Validation of the consensus methodology algorithm for the classification of systemic necrotizing vasculitis in Indian patients

• Published in: International journal of rheumatic diseases Vol. 17; no. 4; pp. 408 - 411
• Main Authors: Sharma, Aman, Mittal, Tarun, Rajan, Roopa, Rathi, Manish, Nada, Ritambhra, Minz, Ranjana W., Joshi, Kusum, Sakhuja, Vinay, Singh, Surjit
• Format: Journal Article
• Language: English
• Published: England Blackwell Publishing Ltd 01.05.2014; Wiley Subscription Services, Inc
• Subjects: Algorithms; Churg-Strauss Syndrome - classification; Churg-Strauss Syndrome - diagnosis; Churg-Strauss Syndrome - epidemiology; Classification; classification criteria; Consensus; consensus methodology algorithm; diagnostic criteria; Diagnostic Errors - prevention & control; Granulomatosis with Polyangiitis - classification; Granulomatosis with Polyangiitis - diagnosis; Granulomatosis with Polyangiitis - epidemiology; Humans; India - epidemiology; Indian; Microscopic Polyangiitis - classification; Microscopic Polyangiitis - diagnosis; Microscopic Polyangiitis - epidemiology; Polyarteritis Nodosa - classification; Polyarteritis Nodosa - diagnosis; Polyarteritis Nodosa - epidemiology; Predictive Value of Tests; Reproducibility of Results; Systemic Vasculitis - classification; Systemic Vasculitis - diagnosis; Systemic Vasculitis - epidemiology; Terminology as Topic; vasculitis; India; Indian; diagnostic criteria; classification criteria; consensus methodology algorithm; vasculitis
• ISSN: 1756-1841; 1756-185X; 1756-185X
• DOI: 10.1111/1756-185X.12219

Aim Many patients with systemic necrotizing vasculitis (SNV) satisfy classification criteria of different disease entities when different classification systems are used. A new classification algorithm has been proposed recently by using the American College of Rheumatology criteria, Chapel Hill Consensus Criteria (CHCC) and Sorensen surrogate markers for a more uniform classification of patients suffering from these rare disorders. Methods We applied this algorithm to patients diagnosed as having systemic vasculitis between 2007 and 2011. We also analyzed the data using this algorithm by incorporating the recently proposed revised CHCC nomenclature of vasculitis in place of the older criteria. Results Seventy‐nine patients with SNV were studied. One patient diagnosed as microscopic polyangiitis (MPA) had to be excluded from analysis as she had previously been diagnosed as having Behcet's disease. All patients of eosinophilic granulomatosis with polyangiitis (EGPA), granulomatosis with polyangiitis (GPA) and MPA were reclassified to the same diagnostic subcategory after application of the algorithm. Three (16.7%) of 18 polyarteritis nodosa patients were unclassifiable after application of the consensus algorithm while two (11.1%) were reclassified as MPA. All previously unclassifiable patients could be classified either as MPA or GPA after application of the new algorithm. There was no difference in the results when the CHCC 2012 nomenclature was used instead of the older CHCC in the consensus algorithm. Conclusion The new classification algorithm is a reliable method for classification of SNV for epidemiological purposes in our population.