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Negative node count improvement prognostic prediction of the seventh edition of the TNM classification for gastric cancer.

Authors :
Deng J
Zhang R
Zhang L
Liu Y
Hao X
Liang H
Source :
PloS one [PLoS One] 2013 Nov 07; Vol. 8 (11), pp. e80082. Date of Electronic Publication: 2013 Nov 07 (Print Publication: 2013).
Publication Year :
2013

Abstract

Objective: To demonstrate that the seventh edition of the tumor-node-metastasis (TNM) classification for gastric cancer (GC) should be updated with the number of negative lymph nodes for the improvement of its prognostic prediction accuracy.<br />Methods: Clinicopathological data of 769 GC patients who underwent curative gastrectomy with lymphadenectomy between 1997 and 2006 were retrospectively analyzed to demonstrate the superiority of prognostic efficiency of the seventh edition of the TNM classification, which can be improved by combining the number of negative lymph nodes.<br />Results: With the Cox regression multivariate analysis, the seventh edition of the TNM classification, the number of negative nodes, the type of gastrectomy, and the depth of tumor invasion (T stage) were identified as independent factors for predicting the overall survival of GC patients. Furthermore, we confirmed that the T stage-N stage-number of negative lymph nodes-metastasis (TNnM) classification is the most appropriate prognostic predictor of GC patients by using case-control matched fashion and multinominal logistic regression. Finally, we were able to clarify that TNnM classification may provide more precise survival differences among the different TNM sub-stages of GC by using the measure of agreement (Kappa coefficient), the McNemar value, the Akaike information criterion, and the Bayesian Information Criterion compared with the seventh edition of the TNM classification.<br />Conclusion: The number of negative nodes, as an important prognostic predictor of GC, can improve the prognostic prediction efficiency of the seventh edition of the TNM classification for GC, which should be recommended for conventional clinical applications.

Details

Language :
English
ISSN :
1932-6203
Volume :
8
Issue :
11
Database :
MEDLINE
Journal :
PloS one
Publication Type :
Academic Journal
Accession number :
24348906
Full Text :
https://doi.org/10.1371/journal.pone.0080082