Evidence map›Paper›PMID 35192227›Full record

ArticleJournal of veterinary internal medicine2022

A scoping review of autoantibodies as biomarkers for canine autoimmune disease.

Amy E Treeful, Emily L Coffey, Steven G Friedenberg

Open access · goldAbstract readScoping Review
In one paragraph

Article in Journal of veterinary internal medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.3field-weighted citation impact, top 47% of its field
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

1 citing paper in PubMed, 4 citations in OpenAlex.

  1. 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

3 authors at 1 institution in 1 country.

Amy E TreefulDepartment of Veterinary Population Medicine, College of Veterinary Medicine, University of Minnesota, St. Paul, Minnesota, USA.ORCID https://orcid.org/0000-0002-7270-0538
Emily L CoffeyDepartment of Veterinary Clinical Sciences, College of Veterinary Medicine, University of Minnesota, St. Paul, Minnesota, USA.ORCID https://orcid.org/0000-0002-1229-5104
Steven G FriedenbergDepartment of Veterinary Clinical Sciences, College of Veterinary Medicine, University of Minnesota, St. Paul, Minnesota, USA.ORCID https://orcid.org/0000-0002-7510-2322
University of Minnesota · US

Funding

Training in PharmacoNeuroImmune Substance Abuse ResearchT32DA007097 · NIDA · UNIVERSITY OF MINNESOTA TWIN CITIES · PI MOLITOR, THOMAS WILLIAM · 1985 to 2021
$13.1M
Comparative Medicine and Pathology TrainingT32OD010993 · OD · UNIVERSITY OF MINNESOTA · PI DAVID R BROWN, Cathy S. Carlson · 2012 to 2026
$6.2M
Immunological Basis of Autoimmune Addison's Disease in a Novel Canine Model SystemK01OD027058 · OD · UNIVERSITY OF MINNESOTA · PI FRIEDENBERG, STEVEN GENE · 2019 to 2023
$724k
NIDA NIH HHS T32 DA007097NIH HHS K01 OD027058NIH HHS T32 OD010993ODCDC CDC HHS K01 OD027058United States Department of Health and Human Services, National Institutes of Health NIH/NIDA T32 DA007097United States Department of Health and Human Services, National Institutes of Health T32 OD010993-15
6 · The paper itself

Abstract

backgroundAutoantibody biomarkers are valuable tools used to diagnose and manage autoimmune diseases in dogs. However, prior publications have raised concerns over a lack of standardization and sufficient validation for the use of biomarkers in veterinary medicine.

objectivesSystematically compile primary research on autoantibody biomarkers for autoimmune disease in dogs, summarize their methodological features, and evaluate their quality; synthesize data supporting their use into a resource for veterinarians and researchers. ANIMALS: Not used.

methodsFive indices were searched to identify studies for evaluation: PubMed, CAB Abstracts, Web of Science, Agricola, and SCOPUS. Two independent reviewers (AET and ELC) screened titles and abstracts for exclusion criteria followed by full-text review of remaining articles. Relevant studies were classified based on study objectives (biomarker, epitope, technique). Data on study characteristics and outcomes were synthesized in independent data tables for each classification.

resultsNinety-two studies qualified for final analysis (n = 49 biomarker, n = 9 epitope, and n = 34 technique studies). A high degree of heterogeneity in study characteristics and outcomes reporting was observed. Opportunities to strengthen future studies could include: (1) routine use of negative controls, (2) power analyses to inform sample sizes, (3) statistical analyses when appropriate, and (4) multiple detection techniques to confirm results.

conclusionsThese findings provide a resource that will allow veterinary clinicians to efficiently evaluate the evidence supporting the use of autoantibody biomarkers, along with the varied methodological approaches used in their development.

Indexed as

Autoimmune DiseasesDog DiseasesVeterinariansAnimalsAutoantibodiesBiomarkersDogsHumansAutoantibodiesBiomarkersautoantibodyautoimmunitybiomarkerdogsimmune-mediated diseases

Identifiers

PMID35192227
PMCPMC8965235
OpenAlexW4213277174

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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 Socratic graph.