Harmonization of anti-nuclear antibody testing (ANA) by indirect immunofluorescence assay: Results from ten years of UK NEQAS external quality assessment.

IF 3.2 3区 医学 Q2 MEDICAL LABORATORY TECHNOLOGY
Maria Infantino, Teresa Carbone, Dina Patel, Ravishankar Sargur, Carol Stanley, Amina Bhayat-Cammack, Emirena Garrafa, Silvia Pancani, Mariangela Manfredi, Luis E C Andrade, Nicola Bizzaro
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引用次数: 0

Abstract

External quality assurance (EQA) programs play a pivotal role in monitoring laboratory practices, allowing each laboratory to evaluate the consistency of results across different methods as well the ability of individual laboratories to compare and improve over time their own performance. The objective of our study was to analyze the UK NEQAS EQA reports for the "Antibodies to Nuclear and Related Antigens" program from 2013 to 2023, to assess the overall level of harmonization of the responses for anti-nuclear antibody (ANA) testing by indirect immunofluorescence (IIF), in terms of both pattern and titer consensus. As a second aim, we analyzed the impact of the introduction in UK NEQAS EQA reports of the International Consensus on ANA Patterns (ICAP) nomenclature and of digital image recognition on the harmonization of the ANA HEp-2 IIF test. The percentage of consensus for positive/negative results was significantly higher (90.9 ± 1.4) in 2023 than in 2013 (64.0 ± 7.8, p < 0.001). Common to all years in the investigated period, consensus on pattern recognition was significantly lower for the homogenous pattern (70.5 ± 16.0) compared to the centromere (84.9 ± 14.9), the speckled (90.3 ± 12.3), and the negative (84.5 ± 18.6, p < 0.001) samples, while it was significantly higher for titers 1:80-1:320 than for titers > 1:320 (p < 0.001). The difference between manual reading and digital reading was not significant (93.8 % vs. 92.4 %; p = 0.078), but it was significant between the pre- and post-use of the ICAP nomenclature (82.6 % vs. 93.8 %; p < 0.001). This study shows that the variability in ANA recognition and reporting is pattern (homogeneous > speckled > centromere) and titer (high titer > low titer) dependent. While we did not find any difference between the use of manual reading compared to digital reading, the adoption of the ICAP nomenclature greatly improved the harmonization of ANA reporting.

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来源期刊
Clinica Chimica Acta
Clinica Chimica Acta 医学-医学实验技术
CiteScore
10.10
自引率
2.00%
发文量
1268
审稿时长
23 days
期刊介绍: The Official Journal of the International Federation of Clinical Chemistry and Laboratory Medicine (IFCC) Clinica Chimica Acta is a high-quality journal which publishes original Research Communications in the field of clinical chemistry and laboratory medicine, defined as the diagnostic application of chemistry, biochemistry, immunochemistry, biochemical aspects of hematology, toxicology, and molecular biology to the study of human disease in body fluids and cells. The objective of the journal is to publish novel information leading to a better understanding of biological mechanisms of human diseases, their prevention, diagnosis, and patient management. Reports of an applied clinical character are also welcome. Papers concerned with normal metabolic processes or with constituents of normal cells or body fluids, such as reports of experimental or clinical studies in animals, are only considered when they are clearly and directly relevant to human disease. Evaluation of commercial products have a low priority for publication, unless they are novel or represent a technological breakthrough. Studies dealing with effects of drugs and natural products and studies dealing with the redox status in various diseases are not within the journal''s scope. Development and evaluation of novel analytical methodologies where applicable to diagnostic clinical chemistry and laboratory medicine, including point-of-care testing, and topics on laboratory management and informatics will also be considered. Studies focused on emerging diagnostic technologies and (big) data analysis procedures including digitalization, mobile Health, and artificial Intelligence applied to Laboratory Medicine are also of interest.
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