Clinical risk assessment holds great promise for identifying individuals who might benefit from preventive interventions. In the case of breast cancer, statistical and genetic models, including the Gail and Claus models, have been developed to assess an individual woman's future risk of developing disease. However, no more than 55% of breast cancer occurrence can be explained by currently recognized risk factors, and there is substantial controversy about how to translate risk information into prevention and control measures.
In light of these uncertainties, ethical concerns have been raised about appropriate use of these models. What criteria should be applied in weighing the risks and potential benefits of models for individualized risk assessment? What obligations do scientists and clinicians have for disclosing uncertainty and communicating the limitations of results?
I argue that the profound uncertainties surrounding breast cancer risk modeling warrant caution in their application. The fact that breast cancer is a significant source of anxiety for many women suggests that the potential harms from misinformation are substantial. Breast cancer risk assessment tools occupy a grey area between public health education and individualized clinical attention. When public health officials promise individualized risk information, there is potential for women to place too much importance nd trust in these risk estimates. Currently, these tools are being made available directly to patients with inadequate explanation of the limitations of the results. Moreover, their use in counseling women about participation in clinical trials raises concerns about informed consent.
Learning Objectives: N/A
Keywords: Genetics, Risk Assessment
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.