FRI0218 Validation of the consensus methodology algorithm for the classification of systemic necrotizing vasculitis. (23rd January 2014)

• Record Type: Journal Article
• Authors: Sharma, A.; Mittal, T.; Rathi, M.; Minz, R.; Singh, S.
• Is Part Of: Annals of the rheumatic diseases. Volume 71(2012)Supplement 3
• Page Start: 387
• Page End: 388
• Publication Date: 2014-01-23
• Subjects: Rheumatism -- Periodicals; 616.723005
• DOI: 10.1136/annrheumdis-2012-eular.2675
• Languages: English
• ISSNs: 0003-4967

Abstract

Abstract : Background: The current classification of systemic necrotizing vasculitis (SNV) is confusing as many patients satisfy criteria for different diseases in different classification systems. Recently, a new classification algorithm was proposed by Watts et al 1 by using the American College of Rheumatology (ACR), Chapel Hill Consensus Criteria (CHCC) and Sorensen surrogate markers (So) for a more uniform classification of patients suffering from these rare disorders. Objectives: The algorithm uses a stepwise approach for individual patient diagnosis and prioritizes individual criteria as per previous validation. In the present study, we have attempted to re-analyze patients of SNV seen at our center using the consensus methodology algorithm. Methods: All patients of primary systemic necrotizing vasculitis who presented to the rheumatology clinic at our center between Jan 2007 and Jun 2011 were included in the study. Results: Seventy nine patients of SNV were studied (see Table 1 ). One patient diagnosed as MPA had to be excluded from analysis as she had previously been diagnosed to have Behcet's disease. All patients of CSS, WG and MPA were reclassified to the same diagnostic subcategory after application of the algorithm. Four (22%) of 18 PAN patients were unclassifiable after application of the consensus algorithm while 1 was reclassified as MPA. All previously unclassifiable patients could be classified either as MPA or WG after application of the new algorithm. Conclusions: We conclude that the new classification algorithm is a reliable method for classification of SNV for epidemiological purposes References: Watts R, Lane S, Hanslik T et al. Ann Rheum Dis 2007;66:222-227 Disclosure of Interest: None Declared