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1.
  • Elkhalifa, Marwa, et al. (author)
  • Anti-beta 2 glycoprotein I IgA in the SLICC classification criteria dataset
  • 2021
  • In: Lupus. - : SAGE Publications. - 0961-2033 .- 1477-0962. ; 30:8, s. 1283-1288
  • Journal article (peer-reviewed)abstract
    • Objective: Anti-beta 2 glycoprotein I IgA is a common isotype of anti-beta 2 glycoprotein I in SLE. Anti-beta 2 glycoprotein I was not included in the American College of Rheumatology (ACR) SLE classification criteria, but was included in the Systemic Lupus International Collaborating Clinics (SLICC) criteria. We aimed to evaluate the prevalence of anti-beta 2-glycoprotein I IgA in SLE versus other rheumatic diseases. In addition, we examined the association between anti-beta 2 glycoprotein I IgA and disease manifestations in SLE. Methods: The dataset consisted of 1384 patients, 657 with a consensus physician diagnosis of SLE and 727 controls with other rheumatic diseases. Anti-beta 2 glycoprotein I isotypes were measured by ELISA. Patients with a consensus diagnosis of SLE were compared to controls with respect to presence of anti-beta 2 glycoprotein I. Among patients with SLE, we assessed the association between anti-beta 2 glycoprotein I IgA and clinical manifestations. Results: The prevalence of anti-beta 2 glycoprotein I IgA was 14% in SLE patients and 7% in rheumatic disease controls (odds ratio, OR 2.3, 95% CI: 1.6, 3.3). It was more common in SLE patients who were younger patients and of African descent (p = 0.019). Eleven percent of SLE patients had anti-beta 2 glycoprotein I IgA alone (no anti-beta 2 glycoprotein I IgG or IgM). There was a significant association between anti-beta 2 glycoprotein I IgA and anti-dsDNA (p = 0.001) and the other antiphospholipid antibodies (p = 0.0004). There was no significant correlation of anti-beta 2 glycoprotein I IgA with any of the other ACR or SLICC clinical criteria for SLE. Those with anti-beta 2 glycoprotein I IgA tended to have a history of thrombosis (12% vs 6%, p = 0.071), but the difference was not statistically significant. Conclusion: We found the anti-beta 2 glycoprotein I IgA isotype to be more common in patients with SLE and in particular, with African descent. It could occur alone without other isotypes.
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2.
  • Petri, Michelle, et al. (author)
  • Comparison of the 2019 European Alliance of Associations for Rheumatology/American College of Rheumatology Systemic Lupus Erythematosus Classification Criteria With Two Sets of Earlier Systemic Lupus Erythematosus Classification Criteria
  • 2021
  • In: Arthritis Care and Research. - : Wiley. - 2151-464X .- 2151-4658. ; 73:9, s. 1231-1235
  • Journal article (peer-reviewed)abstract
    • Objective: The Systemic Lupus International Collaborating Clinics (SLICC) 2012 systemic lupus erythematosus (SLE) classification criteria and the revised American College of Rheumatology (ACR) 1997 criteria are list based, counting each SLE manifestation equally. We derived a classification rule based on giving variable weights to the SLICC criteria and compared its performance to the revised ACR 1997, the unweighted SLICC 2012, and the newly reported European Alliance of Associations for Rheumatology (EULAR)/ACR 2019 criteria sets. Methods: The physician-rated patient scenarios used to develop the SLICC 2012 classification criteria were reemployed to devise a new weighted classification rule using multiple linear regression. The performance of the rule was evaluated on an independent set of expert-diagnosed patient scenarios and compared to the performance of the previously reported classification rules. Results: The weighted SLICC criteria and the EULAR/ACR 2019 criteria had less sensitivity but better specificity compared to the list-based revised ACR 1997 and SLICC 2012 classification criteria. There were no statistically significant differences between any pair of rules with respect to overall agreement with the physician diagnosis. Conclusion: The 2 new weighted classification rules did not perform better than the existing list-based rules in terms of overall agreement on a data set originally generated to assess the SLICC criteria. Given the added complexity of summing weights, researchers may prefer the unweighted SLICC criteria. However, the performance of a classification rule will always depend on the populations from which the cases and non-cases are derived and whether the goal is to prioritize sensitivity or specificity.
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