An algorithm for expanding the TNM staging system

Dechang Chen, Matthew Timothy Hueman, Donald E. Henson, Arnold M. Schwartz

Research output: Contribution to journalArticlepeer-review

Abstract

Aim: We describe a new method to expand the tumor, lymph node, metastasis (TNM) staging system using a clustering algorithm. Cases of breast cancer were used for demonstration. Materials & methods: An unsupervised ensemble-learning algorithm was used to create dendrograms. Cutting the dendrograms produced prognostic systems. Results: Prognostic systems contained groups of patients with similar outcomes. The prognostic systems based on tumor size and lymph node status recapitulated the general structure of the TNM for breast cancer. The prognostic systems based on tumor size, lymph node status, histologic grade and estrogen receptor status revealed a more detailed stratification of patients when grade and estrogen receptor status were added. Conclusion: Prognostic systems from cutting the dendrogram have the potential to improve and expand the TNM.

Original languageEnglish (US)
Pages (from-to)1015-1024
Number of pages10
JournalFuture Oncology
Volume12
Issue number8
DOIs
StatePublished - Apr 1 2016
Externally publishedYes

Keywords

  • breast cancer
  • dendrogram
  • ensemble learning
  • hierarchical clustering
  • prognostic system
  • survival
  • TNM

ASJC Scopus subject areas

  • Oncology
  • Cancer Research

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