Literature DB >> 28280604

The anatomy of the TNM for colon cancer.

Donald E Henson1, Matthew T Hueman2, Dechang Chen1, Jigar A Patel3, Huan Wang4, Arnold M Schwartz5.   

Abstract

BACKGROUND: To visualize the anatomy as revealed by dendrograms of the tumor, lymph node, and metastasis (TNM) staging system for colon cancer and compare it with the Dukes' system.
METHODS: A hierarchical clustering algorithm generated tree-structured dendrograms that stratified patients according to survival only. The dendrograms were constructed with the same prognostic variables used for the TNM. Because combinations of prognostic factors were stratified only on survival, additional factors of any number and type could be integrated into the TNM without changing the TNM categories.
RESULTS: The algorithm provided a step-by-step visualization of the TNM and the Dukes' system for colon cancer. Dendrograms and associated 5-year survival rates were generated for the T category only, the N category only, the T, N combination, and combinations of the T, N, and M, and the T, N, M with histological grade. Dendrograms revealed visual differences between the structure of TNM and the Dukes' system of staging. Dendrograms also revealed how variations in prognostic factors changed survival. By cutting dendrograms along their dissimilarity axis, multiple prognostic subgroups could be created for colon cancer that may reflect outcomes that are more accurate to estimate.
CONCLUSIONS: Dendrograms provide a new way to view cancer patient staging. They reveal a visual step-by-step hierarchical relationship between survival rates and combinations of prognostic variables. The dendrograms also revealed fundamental differences between the TNM and the Dukes system of staging. By stratifying on survival only, additional factors including molecular factors can be added to the TNM, because it classifies patients according to survival rates only and not according to pre-set rules of prognostic factors and stage groups. The clinical implications of stratifying only survival are discussed.

Entities:  

Keywords:  Colon cancer; dendrograms; hierarchical clustering; prognostic groups; staging

Year:  2017        PMID: 28280604      PMCID: PMC5334064          DOI: 10.21037/jgo.2016.11.10

Source DB:  PubMed          Journal:  J Gastrointest Oncol        ISSN: 2078-6891


  8 in total

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Authors:  M W Kattan; V Reuter; R J Motzer; J Katz; P Russo
Journal:  J Urol       Date:  2001-07       Impact factor: 7.450

2.  An algorithm for expanding the TNM staging system.

Authors:  Dechang Chen; Matthew T Hueman; Donald E Henson; Arnold M Schwartz
Journal:  Future Oncol       Date:  2016-02-24       Impact factor: 3.404

3.  Development and validation of a nomogram for predicting survival in patients with resected non-small-cell lung cancer.

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Journal:  J Clin Oncol       Date:  2015-01-26       Impact factor: 44.544

4.  The clinical implications of integrating additional prognostic factors into the TNM.

Authors:  Donald Earl Henson; Arnold M Schwartz; Dechang Chen; Dengyuan Wu
Journal:  J Surg Oncol       Date:  2013-12-11       Impact factor: 3.454

5.  The American Joint Committee on Cancer. Criteria for prognostic factors and for an enhanced prognostic system.

Authors:  H B Burke; D E Henson
Journal:  Cancer       Date:  1993-11-15       Impact factor: 6.860

6.  Thin primary cutaneous malignant melanoma: a prognostic tree for 10-year metastasis is more accurate than American Joint Committee on Cancer staging.

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Journal:  J Clin Oncol       Date:  2004-08-09       Impact factor: 44.544

7.  Improved prediction of recurrence after curative resection of colon carcinoma using tree-based risk stratification.

Authors:  Martin Radespiel-Tröger; Werner Hohenberger; Bertram Reingruber
Journal:  Cancer       Date:  2004-03-01       Impact factor: 6.860

8.  Developing prognostic systems of cancer patients by ensemble clustering.

Authors:  Dechang Chen; Kai Xing; Donald Henson; Li Sheng; Arnold M Schwartz; Xiuzhen Cheng
Journal:  J Biomed Biotechnol       Date:  2009-06-23
  8 in total
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2.  Identification of key pathways and genes in colorectal cancer to predict the prognosis based on mRNA interaction network.

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  2 in total

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