# Preference-Based Treatment Valuation in Low-Risk Thyroid Cancer

> **NIH NIH K08** · UNIVERSITY OF MARYLAND BALTIMORE · 2024 · $279,039

## Abstract

Summary/Abstract:
This Career Development Award (K08) establishes health state utilities across several established and evolving
therapies for low-risk, sub-centimeter thyroid cancer (papillary thyroid microcarcinoma, PTMC). While survival
for PTMC is favorable, its treatment can incur substantial morbidity and societal costs. Acceptable treatments
include active surveillance, partial or total thyroidectomy, and radiofrequency ablation. Due to the disease's
excellent prognosis, it is unlikely that these treatments would yield meaningful differences in survival, however
post-treatment experiences are different. Thus, treatment value is largely driven by patients' perceptions and
preferences regarding the treatment experience. This value may be estimated through stated-preference
instruments that define the utility of pre-defined health states. Thus far, there is little data on health state utilities
in PTMC, and it is unclear whether patients, clinicians, or the general population are the most suitable participants
for studies that estimate utility. The candidate will address these knowledge gaps by estimating the utilities of a
series of PTMC clinical vignettes using a time trade-off preference-based instrument. These utilities will then be
incorporated into a Markov cost-effectiveness model comparing surgical and non-surgical options. Specifically,
the candidate will test the following hypotheses: 1) average utility for the active surveillance health state is non-
inferior to that of partial thyroidectomy, 2) treatment complications significantly reduce utility, 3) general
population respondents significantly underestimate thyroid cancer utilities relative to experienced patients and
healthcare workers, and 4) active surveillance is more cost-effective for the management of PTMC than surgery
or radiofrequency ablation. The long-term objective of this research is to establish preference-based health state
utilities that can be used in health economics research to optimize resource allocation in thyroid cancer. Following
a clinical fellowship in surgical oncology, the candidate was appointed Assistant Professor of surgery at the
University of Maryland Baltimore. He has since partnered with scientific mentor C. Daniel Mullins, PhD, to engage
with patient and physician stakeholders in health services research. This K08 is designed to transition to research
independence through graduate level training in survey design, patient-centered outcomes, biostatistics, and
health policy. Additional professional courses will address research career development and health technology
assessment. The application draws upon resources through the school of medicine's department of surgery and
the school of pharmacy. With the advanced training afforded by the K08, the candidate will be positioned to
submit a competitive R01 application.

## Key facts

- **NIH application ID:** 10947007
- **Project number:** 1K08CA293167-01
- **Recipient organization:** UNIVERSITY OF MARYLAND BALTIMORE
- **Principal Investigator:** Yinin Hu
- **Activity code:** K08 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $279,039
- **Award type:** 1
- **Project period:** 2024-07-17 → 2028-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10947007

## Citation

> US National Institutes of Health, RePORTER application 10947007, Preference-Based Treatment Valuation in Low-Risk Thyroid Cancer (1K08CA293167-01). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10947007. Licensed CC0.

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