ArticleJournal of clinical laboratory analysis1997
Comparison and variation of different methodologies for the detection of autoantibodies to nuclear antigens (ANA).
Article in Journal of clinical laboratory analysis, 1997. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
3 citing papers in PubMed, 16 citations in OpenAlex.
- Antinuclear Antibodies in Systemic Sclerosis: an Update.Clinical reviews in allergy & immunology · 2020Review
- Determination of cut-off titers and agreement between immunofluorescence and immunoblotting methods for detecting antinuclear antibodies in children.Journal of clinical laboratory analysis · 2010Article
- RNA recognition motif (RRM) of La/SSB: the bridge for interparticle spreading of autoimmune response to U1-RNP.Molecular medicine (Cambridge, Mass.)Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Interest in the assessment of autoantibody specificity stems from the need for an autoantibody marker capable of predicting clinical events in autoimmune disorders. However, the multiplicity of epitopes present on autoantigenic particles, the quantitative and qualitative heterogeneity of autoantibodies, as well as the nature of the tests, mean that each of the assays used in their determination have different characteristics. The aim of this study was to compare the specificities of different ANAs using four commercial assays. The routine method used for the detection of ANA is indirect immunofluorescence on Hep-2 cells. The assays used were: counterimmunoelectrophoresis (CIE), enzyme-linked immunosorbent assay (ELISA), and two immunoblotting assays. Kappa statistic was applied to evaluate the consistency between tests. Kappa index is a measure of agreement between categorical data. Kappa has a maximum of 1.00 when the agreement is perfect, a value of zero indicates no agreement better than chance, and negative values show worse than chance agreement. For SS-B antibodies, there was a good concordance between all four methods used (Kappa 0.66-0.74). For anti RNP antibodies, the results for CIE/ELISA (Kappa 0.60) were consistent as were the two immunoblot methods (Kappa 0.69). For anti Scl-70 (topoisomerase I) antibody, results from the ELISA and CIE methods were totally consistent (Kappa 1.00). In spite of the high prevalence of anti SS-A/Ro antibodies, the agreement between the methods was poor, without statistical significance. Finally, for Sm antibodies, more consistent results were obtained between CIE/ELISA (Kappa 0.51) and between one of the immunoblotting methods and ELISA (Kappa 0.54). In conclusion, CIE concurs mostly with ELISA for anti-RNP, Scl-70, Sm and SS-B antibodies, but with some disagreement for SS-A antibodies.
Indexed as
Identifiers
9406062PMC6760727W1980018732What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.