Evidence map›Paper›PMID 32368321›Full record

ArticleWorld journal of gastrointestinal oncology2020

Diagnostic ability of multi-detector spiral computed tomography for pathological lymph node metastasis of advanced gastric cancer.

Zhi-Yong Jiang, Shinichi Kinami, Naohiko Nakamura, Takashi Miyata, Hideto Fujita, Hiroyuki Takamura, Nobuhiko Ueda, Takeo Kosaka

Open access · diamondAbstract read
In one paragraph

Article in World journal of gastrointestinal oncology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
0.5field-weighted citation impact, top 31% 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

6 citing papers in PubMed, 8 citations in OpenAlex.

  1. Review
  2. Evaluation of the efficacy ofFrontiers in oncology · 2025
    Article
  3. Article
  4. Article
  5. Article
  6. 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

8 authors at 2 institutions in 1 country.

Zhi-Yong JiangDepartment of Surgical Oncology, Kanazawa Medical University, 1-1 Daigaku, Uchinada-machi, Kahoku-gun, Ishikawa 920-0293, Japan.
Shinichi KinamiDepartment of Surgical Oncology, Kanazawa Medical University, 1-1 Daigaku, Uchinada-machi, Kahoku-gun, Ishikawa 920-0293, Japan. kinami@kanazawa-med.ac.jp.
Naohiko NakamuraDepartment of Surgical Oncology, Kanazawa Medical University, 1-1 Daigaku, Uchinada-machi, Kahoku-gun, Ishikawa 920-0293, Japan.
Takashi MiyataDepartment of Surgical Oncology, Kanazawa Medical University, 1-1 Daigaku, Uchinada-machi, Kahoku-gun, Ishikawa 920-0293, Japan.
Hideto FujitaDepartment of Surgical Oncology, Kanazawa Medical University, 1-1 Daigaku, Uchinada-machi, Kahoku-gun, Ishikawa 920-0293, Japan.
Hiroyuki TakamuraDepartment of Surgical Oncology, Kanazawa Medical University, 1-1 Daigaku, Uchinada-machi, Kahoku-gun, Ishikawa 920-0293, Japan.
Nobuhiko UedaDepartment of Surgical Oncology, Kanazawa Medical University, 1-1 Daigaku, Uchinada-machi, Kahoku-gun, Ishikawa 920-0293, Japan.
Takeo KosakaDepartment of Surgical Oncology, Kanazawa Medical University, 1-1 Daigaku, Uchinada-machi, Kahoku-gun, Ishikawa 920-0293, Japan.
Kanazawa Medical University · JPKanazawa Medical University Hospital · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe reliability of preoperative nodal diagnosis of advanced gastric cancer by multi-detector spiral computed tomography (MDCT) is still unclear.

aimTo examine the diagnostic ability of MDCT more precisely by using data on intranodal pathological metastatic patterns.

methodsA total of 108 patients with advanced gastric cancer who underwent MDCT and curative gastrectomy at Kanazawa Medical University Hospital were enrolled in this study. The nodal sizes measured on computed tomography (CT) images were compared with the pathology results. A receiver-operating characteristic curve was constructed, from which the critical value (CV) was calculated by using the data of the first 69 patients retrospectively. By using the CV, sensitivity and specificity were calculated with prospectively collected data from 39 consecutive patients. This enabled a more precise one-to-one correspondence of lymph nodes between CT and pathological examination by using the size data of lymph node mapping. The intranodal pathological metastatic patterns were classified into the following four types: Small nodular, peripheral, large nodular, and diffuse.

resultsAlthough all the cases were clinically suspected as having metastasis, 81 had lymph node metastasis and 27 had no metastasis. The number of dissected, detected on CT, and metastatic nodes were, 4241, 897, and 801, respectively. The CV obtained from the receiver-operating characteristic was 7.6 mm for the long axis. The sensitivity was 91.4% and the specificity was 47.3% in the prospective phase. The large nodular and diffuse metastases were easy to diagnose because metastatic nodes with a large axis often exhibit these forms.

conclusionThe ability of MDCT to contribute to a nodal diagnosis of advanced gastric cancer was examined prospectively with precise size data from node mapping, using a CV of 7.6 mm for the long axis that was calculated from the retrospectively collected data. The sensitivity was as high as 91%, and would be improved when referring to the enhanced patterns. However, its specificity was as low as 47%, because most of metastatic nodes in gastric cancer being small in size. The small nodular or peripheral type metastatic nodes were often small and considered difficult to diagnose.

Indexed as

Advanced gastric cancerLymph node metastasisMulti-detector spiral computed tomographyPathological diagnosis

Identifiers

PMID32368321
PMCPMC7191330
OpenAlexW3016604362

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

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.