Breast cancer is a disease in which early detection significantly increases survival, and where prophylactic strategies can decrease the risk of developing breast cancer by up to 90%. Individuals at high risk face a lifetime probability of developing breast cancer eight times greater than the average population risk. Furthermore, the costs of treating early stages of breast cancer are considerably less than the costs of treating advanced stages. However, prophylaxis is often postponed until an individual acquires information that necessitates this course of action, which may not occur at an early enough point in time. Thus, this not only affects the individual's probability of survival, but also drains health care funds which must then be used to treat advanced breast cancer, but could otherwise have been diverted elsewhere. This paper analyses whether high-risk populations (such as Ashkenazi Jewish women) should be routinely tested for BRCA1/2 mutations. The analysis incorporates different probabilities of developing breast cancer, the costs of treatment and the quality of life in various health states to assess whether it is indeed cost-effective to screen certain populations. This is presented as a decision analysis (using DATA software), following expected utility theory, where decisions are made under uncertainty.
Learning Objectives: At the conclusion of the session, the learner will be able to: (1) construct decision trees, integrating different health states and their probabilities; (2) assess medical information that involves uncertainty; (3) Identify explicitly the optimal strategy among various other strategies, and realize why it is optimal
Keywords: Breast Cancer Screening, Decision-Making
Presenting author's disclosure statement:
Organization/institution whose products or services will be discussed: None
I do not have any significant financial interest/arrangement or affiliation with any organization/institution whose products or services are being discussed in this session.