PSY26 Is the Diagnostic Test Accuracy of an Automated Dsdna Test Aligned with the Criteria Included in the Recent SLE Classification Guidelines? an Updated Systematic Literature Review and Meta-Analysis

Abstract

The European League Against Rheumatism (EULAR) and the American College of Rheumatology (ACR) have recently updated the classification criteria for Systemic Lupus Erythematosus (SLE). This guideline states that the double-stranded-DNA (dsDNA) antibody test must have at least 90% specificity against relevant disease controls. Individual studies evaluating the diagnostic test accuracy of anti-dsDNA tests have been published. However, there is no systematic, up-to-date assessment of diagnostic test accuracy of anti-dsDNA assays in the diagnosis of SLE. The objective of our study was to investigate if a fully automated anti-dsDNA test (FEIA dsDNA) complies with the specificity requested in the new EULAR/ACR criteria. Electronic database searches (MEDLINE, EMBASE and Cochrane Library) supplemented by hand searching were conducted to identify cross-sectional or case-control studies reporting diagnostic test accuracy of FEIA dsDNA for SLE (2004-2019). Study quality was assessed using the QUADAS-2 checklist. The reference standard was established ACR or SLICC classification/diagnostic criteria. A hierarchical, bivariate, mixed-effect meta-analysis was conducted using the meqrlogit function in STATA MP v14.2. The systematic review identified six studies (1977 patients, 53% disease controls). The type of disease in the control groups varied across the studies although healthy patients were excluded. In all six studies, the point estimate of the specificity of FEIA dsDNA was above 90% and the meta-analysis estimated a specificity of 95% (95%CI: 92%-97%). A systematic literature review and meta-analysis was conducted to investigate whether the diagnostic performance of FEIA dsDNA concurs with the updated EULAR/ACR classification criteria for SLE. Based on a specificity estimate of 95%, FEIA dsDNA meets the 90% specificity threshold and is therefore suitable for the diagnosis and classification of SLE.