Literature DB >> 18386233

Metastatic/resected lymph nodes ratio-based classification in gastric cancer.

Halil Ozgüç1, Yalçin Sönmez, Omer Yerci.   

Abstract

BACKGROUND/AIMS: Many studies have shown that the metastatic lymph node ratio, calculated by dividing the number of metastatic lymph nodes by the total number of lymph nodes, is an important prognostic factor in gastric cancer. In the present study, the applicability of the metastatic in the 1997 Tumor Node Metastasis system was investigated using our clinical data and discussed in light of the literature.
METHODS: The study was performed on the 166 patients with gastric cancer in whom R0 resection could be performed and more than 15 nodes were resected. The possible effects of age, gender, location, type of resection, number of resected lymph nodes, depth of invasion, number of involved lymph nodes, tumor grade and metastatic on survival were analyzed.
RESULTS: There was a direct correlation between the total number of nodes and the number of metastatic nodes (r: 0.319, p<0.0001). However, there was no correlation between metastatic and the total number of nodes (r: 0.0072, p: 0.354). Tumor location, size, depth of invasion, number of involved nodes and metastatic were found to be determinants of survival in univariate analysis. Cox regression analysis identified metastatic as the only independent prognostic factor.
CONCLUSIONS: A new staging system based on metastatic will be resistant to stage migration and will include the surgical approach in staging. However, further studies are required to determine appropriate cutoff values and the best approach to patients with less than 15 resected nodes.

Entities:  

Mesh:

Year:  2008        PMID: 18386233

Source DB:  PubMed          Journal:  Turk J Gastroenterol        ISSN: 1300-4948            Impact factor:   1.852


  4 in total

1.  Moving from lymph node metastasis in gastric cancer to biological markers: reply to letter.

Authors:  Naoto Fukuda
Journal:  World J Surg       Date:  2010-05       Impact factor: 3.352

2.  Comparison between artificial neural network and Cox regression model in predicting the survival rate of gastric cancer patients.

Authors:  Lucheng Zhu; Wenhua Luo; Meng Su; Hangping Wei; Juan Wei; Xuebang Zhang; Changlin Zou
Journal:  Biomed Rep       Date:  2013-07-18

3.  Prognostic significance of the metastatic lymph node ratio in gastric cancer patients.

Authors:  Naoto Fukuda; Yasuyuki Sugiyama; Akira Midorikawa; Hiroyuki Mushiake
Journal:  World J Surg       Date:  2009-11       Impact factor: 3.352

4.  Application of artificial neural network in predicting the survival rate of gastric cancer patients.

Authors:  A Biglarian; E Hajizadeh; A Kazemnejad; Mr Zali
Journal:  Iran J Public Health       Date:  2011-06-30       Impact factor: 1.429

  4 in total

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