Evidence map›Paper›PMID 41684784›Full record

ReviewFrontiers in nutrition2026

From mechanisms to management: a comprehensive review of sarcopenia in gastric cancer.

Wenhao Liu, Hongliang Cao, Xuanpeng Zhou, Luanbiao Sun, Linchun Li, Xinyuan Song, Yang Gao, Jianpeng Xing, Shuohui Gao

Abstract readReview
In one paragraph

Review in Frontiers in nutrition, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.

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

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

  1. Pooled it
  2. 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

9 authors.

Wenhao Liu *China-Japan Union Hospital of Jilin University, Changchun, Jilin, China.
Hongliang Cao *Department of Urology II, The First Hospital of Jilin University, Changchun, Jilin, China.
Xuanpeng ZhouChina-Japan Union Hospital of Jilin University, Changchun, Jilin, China.
Luanbiao SunChina-Japan Union Hospital of Jilin University, Changchun, Jilin, China.
Linchun LiChina-Japan Union Hospital of Jilin University, Changchun, Jilin, China.
Xinyuan SongDepartment of Statistics, The Chinese University of Hong Kong, New Territories, Hong Kong, China.
Yang GaoZhalute Banner People's Hospital, Tongliao, Inner Mongolia, China.
Jianpeng XingChina-Japan Union Hospital of Jilin University, Changchun, Jilin, China.
Shuohui GaoChina-Japan Union Hospital of Jilin University, Changchun, Jilin, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Gastric cancer (GC), a leading cause of global cancer mortality, induces systemic changes impacting patient prognosis. A growing body of evidence shows a significantly increased prevalence of sarcopenia in GC patients, closely linked to poor outcomes such as higher postoperative complications, enhanced chemotherapy toxicity, and shortened survival. However, its underlying mechanisms and optimal management remain not fully clarified. This review comprehensively analyzes the pathological mechanisms and clinical significance of GC-related sarcopenia, emphasizing systemic inflammation, metabolic/nutritional disorders, neuroendocrine dysfunction, and anti-tumor therapy impacts. Additionally, feasible management methods such as nutritional support, exercise intervention, and related drug treatment were also proposed. By synthesizing current evidence, we delineate sarcopenia's integral role in GC and propose pragmatic strategies to ultimately improve patient outcomes.

Indexed as

gastric cancermanagementmechanismprognosissarcopenia

Identifiers

PMID41684784
PMCPMC12890681

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.