Grant Number:	5R01CA201198-04 Interpret this number
Primary Investigator:	Haymart, Megan
Organization:	University Of Michigan At Ann Arbor
Project Title:	Treatment Decision Making in Low-Risk Thyroid Cancer
Fiscal Year:	2019

Project Summary In the past 30 years, the incidence of thyroid cancer has tripled. The majority of the rise in thyroid cancer incidence is attributed to an increase in low-risk, well-differentiated thyroid cancer, a disease that has a 10-year mortality close to zero. Our previous work suggests that patients with low-risk thyroid cancer are at risk for overtreatment, defined as the use of surgical and medical interventions in the absence of a clear survival benefit. The overtreatment of thyroid cancer has inherent costs, both to patient health and to society. The reason for the intensive management and potential overtreatment of low-risk thyroid cancer remains unclear. By using SEER-linked patient and physician surveys, we plan to understand the treatment decision making in low-risk thyroid cancer. We hypothesize that knowledge and attitudes influence decision making. Specifically, we anticipate that lack of knowledge of risks of death, recurrence and treatment complications is associated with treatment that is more intensive. In addition, we postulate that a general preference for active treatment will also be associated with more intensive cancer treatment. Although both patient and physician perceptions of treatment need (i.e., knowledge and attitudes) likely contribute to treatment intensity, we anticipate that the primary driver will be physicians, even after controlling for their patients' perceptions. This study will serve as the foundation for future intervention studies. By identifying the specific role of physician and patient knowledge and attitudes toward thyroid cancer treatment, we will be able to create tailored educational interventions to personalize surgical and medical care for thyroid cancer patients, thus minimizing overtreatment and its inherent risks and costs. As the rising incidence, low mortality, and pattern of intensive treatment make thyroid cancer arguably the best cancer model for overtreatment, this proposed study will also serve as a model to understand overtreatment in other malignancies.