Understanding and addressing rejection of personalized cancer risk information

PROJECT SUMMARY/ABSTRACT We are entering an era of precision medicine for cancer screening in which screening initiation and maintenance is based on personal risk estimates that incorporate multiple risk factors, with the goal of maximizing screening benefits and minimizing the harms. One increasingly common clinical application

involves using cancer risk prediction models to inform which patients are screened, how often they are screened, and at which ages screening occurs (i.e., risk-based screening). For breast cancer screening with mammography, the U.S. Preventive Services Task Force recommends informed choice about when to begin

regular screening for women age 40-49. Making an informed choice means determining whether, for an individual woman, the likelihood of receiving a screening benefit outweighs the likelihood of harms such as false positive results and overdiagnosis. A critical component of informed choice is a woman’s personal cancer

risk, because the expected benefit of screening depends on a woman’s personal risk of breast cancer, with women at lower risk being less likely to benefit and more likely to be harmed than women at higher risk. Hence, incorporating informed choice into the mammography screening decision-making process means that

women are asked to make decisions about screening based on their personalized breast cancer risk estimates. However, a critical barrier to implementing guideline-recommended informed choice in mammograpy screening is that many people reject that their risk estimate is true for them personally, a phenomenon we refer to as risk rejection. While previous research has focused on risk comprehension as a

high-impact target for improving medical decisions, we argue that risk rejection is also a high impact target for improving health decision making because people who reject their risk are unlikely to make health decisions based on that risk estimate, even when they comprehend the estimate. An estimated 1-in-4 women believe

that their breast cancer risk estimate is not accurate for them, and little is known about why, or the implications for screening decisions. In Aim 1, we will use a longitudinal survey to understand the scientific nature of risk rejection. Aim 1a will identify key demographic and psychological predictors of risk rejection. In particular, we

will test 4 theory-informed hypotheses about why people reject their risk: motivated reasoning, prior knowledge, distrust, and lack of perceived personal relevance. Aim 1b will identify the impact of risk rejection on risk-concordant screening behavior. In Aim 2, we will conduct interviews and use experiments to identify

communication strategies to reduce risk rejection. These studies will provide a comprehensive understanding of a phenomenon – risk rejection – which, if not addressed, will impede the implementation of informed patient choice in breast cancer screening and personalized, risk-based medicine more broadly.