Thyroid nodules, present in over 30% of the U.S. population, are associated with significant morbidity and health resource utilization. Thyroid cancer currently affects over million Americans. A reported increasing incidence is primarily attributed to the diagnosis of indolent papillary thyroid carcinoma (PTC) that has led to changes in clinical guidelines to less aggressive interventions. There is a critical need to identify the minority of patients with in increasing incidence of aggressive disease, while minimizing over-treatment in those patients with indolent PTC. Despite the public health impact thyroid nodule disease, few data exist on the impact of our clinical strategies and conducting clinical trials in this population is prohibitively time-consuming and costly. Our overarching goals are to enhance the health and minimize harm to the large number of patients with thyroid nodules. The specific objective of this proposal is to harness a comprehensive computer model to simulate individuals with benign and malignant nodules in the U.S. population to identify optimal personalized treatment approaches. This proposal builds on three tenets: First, contemporary research considers thyroid cancer in isolation from the more common benign nodular disease, missing the impact of the morbidity and cost associated with identifying those cancers. Secondly, there is a direct correlation between screening and diagnosis of thyroid cancer. It is imperative to consider the underlying reservoir of disease when assessing the effects of potential diagnostic and surveillance strategies. Lastly, while recent shifts in practice have been towards less aggressive management to minimize over- treatment, there is the potential to miss small, potentially lethal, thyroid cancer subtypes. The applicant is an Early Stage Investigator with expertise in thyroid nodular disease. Our team of a multidisciplinary group of experts, including decision scientists and statisticians will refine and expand on our mathematical model that simulates the pre-clinical course of both benign and malignant thyroid nodules (Aim 1) to identify the effectiveness of diagnostic biomarkers to guide treatment strategies (Aim 2) and assess the impact of risk-stratified surveillance approaches to patients with both thyroid nodular disease (Aim 3). Successful completion of the aims will inform our understanding of the health and economic consequences of our current clinical practices in the treatment of patients with thyroid nodular disease. Ultimately, we will identify patient management strategies that will identify aggressive disease while reducing morbidity both from recurrent disease and ineffective medical and surgical interventions.

Public Health Relevance

One-third of the U.S. population has a detectable thyroid nodule and thyroid cancer is increasing in incidence and prevalence; yet the effects of current and emerging clinical practice on patients and related health care utilization are unknown. The proposed comprehensive simulation model of individuals with benign and malignant thyroid nodules in the U.S. population is a powerful, systematic approach to evaluating the impact of recent changes in practice guidelines and future advancements in the diagnosis, treatment, and surveillance strategies on patients with thyroid nodules and cancer. The insights gained through the proposed aims will identify strategies that have the most promise for increasing both length and quality of life, while enhancing the health and minimizing harm to our patients.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Method to Extend Research in Time (MERIT) Award (R37)
Project #
5R37CA231957-02
Application #
9973183
Study Section
Health Services Organization and Delivery Study Section (HSOD)
Program Officer
Mckee, Tawnya C
Project Start
2019-08-01
Project End
2024-07-31
Budget Start
2020-08-01
Budget End
2021-07-31
Support Year
2
Fiscal Year
2020
Total Cost
Indirect Cost
Name
Massachusetts General Hospital
Department
Type
DUNS #
073130411
City
Boston
State
MA
Country
United States
Zip Code
02114