Evidence map›Paper›PMID 24833868›Full record

ReviewWorld journal of gastroenterology2014

Unveiling lymph node metastasis in early gastric cancer.

Nari Shin, Tae-Yong Jeon, Gwang Ha Kim, Do Youn Park

Abstract readReview
In one paragraph

Review in World journal of gastroenterology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

12 citing papers in PubMed.

  1. Artificial intelligence efficiently predicts gastric lesions,Chinese journal of cancer research = Chung-kuo yen cheng yen chiu · 2024
    Article
  2. Article
  3. Preoperative imaging evaluation of the absolute indication criteria for endoscopic submucosal dissection in early gastric cancer patients.Wideochirurgia i inne techniki maloinwazyjne = Videosurgery and other miniinvasive techniques · 2021
    Article
  4. Article
  5. Article
  6. Article
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  8. Histologic purity of signet ring cell carcinoma is a favorable risk factor for lymph node metastasis in poorly cohesive, submucosa-invasive early gastric carcinoma.Gastric cancer : official journal of the International Gastric Cancer Association and the Japanese Gastric Cancer Association · 2017
    Article
  9. Article
  10. Article
  11. Effect of World Health Organization (WHO) Histological Classification on Predicting Lymph Node Metastasis and Recurrence in Early Gastric Cancer.Medical science monitor : international medical journal of experimental and clinical research · 2016
    Article
  12. Predictable factors for lymph node metastasis in early gastric cancer analysis of clinicopathologic factors and biological markers.Tumour biology : the journal of the International Society for Oncodevelopmental Biology and Medicine · 2016
    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.

Nari ShinNari Shin, Do Youn Park, Department of Pathology, Pusan National University Hospital and Pusan National University School of Medicine, Busan 602-739, South Korea.
Tae-Yong JeonNari Shin, Do Youn Park, Department of Pathology, Pusan National University Hospital and Pusan National University School of Medicine, Busan 602-739, South Korea.
Gwang Ha KimNari Shin, Do Youn Park, Department of Pathology, Pusan National University Hospital and Pusan National University School of Medicine, Busan 602-739, South Korea.
Do Youn ParkNari Shin, Do Youn Park, Department of Pathology, Pusan National University Hospital and Pusan National University School of Medicine, Busan 602-739, South Korea.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

With respect to gastric cancer treatment, improvements in endoscopic techniques and novel therapeutic modalities [such as endoscopic mucosal resection (EMR) and endoscopic submucosal dissection (ESD)] have been developed. Currently, EMR/ESD procedures are widely accepted treatment modalities for early gastric cancer (EGC). These procedures are most widely accepted in Asia, including in Korea and Japan. In the present era of endoscopic resection, accurate prediction of lymph node (LN) metastasis is a critical component of selecting suitable patients for EMR/ESD. Generally, indications for EMR/ESD are based on large Japanese datasets, which indicate that there is almost no risk of LN metastasis in the subgroup of EGC cases. However, there is some controversy among investigators regarding the validity of these criteria. Further, there are currently no accurate methods to predict LN metastasis in gastric cancer (for example, radiologic methods or methods based on molecular biomarkers). We recommend the use of a 2-step method for the management of early gastric cancer using endoscopic resection. The first step is the selection of suitable patients for endoscopic resection, based on endoscopic and histopathologic findings. After endoscopic resection, additional surgical intervention could be determined on the basis of a comprehensive review of the endoscopic mucosal resection/endoscopic submucosal dissection specimen, including lymphovascular tumor emboli, tumor size, histologic type, and depth of invasion. However, evaluation of clinical application data is essential for validating this recommendation. Moreover, gastroenterologists, surgeons, and pathologists should closely collaborate and communicate during these decision-making processes.

Indexed as

DissectionEarly Detection of CancerGastrectomyGastroscopyHumansLymphatic MetastasisLymph NodesNeoplasm InvasivenessPatient SelectionPredictive Value of TestsStomach NeoplasmsTreatment OutcomeBiomarkerClinicopathologic featuresEarly gastric cancerEndoscopic submucosal dissectionLymph node metastasis

Identifiers

PMID24833868
PMCPMC4017053

What OpenQuestion holds

Textmetadata
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.