Prognostic Factors in Breast Cancer.

Abstract

The independent value of gross and histologic examination, S-phase determination, microvessel density and immunohistochemical expression of epidermal growth factor receptor (egfr), her2lneu, Ki-67 (a proliferation marker), estrogen and progesterone receptor status and p53 accumulation are being determined using a cohort of 1000 women who underwent biopay or mastectomy between 1970 and 1980 and on whom vital status has been obtained. Following accumulation of the complete data set, the relationship between survival and each of these variables will be determined using a proportional hazards model, as will the independent value of each of these prognostic indicators. In addition, the use of a backpropagation neural network model for improving prognostic statements will be explored.

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 1995
Accession Number
ADA299729

Entities

People

  • Jeffery Seidman

Organizations

  • Armed Forces Institute of Pathology

Tags

Communities of Interest

  • Human Systems

DTIC Thesaurus Topics

  • Alcohols
  • Biomedical Research
  • Breast Cancer
  • Cancer
  • Cell Physiological Processes
  • Chemistry
  • Database Management Systems
  • Databases
  • Diseases And Disorders
  • Drug Therapy
  • Health Services
  • Information Science
  • Lymph Nodes
  • Materials
  • Medical Personnel
  • Neoplasms
  • Surgery

Readers

  • Neural Network Machine Learning.
  • Oncology (Cancer Research).
  • Women's Health and Cancer Risk Research: African American Women and Pregnancy Outcomes.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference