Evidence map›Paper›PMID 39917315›Full record

ReviewJournal of translational autoimmunity2025

Monitoring the follow-up of autoimmune chronic atrophic gastritis using parietal cell antibodies and markers of gastric function.

Maria Piera Panozzo, Antonio Antico, Nicola Bizzaro

Abstract readReview
In one paragraph

Review in Journal of translational autoimmunity, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. The Evolution of Autoimmune Gastritis Research (1995-2025): A Hybrid Bibliometric-Conceptual Synthesis.The Korean journal of helicobacter and upper gastrointestinal research · 2026
    Article
  2. Autoimmune gastritis: emerging insights and clinical management.Nature reviews. Gastroenterology & hepatology · 2026
    Review
  3. Review
  4. Review
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.

Maria Piera PanozzoDepartment of Laboratory Medicine, AULSS7 Pedemontana, Santorso, Italy.
Antonio AnticoDepartment of Laboratory Medicine, AULSS2 Marca Trevigiana, Treviso, Italy.
Nicola BizzaroLaboratory of Clinical Pathology, Azienda Sanitaria Universitaria Integrata, Udine, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Increased interest in the pathogenesis and the evolution of autoimmune chronic atrophic gastritis (A-CAG) has led to the search for serological markers that can be used to detect changes in the gastric mucosa at an early stage and to monitor the course of the disease. Parietal cell autoantibodies have been proposed as suitable immunological markers of atrophic damage, as they can be detected in the serum when symptoms of gastritis are not yet present. However, the utility of measuring only the level of parietal cell autoantibodies in the follow-up of A-CAG does not appear to suffice. Recent evidence has suggested that, in monitoring A-CAG, parietal cell antibodies should be associated with an evaluation of gastric function through biochemical and hormonal tests, such as pepsinogens and gastrin 17. This integrated approach will allow for the more effective real-time monitoring of the state of the gastric mucosa. As A-CAG is a progressive disorder associated with an increased risk of gastric cancer and neuroendocrine tumors, the precise follow-up of patients with gastric atrophy needs to be better defined. Further longitudinal studies in large cohorts must be performed with long-term follow-up.

Indexed as

Autoimmune chronic atrophic gastritisGastrin 17Intrinsic factor autoantibodiesNeuroendocrine tumorsParietal cell autoantibodiesPepsinogens

Identifiers

PMID39917315
PMCPMC11800024

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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.