Evidence map›Paper›PMID 42395630›Full record

SynthesisFrontiers in nutrition2026

Prognostic nutritional indices and long-term survival after endoscopic submucosal dissection for early gastric cancer in elderly patients: a systematic review and meta-analysis.

Huan Li, Xiao-Zhi Fu, Jie Chen, Xue-Fang Huang, Hui Long

Abstract readSystematic Review
In one paragraph

Synthesis in Frontiers in nutrition, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0cells of the map it votes in
0citing 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

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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

5 authors.

Huan LiDepartment of Gastroenterology, Tianyou Hospital Affiliated to Wuhan University of Science and Technology, Wuhan, China.
Xiao-Zhi FuDepartment of Gastroenterology, Tianyou Hospital Affiliated to Wuhan University of Science and Technology, Wuhan, China.
Jie ChenDepartment of Gastroenterology, Tianyou Hospital Affiliated to Wuhan University of Science and Technology, Wuhan, China.
Xue-Fang HuangDepartment of Gastroenterology, Tianyou Hospital Affiliated to Wuhan University of Science and Technology, Wuhan, China.
Hui LongDepartment of Gastroenterology, Tianyou Hospital Affiliated to Wuhan University of Science and Technology, Wuhan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Nutritional risk and host vulnerability may influence long-term outcomes in elderly patients with early gastric cancer (EGC) undergoing endoscopic submucosal dissection (ESD). The prognostic nutritional index (PNI) and geriatric nutritional risk index (GNRI) are simple nutritional and prognostic indices, but their prognostic value in this population has not been systematically evaluated. Methods: We conducted a systematic review and meta-analysis of studies assessing the association between PNI or GNRI and long-term survival in elderly patients (≥ 65 years) treated with ESD for EGC. PubMed, Embase, and Web of Science were searched up to December 28, 2025. Hazard ratios (HRs) or comparable multivariable estimates with 95% confidence intervals (CIs) were synthesized using fixed- or random-effects models. Subgroup and sensitivity analyses were conducted to assess consistency and heterogeneity. Results: Conclusion: Lower PNI and GNRI were associated with poorer survival outcomes in elderly patients with EGC treated by ESD. These findings highlight the potential clinical relevance of nutritional risk assessment and may help inform risk stratification, but further prospective studies are needed to validate their clinical utility and assess whether targeted interventions can modify outcomes. Systematic review registration: identifier: CRD420251270408.

Indexed as

early gastric cancerelderly patientsendoscopic submucosal dissectionlong-term survivalnutritional indices

Identifiers

PMID42395630
PMCPMC13322933

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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.