4.2 Article

Influence of anticardiolipin and anti-β2 glycoprotein I antibody cutoff values on antiphospholipid syndrome classification

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出版社

WILEY
DOI: 10.1002/rth2.12207

关键词

antiphospholipid antibodies; clinical laboratory testing; immunoassay; reference values; thrombosis

资金

  1. Werfen/Inova Diagnostics
  2. Werfen/Instrumentation Laboratory
  3. Bio-Rad Laboratories
  4. Thermo Fisher Scientific/Phadia

向作者/读者索取更多资源

Background: Anticardiolipin (aCL) and anti-beta 2 glycoprotein I (a beta 2GPI) immunoglobulin (Ig) G/IgM antibodies are 2 of the 3 laboratory criteria for classification of antiphospholipid syndrome (APS). The threshold for clinically relevant levels of antiphospholipid antibodies (aPL) for the diagnosis of APS remains a matter of debate. The aim of this study was to evaluate the variation in cutoffs as determined in different clinical laboratories based on the results of a questionnaire as well as to determine the optimal method for cutoff establishment based on a clinical approach. Methods: The study included samples from 114 patients with thrombotic APS, 138 patients with non-APS thrombosis, 138 patients with autoimmune disease, and 183 healthy controls. aCL and a beta 2GPI IgG/IgM antibodies were measured at 1 laboratory using 4 commercial assays. Assay-specific cutoff values for aPL were obtained by determining 95th and 99th percentiles of 120 compared to 200 normal controls by different statistical methods. Results: Normal reference value data showed a nonparametric distribution. Higher cutoff values were found when calculated as 99th rather than 95th percentiles. These values also showed a stronger association with thrombosis. The use of 99th percentile cutoffs reduced the chance of false positivity but at the same time reduced sensitivity. The decrease in sensitivity was higher than the gain in specificity when 99th percentiles were calculated by methods wherein no outliers were eliminated. Conclusions: We present cutoff values for aPL determined by different statistical methods. The 99th percentile cutoff value seemed more specific. However, our findings indicate the need for standardized statistical criteria to calculate 99th percentile cutoff reference values.

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