||5R01CA251566-03 Interpret this number
||University Of Wisconsin-Madison
||Estimating and Mitigating Thyroid Cancer Overdiagnosis: a Mathematical Modeling Approach
This proposal will generate evidence to reduce the overdiagnosis of thyroid cancer in the United States.
Overdiagnosis is the identification of a disease that, had it not been detected, would be unlikely to cause
symptoms or death during a patient’s lifetime. Overdiagnosis has significant consequences, such as
overtreatment with associated side effects and complications, patient anxiety, and increased healthcare costs.
Despite a three-fold increase in thyroid cancer diagnoses since the late 1980s, the mortality rate remains
stable. Small papillary thyroid cancers, which are rarely lethal, are responsible for virtually the entire increase
in incidence. However, it is not safe to assume that all small thyroid cancers are overdiagnosed; some small
thyroid cancers can be aggressive and do need treatment. Effective methods are urgently needed to
understand the key factors contributing to thyroid cancer overdiagnosis, so that directed solutions can be
developed and implemented to reduce overdiagnosis. We propose the innovative use of systems engineering
and simulation modeling to address this knowledge gap and provide a nuanced understanding of the natural
history of thyroid tumors. We will use our model to identify the effect of reducing referrals for and use of thyroid
imaging on overdiagnosis; the effect of changing the size threshold for biopsy on overdiagnosis; and the
downstream impact of reducing overdiagnosis on harms and benefits of treatment. This approach also
accounts for differential use and improved precision of ultrasound over time. Our goal is to create and validate
a simulation model that quantifies overdiagnosis in thyroid cancer. We will engage stakeholders at all stages of
development, from model conception to validation, to elicit clinical guidance and inform our model inputs,
outcomes, and dissemination strategies. Our research team comprises an industrial-systems engineer with
expertise in cancer modeling, as well as experts in thyroid cancer, cancer epidemiology, health services
research, and communication. The multidisciplinary team is highly qualified to complete the three specific
aims: (1) Develop and validate a simulation model to quantify overdiagnosis of thyroid cancer in the US; (2)
Identify healthcare utilization patterns (e.g., provider encounters and referral decisions) that expose patients to
increased thyroid imaging, biopsies, and the overdiagnosis of thyroid cancer; (3) Engage key stakeholders
throughout the duration of the project to ensure that the model has face validity, and that the output can be
applied to questions important to both clinicians and policy makers. The proposed research aligns with the
National Cancer Institute’s mission to help people live longer and healthier lives. Results from this innovative
model will help to inform clinical practice guidelines and referral practice recommendations to improve
the quality of health care, while reducing inappropriate testing, to minimize overdiagnosis and
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