P4-10-04: Automated Breast Cancer Risk Assessment: Identifying High Risk Women in the Primary Care Setting.
Authors: E Ozanne, Z Omer, K Carlson
Journal: Cancer Research (2011)

Abstract Background: Despite the availability of risk assessment tools and risk-reducing interventions, high risk women are not routinely identified in clinical practice, and the few that are, rarely choose interventions — often due to misperception of risk. Identification of patients at risk needs to begin in the primary care setting, rather than the breast health specialty world. To accomplish this, we developed a web-based tool that provides automated risk assessment and personalized decision support designed for collaborative use between patients and clinicians in the primary care setting. We assessed the feasibility and efficacy of using this tool in a primary care clinic at an academic hospital to identify women at high. Methods: Women aged 40 to 65 years of age were recruited from a schedule of patients attending annual physicals at a primary care clinic in an academic hospital. Patients with a history of breast cancer, genetic testing, or chemoprevention education were excluded. Information used to assess breast cancer risk was gathered from medical record review and phone interviews when necessary. Risk assessment was performed on all patients using four risk assessment models (Gail, Claus, BRCAPRO, and BCSC Density). Patients were randomized to view the decision aid either before their appointment or with their PCP during their appointment. Prior to each visit, providers received a risk report that summarized patient risk and recommended referrals. Outcomes were gathered from surveys administered to patients before and after appointments, and to providers after appointments. Results: Over 4-months, 98 women were approached to reach the enrollment goal of 60 women (61%). 24/60 (40%) patients were identified to be high risk for breast cancer using standard high risk thresholds. 9/60 (15%) of patients fit criteria for referral to genetic counseling, while 15/60 (25%) fit the criteria for referral to a BC specialist. Out of the 24 patients who fit the referral criteria, 17 (71%) were referred to a high risk clinic by their PCPs. 9/17 (53%) patients followed through in scheduling the appointment within 4 months of the referral date. The PCPs’ perceptions of these patients’ risk was in line with the calculated risk for 21 (88%) of the patients. A discussion regarding breast cancer risk reduction occurred with 22/24 (92%) of these patients during the visit, while the PCPs chose to use the decision aid with only 13/24 (54%) of them. PCP chose to view the decision aid during the visit with more high risk patients than average risk patients (p=0.04). Use of the DA during the appointment did not alter provider satisfaction with visit. A majority of patients thought the DA was helpful in making a decision and would recommend it to women like them. Conclusions: Performing personalized risk assessment and use of the decision aid in the primary care setting was feasible and acceptable. These results suggest risk assessment alone may be enough to encourage a discussion about breast cancer risk reduction for some providers. This method of risk assessment and decision support holds promise in the effort to reduce the incidence and burden of breast cancer. Citation Information: Cancer Res 2011;71(24 Suppl):Abstract nr P4-10-04.