Evidence map›Paper›PMID 26000127›Full record

ReviewAuto- immunity highlights2012

Toward a new autoantibody diagnostic orthodoxy: understanding the bad, good and indifferent.

Marvin J Fritzler

Abstract readReview
In one paragraph

Review in Auto- immunity highlights, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

12 citing papers in PubMed.

  1. Review
  2. Antinuclear Antibodies in Systemic Sclerosis: an Update.Clinical reviews in allergy & immunology · 2020
    Review
  3. Analysis of autoantibody profiles in two asbestiform fiber exposure cohorts.Journal of toxicology and environmental health. Part A · 2018
    Article
  4. Review
  5. Article
  6. Review
  7. Article
  8. Detection of autoantibodies using chemiluminescence technologies.Immunopharmacology and immunotoxicology · 2016
    Review
  9. Review
  10. Autoantibodies and SLE: the threshold for disease.Nature reviews. Rheumatology · 2014
    Review
  11. Article
  12. Article
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

1 author.

Marvin J FritzlerFaculty of Medicine, University of Calgary, 3330 Hospital Dr. NW, Calgary, AB T2N 4N1 Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Rapid advances in diagnostic technologies used to detect autoantibodies have made it difficult for even the most modern laboratory to keep abreast of the changing approaches and platforms, not to mention the clinicians who are hard pressed to keep abreast of evolving diagnostic paradigms attended by these newer techniques. While autoantibody testing is traditionally considered to be primarily serving the realm of diagnostic medicine, there is little doubt that autoantibodies are also being recognized as an approach to providing prognostic and therapeutic information. Accordingly, along with related proteomics, genomics and metabolomics, it is taking on increasing importance in the realm of personalized medicine. In today's world of autoantibody diagnostics, overarching concerns about false-negative and false-positive autoantibodies tests cannot be summarily dismissed by citing pros or cons of any one technology or diagnostic platform, but often point to persisting gaps in our knowledge about, and understanding of, the origin and roles of autoantibodies. Before we can hope to completely understand the enigmas that attend the results of autoantibody diagnostic tests, perhaps it is time to step back and re-examine long-accepted paradigms and beliefs. This review will address some of the issues that impact on autoantibody detection technologies and some of the considerations and issues that will attend a new orthodoxy of autoantibody diagnostics. These issues will be addressed in the context of "bad" (pathogenic), "good" (protective) or "indifferent" (no apparent role in disease) autoantibodies.

Indexed as

Anti-nuclear antibodiesAutoantibodiesAutoantigensDiagnostics

Identifiers

PMID26000127
PMCPMC4389070

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.