Hormonal Replacement Therapy for Breast Cancer Survivors: A Decision Analysis

Abstract

Since the overall risks and benefits of hormonal replacement therapy (HRT) in breast cancer survivors are not clearly established, and it is unlikely that a definitive answer will be available in the near future, we developed a decision analytic computer model for individualizing decisions, using the best available literature estimates for all currently known or suspected benefits and adverse outcomes. In addition, the model allows input of individual risk factors for breast cancer recurrence, coronary artery disease, osteoporosis, etc., and allows weighting of patients' preferences for these outcomes. We found that women at average risk for coronary heart disease (CHD) and hip fracture lose 4,3 quality-adjusted life months (QALMs) by taking HRT. Women who value the ClID and hip fracture states as having the worst impact on health and breast cancer recurrence as having the mildest impact on health lose the least from HRT, 3.6 QALMs. Women who value the CHD and hip fracture states as having the mildest impact and breast cancer recurrence as having the worst impact on health lose 5.3 QALMS. Therefore, unless future studies show a larger benefit on CHD mortality or other health states, HRT decisions for breast cancer surivors should include careful consideration of individual preferences for all of the potential outcomes. The model can readily incorporate data on new treatments and other outcomes as they become available.

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Document Details

Document Type
Technical Report
Publication Date
Aug 01, 2001
Accession Number
ADA405265

Entities

Organizations

  • Icahn School of Medicine at Mount Sinai

Tags

DTIC Thesaurus Topics

  • Alzheimer Disease
  • Biomedical Research
  • Breast Cancer
  • Cancer
  • Colon Cancer
  • Data Analysis
  • Diseases And Disorders
  • Health
  • Heart Diseases
  • Medical Personnel
  • Models
  • Myocardial Ischemia
  • Neoplasms
  • New York
  • Osteoporosis
  • Probability
  • Risk Factors

Fields of Study

  • Medicine

Readers

  • Computational Modeling and Simulation
  • Women's Health and Cancer Risk Research: African American Women and Pregnancy Outcomes.