Evidence map›Paper›PMID 41393136›Full record

SynthesisFrontiers in medicine2025

Endoscopic submucosal dissection vs. endoscopic mucosal resection for early gastric cancer: a meta-analysis.

Xiaoli Zheng, Long Xu

Abstract readSystematic Review
In one paragraph

Synthesis in Frontiers in medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. A preoperative risk-scoring model for predicting intraoperative hemorrhage during endoscopic submucosal dissection for gastric neoplasms.Gastric cancer : official journal of the International Gastric Cancer Association and the Japanese Gastric Cancer Association · 2026
    Article
  2. Review
  3. 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

2 authors.

Xiaoli ZhengDepartment of Gastroenterology, Shenzhen University General Hospital, Shenzhen, Guangdong, China.
Long XuDepartment of Gastroenterology, Shenzhen University General Hospital, Shenzhen, Guangdong, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: This study aimed to evaluate the efficacy and safety of endoscopic mucosal resection (EMR) versus endoscopic submucosal dissection (ESD) in the treatment of early gastric cancer (EGC) through a meta-analysis, and to provide evidence-based guidance for clinical decision-making. Methods: Relevant studies were systematically retrieved from PubMed, EMBASE, Web of Science, the Cochrane Library, and major Chinese databases. Randomized controlled trials (RCTs) comparing EMR and ESD for EGC were included. Meta-analysis was performed using Review Manager 5.3 software. The primary outcomes included en bloc resection rate, curative resection rate, local tumor recurrence, procedure time, and complications. Subgroup analyses were performed according to procedure time, follow-up duration, and lesion type to explore potential sources of heterogeneity. Results: A total of nine studies comprising 3,574 patients were included. The results showed that ESD was associated with significantly higher en bloc resection and curative resection rates compared to EMR (OR = 4.00, Conclusion: ESD provides superior therapeutic efficacy over EMR in early gastric cancer, particularly in differentiated lesions and long-term follow-up settings, though it demands greater technical expertise and longer operative time. These findings support ESD as the preferred approach for appropriately selected EGC patients.

Indexed as

early gastric cancerendoscopic mucosal resectionendoscopic submucosal dissectionmeta-analysissubgroup analysistherapeutic efficacy

Identifiers

PMID41393136
PMCPMC12695570

What OpenQuestion holds

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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.