Evidence map›Paper›PMID 37384287›Full record

ArticleFrontiers in oncology2023

Prognostic and predictive values of the grading system of lymph node status in patients with advanced-stage gastric cancer.

Xue-Mei Zhang, Wei-Wei Shen, Ling-Jun Song

Open access · goldAbstract read
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Article in Frontiers in oncology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
1.6field-weighted citation impact, top 16% of its field
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

5 citing papers in PubMed, 6 citations in OpenAlex.

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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 at 2 institutions in 1 country.

Xue-Mei ZhangPathology Center, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Wei-Wei ShenKey Laboratory of Cell Differentiation and Apoptosis of Chinese Ministry of Education, Institutes of Medical Sciences, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Ling-Jun SongPathology Center, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Shanghai Jiao Tong University · CNShanghai First People's Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Lymph node metastasis is one of the most important prognostic factors of gastric cancer. However, the effect of germinal centers in lymph nodes on the prognosis of patients with gastric cancer has not been reported. This study aimed to investigate the contribution of germinal center generation to prognostic parameters and clinicopathological significance in gastric cancer. Methods: We retrospectively reviewed gastric cancer patients who underwent surgery from October 2012 to June 2022. We analyzed 5484 lymph nodes (210 patients) and calculated the lymph node metastasis rate (LNMR) and the proportion of non-metastatic lymph nodes containing three or more germinal centers (NML-GCP). Results: Using a grading system that incorporated LNMR and NML-GCP. The tumors were classified into three groups based on this system, which was found to be significantly associated with prognosis. The TNM stage and grading system of lymph node status were independent risk factors for overall survival (OS) and disease-free survival (DFS). The 5-year OS rates for patients with advanced gastric cancer were 85.07% (n=50), 58.34% (n=42), and 24.44% (n=21) for Grades 1, 2, and 3, respectively ( Conclusion: These findings suggest that the grading system may be valuable for predicting prognosis and guiding clinical management in patients with gastric cancer, and provides good prognostic stratification for OS and DFS in patients with TNM stage II and III.

Indexed as

chemotherapy resistancegastric cancergerminal centerlymph nodeprognosis

Identifiers

PMID37384287
PMCPMC10299729
OpenAlexW4380480128

What OpenQuestion holds

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LicenceCC BY
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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.