences confirm diagnostic value of the algorithm. In conclusion, the proposed algorithm will help to improve the diagnosis of AAV. It is important that crucial in the AAV diagnosis belongs focused and systematic clinical examination of patients.