# Thyroid Nodule Treatment Optimization: A Personalized Approach

> **NIH NIH R37** · MASSACHUSETTS GENERAL HOSPITAL · 2022 · $502,816

## Abstract

Project Summary / Abstract
 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 ½ 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.

## Key facts

- **NIH application ID:** 10475609
- **Project number:** 5R37CA231957-04
- **Recipient organization:** MASSACHUSETTS GENERAL HOSPITAL
- **Principal Investigator:** Carrie Elizabeth Cunningham
- **Activity code:** R37 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $502,816
- **Award type:** 5
- **Project period:** 2019-08-01 → 2024-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10475609

## Citation

> US National Institutes of Health, RePORTER application 10475609, Thyroid Nodule Treatment Optimization: A Personalized Approach (5R37CA231957-04). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10475609. Licensed CC0.

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