Evidence map›Paper›PMID 29629217›Full record

ArticleJournal of gastric cancer2018

Is Lymph Node Size a Reliable Factor for Estimating Lymph Node Metastasis in Early Gastric Cancer?

Dong Jin Kim, Wook Kim

Erratum issuedAbstract read
In one paragraph

Article in Journal of gastric cancer, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing 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

14 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. [Multivisceral resection with and without HIPEC in cancer surgery].Der Chirurg; Zeitschrift fur alle Gebiete der operativen Medizen · 2019
    Review
  13. Article
  14. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

2 authors.

Dong Jin KimDepartment of Surgery, The Catholic University of Korea St. Paul's Hospital, The Catholic University of Korea College of Medicine, Seoul, Korea.ORCID https://orcid.org/0000-0001-5103-5607
Wook KimDepartment of Surgery, The Catholic University of Korea Yeouido St. Mary's Hospital, The Catholic University of Korea College of Medicine, Seoul, Korea.ORCID https://orcid.org/0000-0003-3841-4017

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposePre-operative lymph node (LN) size is a valuable parameter for determining treatment strategy for gastric cancer. However, a correlation between LN size and metastasis has not been established. MATERIALS AND

methodsThirty-six LN-positive (LNP) and matched 36 LN-negative (LNN) patients were included, and pathology slides of the LNs of these patients were reviewed. All the LNs were measured along the long-axis (LA) and short-axis (SA), manually.

resultsAverage retrieved LNs were 37.3±19.8 and 40.5±11.6 in the LNN and LNP groups, respectively. In total 2,800 LNs, including 136 metastatic LNs (MLNs) and 2,664 non-metastatic LNs (nMLNs), were evaluated. Mean length was significantly more in MLNs along both, the LA and SA (MLN_LA vs. nMLN_LA: 4.97±3.84 vs. 3.37±2.40 mm, MLN_SA vs. nMLN_SA: 3.86±3.19 vs. 2.43±1.59 mm; P<0.001). However, 92.6% (126/136) and 95.6% (130/136) of MLNs were <10 mm along the LA and SA, respectively. In addition, only 22.2% of the LNP group exhibited an MLN as the largest LN.

conclusionsPre-operative multi-detector computed tomography has limited ability in estimating the presence of metastasis in LNs because most MLNs are less than 10 mm, and only a small proportion of the LNP group exhibits an MLN as the largest MLN.

Indexed as

DiagnosisLymph nodesStomach neoplasms

Identifiers

PMID29629217
PMCPMC5881007

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.