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Functional maps of metastases from breast cancers: Proof of the principle that multidimensional scaling can summarize disease progression
World Journal of Surgery (2004)
  • Lincoln C Gray, James Madison University
  • J Vaidya
  • M Baum
  • R Badwe
  • I Mittra
  • T Siddiqui
  • D Wiarda
The mathematic technique of multidimensional scaling can create "functional maps" of metastases from breast cancer such that positions of organs in these maps are proportional to the probability of metastases. Areas that are likely to share disease are close together in a functional map, even though they may be physically distant, and vice versa. Two functional maps of breast cancers-one of local metastases to axillary levels I to III and another of distant metastases-are statistically significant and clinically meaningful. The maps accurately reflect the clinical data ( r > 0.97, p < 0.01), and so the progression of disease is revealed in simple visual summaries. As an analogy, the metastatic sites are like buoys on a fluid surface, and cancer spreads from a primary tumor like waves emanating from a point of impact on that surface. Metastases are predicted when the waves swamp the buoys. Because breast cancers do not always spread to the next nearest site, these functional maps do not resemble anatomic maps. The maps are a view of the body as "seen" by the tumor. Several well known clinical features are seen in these maps: most local metastases are to axillary level I; upper-inner primaries spread equally to levels II and III; in-transit metastases in the lymph and blood vessels do not follow the pattern of other distant metastases. Future functional maps can expand these summary diagrams to include biologic parameters (gene-expression profiles or endocrine response) and give valuable insights into patterns of recurrence in different populations.
  • Adult,
  • Aged,
  • Aged,
  • 80 and over,
  • Axilla,
  • Breast Neoplasms/pathology,
  • Disease Progression,
  • Female Humans,
  • Lymphatic Metastasis/pathology,
  • Middle Aged Models,
  • Statistical,
  • Neoplasm Metastasis
Publication Date
Citation Information
Gray, L., Vaidya, J., Baum, M., Badwe, R., Mittra, I., Siddiqui, T., & Wiarda, D. Functional Maps of Metastases from Breast Cancers: Proof of the Principle that Multidimensional Scaling can Summarize Disease Progression. World Journal of Surgery 28: 646-651, 2004.