New Classification Criteria for Small‐Vessel Vasculitis: Is Antineutrophil Cytoplasmic Antibody Inclusion Their Major Advance?

Vasculitis is the generic term characterizing an inflammatory disease of the blood vessels that affects arteries and veins of different types, sizes, and histologies. Clinical manifestations can be relatively specific for a single vasculitic entity (e.g., anterior ischemic optic neuropathy for giant cell arteritis) or common to several vasculitides (e.g., pauci-immune glomerulonephritis). Most vasculitides are primary, but some develop secondary to viral infections, malignancies, genetic abnormalities, other autoimmune diseases, or drugs. Therefore, classifications, nomenclatures, and diagnostic criteria are needed to facilitate their description and distinction, and foster academic studies among clinicians and researchers all over the world (1–3). In this issue of Arthritis & Rheumatology, the 2022 American College of Rheumatology (ACR)/European Alliance of Associations for Rheumatology (EULAR) classification criteria for granulomatosis with polyangiitis (GPA) (4), microscopic polyangiitis (MPA) (5), and eosinophilic granulomatosis with polyangiitis (EGPA) (6) are presented. They are based on the analysis of the most ambitious prospective cohort study ever on vasculitis, the Diagnostic and Classification Criteria in Vasculitis (DCVAS) project, involving almost 7,000 patients from 136 sites worldwide. The methodology for the development of criteria was robust, including a mixture of a data-driven approach to derive and weight the individual items of the criteria, expert opinion, and final validation. According to the new criteria, a patient can only be classified as having a specific entity if 2 requirements are fulfilled: 1) an established diagnosis of smallor medium-vessel vasculitis and 2) the exclusion of vasculitis mimics. Weighted parameters are then combined to obtain a final score, with cutoffs of 5 points for GPA and MPA, and 6 points for EGPA. The new criteria outperformed the 1990 ACR classification criteria for GPA and EGPA (2,3) with regard to sensitivity and specificity using the DCVAS data set, whereas for MPA, no previous criteria had been available. Unlike the version preceding the 1990 ACR vasculitis criteria and the Chapel Hill Consensus Conference nomenclature (1), these new classification criteria focus predominantly on vasculitides characterized by their belonging to the antineutrophil cytoplasmic antibody (ANCA)–associated small-vessel vasculitis group. A major question is how the 2022 ACR/EULAR classification criteria will be used in real life. The purpose of classification is to distinguish GPA, MPA, and EGPA from one another and from other forms of vasculitis and mimics of vasculitis. Classification criteria are designed for drug trials and other academic studies. However, it is highly likely that clinicians will also use them to guide their clinical and therapeutic decisions, and probably also misuse them for diagnostic purposes, like earlier classification criteria. It is clear that diagnoses of patients included in the DCVAS cohort were largely based on the detection of ANCAs and, more specifically, antimyeloperoxidase (anti-MPO) and anti–proteinase 3 (antiPR3). As a consequence, the criteria of ANCA detection and type outweighed the other (diagnostically relevant) typical characteristics of small-vessel vasculitis, such as certain clinical manifestations (e.g., constitutional symptoms or skin lesions) or histologically confirmed pauci-immune glomerulonephritis, which are either not included among the new classification criteria or were accorded relatively low weights. Patients with ANCA-negative limited GPA, for example, would hardly fulfill the new classification criteria and therefore be missed if the criteria were (mis)used for diagnostic purposes (4). The main objective of the experts developing the 2022 ACR/EULAR classification criteria seemed to be distinguishing among GPA, MPA, and EGPA, given the high number of cases selected as comparators, in order to derive the individual parameters and their weights by statistical means. Regarding the