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Related Experiment Video

Updated: Aug 16, 2025

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[The analysis to data from Chinese Rheumatism Data Center external quality assurance program for autoantibodies in

Y N Bai1, C W Deng1, N Song1

  • 1Department of Rheumatology and Clinical Immunology, Chinese Academy of Medical Sciences & Peking Union Medical College, National Clinical Research Center for Dermatologic and Immunologic Diseases, Ministry of Science & Technology, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Key Laboratory of Rheumatology and Clinical Immunology, Ministry of Education, Beijing 100730, China.

Zhonghua Yu Fang Yi Xue Za Zhi [Chinese Journal of Preventive Medicine]
|December 20, 2022
PubMed
Summary

External quality assurance for autoantibody detection in China shows high consensus in qualitative results but variations in quantitative measures. Differences were noted in positivity grades and manufacturer-based coefficients of variation, impacting lab testing consistency.

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Area of Science:

  • Rheumatology and Immunology
  • Clinical Laboratory Science
  • Diagnostic Accuracy

Context:

  • External Quality Assurance Programs (EQAP) are crucial for standardizing laboratory testing.
  • Autoantibody detection is vital for diagnosing autoimmune rheumatic diseases.
  • The Chinese Rheumatism Data Center (CRDC-QAP) initiated a program to assess autoantibody testing quality in China.

Purpose:

  • To evaluate the 2021 CRDC-QAP data on autoantibody detection.
  • To assess cross-laboratory consensus and identify differences in autoantibody testing across China.
  • To analyze both qualitative and quantitative aspects of autoantibody measurements.

Summary:

  • A retrospective analysis of the 2021 CRDC-QAP autoantibody detection program involved 303 and 332 clinical laboratories.
  • High cross-laboratory consensus (>96%) was observed for qualitative autoantibody results, except for anti-β2 glycoprotein type I (aβ2-GPI) IgM.
  • Quantitative analysis revealed variations in positivity grades (S/CO ratio) and manufacturer-based coefficients of variation (CV), with P<0.01 for differences.

Impact:

  • Identifies areas for improvement in quantitative autoantibody testing standardization.
  • Highlights the need for addressing inter-laboratory variability in diagnostic assays.
  • Provides data to enhance the reliability and comparability of autoantibody test results across different laboratories in China.