Evidence map›Paper›PMID 39607533›Full record

ArticleJapanese journal of radiology2025

Influence of visceral adipose tissue on the accuracy of tumor T-staging of gastric cancer in preoperative CT.

Danping Wu, Linjie Bian, Zhongjuan Wang, Jianming Ni, Yigang Chen, Lei Zhang, Xulei Chen

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Article in Japanese journal of radiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
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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

7 authors.

Danping Wu *Department of Nuclear Medicine, Jiangyuan Hospital Affiliated to Jiangsu Institute of Nuclear Medicine, Wuxi, Jiangsu, China.
Linjie Bian *Department of Nuclear Medicine, Fudan University Shanghai Cancer Center, Shanghai, China.
Zhongjuan WangDepartment of Radiology, Wuxi No. 2 People's Hospital, Wuxi, Jiangsu, China. nancywzj2013@163.com.ORCID http://orcid.org/0009-0004-0628-0899
Jianming NiDepartment of Radiology, Wuxi No. 2 People's Hospital, Wuxi, Jiangsu, China.
Yigang ChenDepartment of General Surgery, Wuxi No. 2 People's Hospital, Wuxi, Jiangsu, China.
Lei ZhangDepartment of Radiology, Wuxi No. 2 People's Hospital, Wuxi, Jiangsu, China.
Xulei ChenDepartment of Pathology, Wuxi No. 2 People's Hospital, Wuxi, Jiangsu, China.

Funding

Soft Science Research Project of Wuxi Science and Technology Association KX-24-B83Youth Science Project of Wuxi Health Committee Q202249
6 · The paper itself

Abstract

objectivesTo evaluate the impact of the visceral adipose tissue (VAT) area and density on the accuracy of tumor T-staging of gastric cancer in preoperative computed tomography (CT).

methodsThis study included 136 patients with gastric cancer in our research center from January 2021 to June 2022. The patients were divided into two groups based on their postoperative pathological results: accurate-staging (matched T-staging evaluated by preoperative CT and postoperative pathology) and inaccurate-staging (unmatched T-staging evaluated by preoperative CT and postoperative pathology) groups. Preoperative CT was performed to assess the VAT area and density, and logistic regression was employed to evaluate the effect of VAT on the accuracy of preoperative-CT-evaluated T-staging of patients with gastric cancer.

resultsThe accurate-staging group had a significantly higher VAT area (134.64 ± 70.55 cm

conclusionsA low VAT area in patients with gastric cancer had adverse effects on preoperative CT-evaluated T-staging.

Indexed as

Intra-Abdominal FatStomach NeoplasmsTomography, X-Ray ComputedAdultAgedAged, 80 and overFemaleHumansMaleMiddle AgedNeoplasm StagingPreoperative CareRetrospective StudiesStomachGastric cancerPostoperative complicationsVisceral fat

Identifiers

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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.