Abstract B78: Assessing breast cancer risk in Kenya: The feasibility of telemedicine utilization

Abstract

Abstract Introduction: By 2020, 70% of all cancer cases are expected to be in the least developed countries1. The current project explores the feasibility of telemedicine in addressing the growing burden of breast cancer in Kenya. Through the introduction of questions specifically designed to estimate a woman's risk of developing breast cancer, the resulting risk profile can inform physician recommendations for breast cancer screening and can also be influential in informing a woman's screening behaviors. The specific goals of this study are to develop and identify the strengths and limitations of a breast cancer risk questionnaire in the Kenyan context, to explore patient knowledge of breast cancer and identify potential barriers or patient resistance to completing the risk questionnaire, and to determine if Community Health Workers (CHWs) are the appropriate collectors of information. Methods: Expanding the women's health section of the a telemedicine system's patient interview permits both parties to understand a woman's estimated relative risk of developing breast cancer through a series of questions assessing a woman's exposure to disease-specific risk factors. With this tool, women at the greatest risk for developing the disease can understand their elevated risk and modify their screening behaviors accordingly. The Gail Model predicts a woman's relative risk for breast cancer as a function of the woman's age, race/ethnicity, her age at first menstruation and age at first live child birth, the number of first order relatives with breast cancer, and a woman's past history of breast disease2. This information was collected during the telemedicine consultation and it will be utilized in formulating a woman's relative risk profile. Results: A total of 246 women in Nyeri, Kenya provided oral responses to the breast cancer risk metric via CHWs. During recorded interviews with the CHWs who collected the information, the CHWs introduced the difficulties of collecting demographic data among this population. Often, women could not recall their current age or their age of first menstruation. Acquiring accurate marital status and educational attainment proved difficult. Of the 246 women, 23 (9.35%) reported a family history of breast cancer among first-order relatives. Further, 15 of the participants (6.01%) reported receiving a breast biopsy. Despite the high self-reported family history and breast biopsy among these rural, Kenyan women, the CHWs collecting the information shared concerns relating to the accuracy of these results. These findings may be biased due to misinterpretation of the diagnostic criteria and screening tools for breast cancer. Discussion: The complications associated with collecting demographic and breast health history information in rural Kenya potentially limit the ability of the breast cancer risk metric to identify meaningful differences in breast cancer risk among participants. Future research ought to assess the feasibility of using alternative culturally-appropriate demographic questions. CHWs involved in administering the questionnaire should first demonstrate their understanding of breast cancer screening and diagnosis processes and their ability to clearly communicate the distinctions to lay community members. 1Anderson, B.O., Yip, C.H., Smith, R.A., Shyyan, R., Sener, S.F., Eniu, A., Carlson, R.W., Azavedo, E. & Harford, J. (2008). Guideline implementation for breast healthcare in low-income and middle-income countries. Cancer, 113, 8, 2221-2243. 2Gail, M.H., Costantino, J.P., Pee, D., Bondy, M., Newman, L., Selvan, M., Anderson, G.L., Malone, K.E., Marchbanks, P.A., McCaskill-Stevens, W., Norman, S.A., Simon, M.S., Spirtas, R., Ursin, G., & Bernstein, L. (2007). Projecting Individualized Absolute Invasive Breast Cancer Risk in African American Women. Journal of the National Cancer Institute, 99, 23, 1782-1792. Citation Format: Katelyn R. Holmes. Assessing breast cancer risk in Kenya: The feasibility of telemedicine utilization. [abstract]. In: Proceedings of the Sixth AACR Conference: The Science of Cancer Health Disparities; Dec 6–9, 2013; Atlanta, GA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2014;23(11 Suppl):Abstract nr B78. doi:10.1158/1538-7755.DISP13-B78