Evidence map›Paper›PMID 37746651›Full record

ArticleWorld journal of gastrointestinal oncology2023

Efficacy of multi-slice spiral computed tomography in evaluating gastric cancer recurrence after endoscopic submucosal dissection.

Jian-Jun Yin, Xiao Hu, Sen Hu, Guo-Hong Sheng

Abstract read
In one paragraph

Article in World journal of gastrointestinal oncology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

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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

1 citing paper in PubMed.

  1. 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

4 authors.

Jian-Jun YinDepartment of Radiology, Huangshi Maternity and Children's health Hospital, Affiliated Maternity and Children's Health Hospital of Hubei Polytechnic University, Huangshi 435000, Hubei Province, China.
Xiao HuDepartment of Geriatrics, Huangshi Central Hospital, Affiliated Hospital of Hubei Polytechnic University, Huangshi 435000, Hubei Province, China. 11786356@qq.com.
Sen HuDepartment of Radiology, Huangshi Maternity and Children's health Hospital, Affiliated Maternity and Children's Health Hospital of Hubei Polytechnic University, Huangshi 435000, Hubei Province, China.
Guo-Hong ShengDepartment of Radiology, Huangshi Maternity and Children's health Hospital, Affiliated Maternity and Children's Health Hospital of Hubei Polytechnic University, Huangshi 435000, Hubei Province, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundRecurrence is the major challenge facing endoscopic submucosal dissection (ESD)-based treatment therapies for early gastric cancer (EGC). Urgent development of simple and easy surveillance approaches will enhance clinical treatment of the disease.

aimTo explore the role of computed tomography (CT) recurrence in evaluating EGC after ESD treatment.

methodsWe retrospectively recruited patients from our endoscopy department, between January 2002 and December 2015, and analyzed their basic characteristics, including symptoms, CT results, and results of endoscopy with biopsy, among others.

resultsAmong a total of 2150 patients EGC patients surveyed, 1362 met our inclusion and exclusion criteria and were therefore enrolled in our study. The cohort's sensitivity of CT for recurrent GC and specificity were 44.22% and 43.86%, respectively, with negative and positive predictive values of 40.15% (275/685) and 48.01% (325/677), respectively. The area under the curve of arterial and venous CT values for recurrent EGC were 0.545, and 0.604, respectively. Receiver operating characteristic curve revealed no statistically significant differences between arterial and venous CT values for recurrent EGC.

conclusionEnhanced CT has superior diagnostic efficacy, but less accuracy, compared to gold standard techniques in patients with recurrent EGC.

Indexed as

Computed tomographyEarly gastric cancerGastric cancerMulti-slice spiral computed tomography

Identifiers

PMID37746651
PMCPMC10514731

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