Does Physician Description of Therapeutic Options Influence Breast Cancer Patient Treatment Choice?

Abstract

Patients with metastatic breast cancer frequently undergo aggressive therapies that have an uncertain quality-adjusted survival advantage. Framing theory suggests that individuals may not maximize their expected utility if presented with treatment options described in a negative manner. as opposed to the same information described in a positive manner. We developed an instrument to assess information framing and tested it in a pilot survey of oncologists who offer stem-cell transplant therapy to their patients. The framing instrument was evaluated by assessing agreement between coders. Analysis of pilot data included descriptive statistics, logistic and log-linear regression of the recommendation of aggressive treatment across three scenarios and the use of content and context in treatment recommendation on physician characteristics and practice patterns. In univariate analysis physicians who recommended stem cell transplantation in all three cases were likely to do so to improve survival ("<0.001) and those who did not recommend stem cell transplantation in all cases were more likely to recommend an alternative treatment to improve quality of life ("<0.02). Preliminary analysis indicates that physician characteristics, practice characteristics and scenario treatment recommendations are related to the phrasing of treatment options for patients with metastatic breast cancer.

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Document Details

Document Type
Technical Report
Publication Date
Jul 29, 1995
Accession Number
ADA299273

Entities

People

  • K. F. Gold
  • K. R. Yabroff
  • Kevin A. Schulman
  • L. E. Rubenstein
  • N. J. Meropol

Organizations

  • Georgetown University

Tags

DTIC Thesaurus Topics

  • Biomedical Research
  • Bone Marrow
  • Breast Cancer
  • Cells
  • Chemotherapy
  • Diseases And Disorders
  • Laboratory Animals
  • Materials
  • Medical Personnel
  • Neoplasms
  • Oncology
  • Physicians
  • Quality Of Life
  • Social Sciences
  • Stem Cells
  • Surveys
  • Transplants

Fields of Study

  • Medicine

Readers

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

Technology Areas

  • Biotechnology