Prophylactic mastectomy and oophorectomy for women at risk of breast and ovarian cancer: Incorporating preferences in a decision analysis

Charlotte Cheng-Ling Sun, The University of Texas School of Public Health

Abstract

The discoveries of the BRCA1 and BRCA2 genes have made it possible for women of families with hereditary breast/ovarian cancer to determine if they carry cancer-predisposing genetic mutations. Women with germline mutations have significantly higher probabilities of developing both cancers than the general population. Since the presence of a BRCA1 or BRCA2 mutation does not guarantee future cancer development, the appropriate course of action remains uncertain for these women. Prophylactic mastectomy and oophorectomy remain controversial since the underlying premise for surgical intervention is based more upon reduction in the estimated risk of cancer than on actual evidence of clinical benefit. Issues that are incorporated in a woman's decision making process include quality of life without breasts, ovaries, attitudes toward possible surgical morbidity as well as a remaining risk of future development of breast/ovarian cancer despite prophylactic surgery. The incorporation of patient preferences into decision analysis models can determine the quality-adjusted survival of different prophylactic approaches to breast/ovarian cancer prevention. Monte Carlo simulation was conducted on 4 separate decision models representing prophylactic oophorectomy, prophylactic mastectomy, prophylactic oophorectomy/mastectomy and screening. The use of 3 separate preference assessment methods across different populations of women allows researchers to determine how quality adjusted survival varies according to clinical strategy, method of preference assessment and the population from which preferences are assessed.

Subject Area

Public health|Oncology|Surgery

Recommended Citation

Sun, Charlotte Cheng-Ling, "Prophylactic mastectomy and oophorectomy for women at risk of breast and ovarian cancer: Incorporating preferences in a decision analysis" (2001). Texas Medical Center Dissertations (via ProQuest). AAI3027655.
https://digitalcommons.library.tmc.edu/dissertations/AAI3027655

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