Re-evaluation of 129 patients with systemic necrotizing vasculitides by using classification algorithm according to consensus methodology.

Recently, a new classification algorithm (CA) for systemic necrotizing vasculitides was proposed by Watts et al. (Annals Rheum Dis 66:222-227, 2007) by using the American College of Rheumatology (ACR), Chapel Hill Consensus Criteria (CHCC) and Sorensen surrogate markers (So). We aimed to validate CA in our patients. One hundred twenty-nine patients followed up in our vasculitis clinic were reclassified according to CA in different categories (ACR or Lanham criteria in "1" for Churg-Strauss Syndrome (CSS); ACR in "2a"; CHCC-Wegener's granulomatosis (WG) in "2b"; CHCC-microscopic polyangiitis (MPA), So-WG in "2c"; So-WG, proteinase 3 (PR3) or myeloperoxidase antineutrophil cytoplasmic antibody (MPO ANCA) serology in "2d" for WG; clinical features and histology compatible with small vessel vasculitis without So-WG in "3a"; So-MPA, PR3 or MPO ANCA serology in "3b" for MPA; CHCC-classic-polyarteritis nodosa (c-PAN) or typical angiographic features in "4" for c-PAN; unclassifiable in "5"). Kappa statistic was used to analyse the agreement of the criteria that formed the algorithm. All of 12 CSS, 91% of 69 WG, 78% of 18 MPA and 93% of 26 c-PAN patients remained in their previous diagnosis. WG patients were placed in 2a (83%), 2c (3%), 2d (14%) categories. Four WG (6%) and four MPA (22%) patients were categorized as MPA (in 3a (75%), 3b (25%)) and WG (in 2c (75%), 2d (25%)), respectively. Three of four unclassified patients could be classified as c-PAN (two) and MPA (one). Significant agreement was demonstrated only for ACR and So criteria in WG (κ = 0.62, p < 0.001). The majority of our patients stayed on their previous diagnosis in "CA". Our findings suggest that this algorithm is helpful and practical for epidemiological studies. Poor correlation of defined criteria was thought to be related to the fact that each criteria mainly consist of different characteristics of vasculitides such as clinical, histopathological and serological features.