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Published in: BMC Cancer 1/2018

Open Access 01-12-2018 | Research article

The lymph node status as a prognostic factor in colon cancer: comparative population study of classifications using the logarithm of the ratio between metastatic and nonmetastatic nodes (LODDS) versus the pN-TNM classification and ganglion ratio systems

Authors: Carlos Fortea-Sanchis, David Martínez-Ramos, Javier Escrig-Sos

Published in: BMC Cancer | Issue 1/2018

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Abstract

Background

pN stage in the TNM classification has been the “gold standard” for lymph node staging of colorectal carcinomas, but this system recommends collecting at least 12 lymph nodes for the staging to be reliable. However, new prognostic staging systems have been devised, such as the ganglion quotients or lymph node ratios and natural logarithms of the lymph node odds methods. The aim of this study was to establish and validate the predictive and prognostic ability of the lymph node ratios and natural logarithms of the lymph node odds staging systems and to compare them to the pN nodal classification of the TNM system in a population sample of patients with colon cancer.

Methods

A multicentric population study between January 2004 and December 2007. The inclusion criteria were that the patients were: diagnosed with colon cancer, undergoing surgery with curative intent, and had a complete anatomopathological report. We excluded patients with cancer of the rectum or caecal appendix with metastases at diagnosis. Survival analysis was performed using the Kaplan–Meier actuarial method and the Log-Rank test was implemented to estimate the differences between groups in terms of overall survival and disease-free survival. Multivariate survival analysis was performed using Cox regression.

Results

We analysed 548 patients. For the overall survival, the lymph node ratios and natural logarithms of the lymph node odds curves were easier to discriminate because their separation was clearer and more balanced. For disease-free survival, the discrimination between the pN0 and pN1 groups was poor, but this phenomenon was adequately corrected for the lymph node ratios and natural logarithms of the lymph node odds curves which could be sufficiently discriminated to be able to estimate the survival prognosis.

Conclusions

Lymph node ratios and natural logarithms of the lymph node odds techniques can more precisely differentiate risk subgroups from within the pN groups. Of the three methods tested in this study, the natural logarithms of the lymph node odds was the most accurate for staging non-metastatic colon cancer. Thus helping to more precisely adjust and individualise the indication for adjuvant treatments in these patients.
Literature
26.
go back to reference Edler D, Ohrling K, Hallstrom M, Karlberg M, Ragnhammar P. The number of analyzed lymph nodes a prognostic factor in colorectal cancer. Acta Oncol. 2007;46:975–81.CrossRefPubMed Edler D, Ohrling K, Hallstrom M, Karlberg M, Ragnhammar P. The number of analyzed lymph nodes a prognostic factor in colorectal cancer. Acta Oncol. 2007;46:975–81.CrossRefPubMed
Metadata
Title
The lymph node status as a prognostic factor in colon cancer: comparative population study of classifications using the logarithm of the ratio between metastatic and nonmetastatic nodes (LODDS) versus the pN-TNM classification and ganglion ratio systems
Authors
Carlos Fortea-Sanchis
David Martínez-Ramos
Javier Escrig-Sos
Publication date
01-12-2018
Publisher
BioMed Central
Published in
BMC Cancer / Issue 1/2018
Electronic ISSN: 1471-2407
DOI
https://doi.org/10.1186/s12885-018-5048-4

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