Evidence map›Paper›PMID 24868563›Full record

ReviewJournal of immunology research2014

Current concepts and future directions for the assessment of autoantibodies to cellular antigens referred to as anti-nuclear antibodies.

Michael Mahler, Pier-Luigi Meroni, Xavier Bossuyt, Marvin J Fritzler

Abstract readReview
In one paragraph

Review in Journal of immunology research, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 74 papers.

0numbers the graph read from it
0cells of the map it votes in
74citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

74 citing papers in PubMed.

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  11. From Lab to Clinic: Success Stories of Repurposed Drugs in Treating Major Diseases.Advances in pharmacological and pharmaceutical sciences · 2025
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14 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Michael MahlerINOVA Diagnostics, Inc., 9900 Old Grove Road, San Diego, CA 92131-1638, USA.
Pier-Luigi MeroniRheumatology & Experimental Laboratory of Immuno-rheumatology, University of Milan, Istituto Auxologico Italiano, Via G. Zucchi 18, 20095 Cusano Milanino, Milan, Italy.
Xavier BossuytDepartment of Microbiology and Immunology, Laboratory Medicine, University Hospitals Leuven, KU Leuven, Belgium.
Marvin J FritzlerFaculty of Medicine, University of Calgary, Calgary, Alberta, Canada T2N 4N1.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The detection of autoantibodies that target intracellular antigens, commonly termed anti-nuclear antibodies (ANA), is a serological hallmark in the diagnosis of systemic autoimmune rheumatic diseases (SARD). Different methods are available for detection of ANA and all bearing their own advantages and limitations. Most laboratories use the indirect immunofluorescence (IIF) assay based on HEp-2 cell substrates. Due to the subjectivity of this diagnostic platform, automated digital reading systems have been developed during the last decade. In addition, solid phase immunoassays using well characterized antigens have gained widespread adoption in high throughput laboratories due to their ease of use and open automation. Despite all the advances in the field of ANA detection and its contribution to the diagnosis of SARD, significant challenges persist. This review provides a comprehensive overview of the current status on ANA testing including automated IIF reading systems and solid phase assays and suggests an approach to interpretation of results and discusses meeting the problems of assay standardization and other persistent challenges.

Indexed as

Antibodies, AntinuclearAutoantigensAutoimmune DiseasesAutomation, LaboratoryCell LineDiagnostic ErrorsFluorescent Antibody Technique, IndirectForecastingHumansSensitivity and SpecificityAntibodies, AntinuclearAutoantigens

Identifiers

PMID24868563
PMCPMC4020446

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Registered trials

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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.