Evidence map›Paper›PMID 36690895›Full record

ArticleSurgical endoscopy2023

Preoperative diagnosis of tumor depth in gastric cancer using transabdominal ultrasonography compared to using endoscopy and computed tomography.

Shinya Urakawa, Toshiya Michiura, Shinji Tokuyama, Yasunari Fukuda, Yasuaki Miyazaki, Nobuyasu Hayashi, Kazuo Yamabe

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Article in Surgical endoscopy, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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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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

3 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Shinya UrakawaDepartment of Gastroenterological Surgery, Kinan Hospital, Wakayama, Japan. urashin.1130@gmail.com.
Toshiya MichiuraDepartment of Gastroenterological Surgery, Kinan Hospital, Wakayama, Japan.
Shinji TokuyamaDepartment of Gastroenterological Surgery, Kinan Hospital, Wakayama, Japan.
Yasunari FukudaDepartment of Gastroenterological Surgery, Kinan Hospital, Wakayama, Japan.
Yasuaki MiyazakiDepartment of Gastroenterological Surgery, Kinan Hospital, Wakayama, Japan.
Nobuyasu HayashiDepartment of Gastroenterological Surgery, Kinan Hospital, Wakayama, Japan.
Kazuo YamabeDepartment of Gastroenterological Surgery, Kinan Hospital, Wakayama, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAn accurate evaluation method for preoperative diagnosis has not yet been established in patients with gastric cancer (GC), though it is essential for optimal treatment. Current standard modalities are endoscopy and contrast computed tomography (CT). In this study, we investigated the efficacy and limitations of transabdominal ultrasonography (TUS) for the assessment of tumor invasion.

methodsWe enrolled 178 consecutive patients with GC evaluated by TUS, endoscopy, and contrast CT before gastrectomy. For the TUS examination, patients ingested water to fill their stomachs. The clinical staging determined using these modalities was compared to the pathological staging.

resultsThe overall accuracy of clinical T staging using TUS was 47.8% (pT1a: 5.8% (2/35); pT1b: 58.8% (20/35); pT2: 69.6% (16/23); pT3: 66.7% (22/33); pT4a: 46% (23/50); pT4b: 100% (2/2)). Using endoscopy, contrast CT, and TUS, the overall accuracy was 60.7%. The accuracy of TUS was associated with the tumor region (U region: 50% (14/28); M: 31.8% (14/44); L: 53.7% (57/106); P = 0.048), but not with the cross-sectional parts (P = 0.49). Multivariate analysis identified inaccurate TUS as independently correlating with tumor region (M vs. U/L, odds ratio (OR) = 3.11, 95% confidence interval (CI) 1.41-6.87; P = 0.005) and pT (pT1 vs. pT2-4, OR = 3.00, 95%CI 1.31-6.87; P = 0.009).

conclusionsThe present study demonstrated the importance of TUS in evaluating GC. Thus, TUS may be useful for clinical T staging in certain circumstances, leading to treatment optimization.

Indexed as

Stomach NeoplasmsCross-Sectional StudiesEndoscopy, GastrointestinalHumansNeoplasm StagingTomography, X-Ray ComputedUltrasonographyGastric cancerTransabdominal ultrasonographyTumor depth

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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.