An algorithm for expanding the TNM staging system. (April 2016)

• Record Type: Journal Article
• Authors: Chen, Dechang; Hueman, Matthew T; Henson, Donald E; Schwartz, Arnold M
• Is Part Of: Future oncology. Volume 12:Number 8(2016)
• Page Start: 1015
• Page End: 1024
• Publication Date: 2016-04
• Subjects: breast cancer -- dendrogram -- ensemble learning -- hierarchical clustering -- prognostic system -- survival -- TNM; Oncology -- Periodicals; 616.99405
• DOI: 10.2217/fon.16.5
• Languages: English
• ISSNs: 1479-6694

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.