An Algorithm for Creating Prognostic Systems for Cancer

  • Dechang Chen
  • Huan Wang
  • Li Sheng
  • Matthew T. Hueman
  • Donald E. Henson
  • Arnold M. Schwartz
  • Jigar A. Patel
Mobile Systems
Part of the following topical collections:
  1. Advances in Big-Data based mHealth Theories and Applications

Abstract

The TNM staging system is universally used for classification of cancer. This system is limited since it uses only three factors (tumor size, extent of spread to lymph nodes, and status of distant metastasis) to generate stage groups. To provide a more accurate description of cancer and thus better patient care, additional factors or variables should be used to classify cancer. In this paper we propose a hierarchical clustering algorithm to develop prognostic systems that classify cancer according to multiple prognostic factors. This algorithm has many potential applications in augmenting the data currently obtained in a staging system by allowing more prognostic factors to be incorporated. The algorithm clusters combinations of prognostic factors that are formed using categories of factors. The dissimilarity between two combinations is determined by the area between two corresponding survival curves. Groups from cutting the dendrogram and survival curves of the individual groups define our prognostic systems that classify patients using survival outcomes. A demonstration of the proposed algorithm is given for patients with breast cancer from the Surveillance, Epidemiology, and End Results (SEER) Program of the National Cancer Institute.

Keywords

TNM Survival Breast cancer Hierarchical clustering Area between curves Dendrogram Prognostic system 

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Copyright information

© Springer Science+Business Media New York (outside the USA) 2016

Authors and Affiliations

  • Dechang Chen
    • 1
  • Huan Wang
    • 2
  • Li Sheng
    • 3
  • Matthew T. Hueman
    • 4
  • Donald E. Henson
    • 1
    • 5
  • Arnold M. Schwartz
    • 6
    • 7
  • Jigar A. Patel
    • 8
  1. 1.Department of Preventive Medicine and BiostatisticsThe Uniformed Services University of the Health SciencesBethesdaUSA
  2. 2.Department of StatisticsThe George Washington UniversityWashingtonUSA
  3. 3.Department of MathematicsDrexel UniversityPhiladelphiaUSA
  4. 4.Surgical Oncology, John P. Murtha Cancer CenterWalter Reed National Military Medical CenterBethesdaUSA
  5. 5.Department of SurgeryThe Uniformed Services University of the Health SciencesBethesdaUSA
  6. 6.Department of PathologyThe George Washington University Medical CenterWashingtonUSA
  7. 7.Department of SurgeryThe George Washington University Medical CenterWashingtonUSA
  8. 8.Department of SurgeryWalter Reed National Military Medical CenterBethesdaUSA

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