Evidence map›Paper›PMID 39743929›Full record

SynthesisHistology and histopathology2025

Molecular and immunohistochemical markers in appendiceal mucinous neoplasms: A systematic review and comparative analysis with ovarian mucinous neoplasms and colorectal adenocarcinoma.

Basel Elsayed, Amgad Mohamed Elshoeibi, Mohamed Elhadary, Abdullah M Al-Jubouri, Noof Al-Qahtani, Semir Vranic, Rafif Al-Saady

Abstract readSystematic ReviewComparative Study
PubMed Publisher
In one paragraph

Synthesis in Histology and histopathology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed, 1 pooled it
–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

3 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. 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

7 authors.

Basel ElsayedCollege of Medicine, QU Health, Qatar University, Doha, Qatar. be1905231@qu.edu.qa.
Amgad Mohamed ElshoeibiCollege of Medicine, QU Health, Qatar University, Doha, Qatar.
Mohamed ElhadaryCollege of Medicine, QU Health, Qatar University, Doha, Qatar.
Abdullah M Al-JubouriCollege of Medicine, QU Health, Qatar University, Doha, Qatar.
Noof Al-QahtaniCollege of Medicine, QU Health, Qatar University, Doha, Qatar.
Semir VranicDepartment of Pathology, College of Medicine, QU Health, Qatar University, Doha, Qatar.
Rafif Al-SaadyDepartment of Pathology, College of Medicine, QU Health, Qatar University, Doha, Qatar.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionAppendiceal mucinous neoplasms (AMNs) represent a rare and diagnostically challenging group of tumors. This systematic review aims to summarize the reported molecular and immunohistochemical markers (IHC) associated with AMNs and compare them with ovarian mucinous neoplasms (OMNs) and colorectal adenocarcinoma (CRC).

methodsA comprehensive search was performed in PubMed/MEDLINE/PMC, Scopus, Embase, and Web of Science databases to identify studies looking at IHC and molecular markers in AMNs. Chi-squared and Fisher's exact tests were utilized to compare the marker expression across different tumor types.

resultsWe identified 27 articles reporting several potential biomarkers for distinguishing between different subtypes of AMNs. Mutations in

conclusionThis systematic review identified possible markers for distinguishing AMNs and differentiating between AMNs, OMNs, or CRCs.

Indexed as

Adenocarcinoma, MucinousAppendiceal NeoplasmsBiomarkers, TumorColorectal NeoplasmsOvarian NeoplasmsFemaleHumansImmunohistochemistryMutationBiomarkers, Tumor

Identifiers

PMID39743929

What OpenQuestion holds

Textmetadata
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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.