Literature DB >> 19670457

Why cancer at the primary site and in the lymph nodes contributes to the risk of cancer death.

James S Michaelson1, L Leon Chen, Melvin J Silverstein, Justin A Cheongsiatmoy, Martin C Mihm, Arthur J Sober, Kenneth K Tanabe, Barbara L Smith, Jerry Younger.   

Abstract

BACKGROUND: : Cancer at both the primary site and in the lymph nodes is associated with lethality, although the mechanism by which lethality arises from each site has been poorly understood. For breast carcinoma, each positive lymph node contributes an approximately 6% risk of death, and each millimeter of primary tumor greatest dimension contributes approximately 1%; whereas, for melanoma, each positive lymph node contributes an approximately 23% risk, and each millimeter of tumor thickness contributes approximately 8%: This is described by a pair of linked equations, the Size+Nodes method.
METHODS: : A simple expression, the ProbabilityEstimation equation, which was derived from the authors' binary-biologic model of cancer metastasis, was used to calculate the probabilities of spread of cancer cells from data on tumor size, lymph node status, and death rate.
RESULTS: : In this report, the authors demonstrated, that when similar masses of cancer are compared, the chance of lethal spread of a cancer cell to the periphery is approximately the same whether the spread emerges from a lymph node or from the primary site. The greater the number of cells at the primary site (tumor size) or the greater the number of cells in the lymph nodes (number of positive lymph nodes), the greater is the aggregate chance that 1 or more cells has undergone a lethal event of spread, a process captured by the Size+Nodes equations.
CONCLUSIONS: : The lethal contributions of cancer at the primary site and lymph nodes can be explained by a simple mechanical process of the spread of cancer cells occurring with definable probabilities per cell. The presence of cancer in the lymph nodes does not indicate an intrinsic change in a malignancy but, rather, an increased mass of cancer from which spread can emerge. Cancer 2009. (c) 2009 American Cancer Society.

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Mesh:

Year:  2009        PMID: 19670457     DOI: 10.1002/cncr.24542

Source DB:  PubMed          Journal:  Cancer        ISSN: 0008-543X            Impact factor:   6.860


  8 in total

1.  The expression of HIF-1α in primary hepatocellular carcinoma and its correlation with radiotherapy response and clinical outcome.

Authors:  Zuo-Lin Xiang; Zhao-Chong Zeng; Jia Fan; Zhao-You Tang; Jian He; Hai-Ying Zeng; Joe Y Chang
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Review 2.  The impact of hypoxia in hepatocellular carcinoma metastasis.

Authors:  Carmen Chak-Lui Wong; Alan Ka-Lun Kai; Irene Oi-Lin Ng
Journal:  Front Med       Date:  2013-11-14       Impact factor: 4.592

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Authors:  Emily C Zabor; Daniel Coit; Jeffrey E Gershenwald; Kelly M McMasters; James S Michaelson; Arnold J Stromberg; Katherine S Panageas
Journal:  Ann Surg Oncol       Date:  2018-02-22       Impact factor: 5.344

4.  Cathepsin B: a potential prognostic marker for inflammatory breast cancer.

Authors:  Mohamed A Nouh; Mona M Mohamed; Mohamed El-Shinawi; Mohamed A Shaalan; Dora Cavallo-Medved; Hussein M Khaled; Bonnie F Sloane
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5.  Model for in vivo progression of tumors based on co-evolving cell population and vasculature.

Authors:  Sehyo C Choe; Guannan Zhao; Zhenyuan Zhao; Joseph D Rosenblatt; Hyun-Mi Cho; Seung-Uon Shin; Neil F Johnson
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6.  Inherent variability of cancer-specific aneuploidy generates metastases.

Authors:  Mathew Bloomfield; Peter Duesberg
Journal:  Mol Cytogenet       Date:  2016-12-16       Impact factor: 2.009

7.  Consolidated mathematical growth model of the primary tumor and secondary distant metastases of breast cancer (CoMPaS).

Authors:  Ella Ya Tyuryumina; Alexey A Neznanov
Journal:  PLoS One       Date:  2018-07-06       Impact factor: 3.240

8.  Hyperlipidemia and hyper glycaemia in Breast Cancer Patients is related to disease stage.

Authors:  Uzma Raza; Mahay Rookh Asif; Asif Bin Rehman; Aminuddin Sheikh
Journal:  Pak J Med Sci       Date:  2018 Jan-Feb       Impact factor: 1.088

  8 in total

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