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Mapping Patient Decision-making in Thyroid Cancer

University of California, Los Angeles · 2028
ClinicalTrials.gov · Datasets · License: Public Domain · 2028
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The incidence of thyroid cancer has exploded in the past 5 decades, with a roughly three-fold increase since 1995. Fortunately, many new cases are small, early-stage thyroid cancers. The American Thyroid Association guidelines state that patients with papillary thyroid cancers less than 4 cm can choose either thyroid lobectomy or total thyroidectomy. However, it is unclear why patients will sometimes choose more aggressive treatments that carry additional operative risk when a less aggressive option is available. When investigators examined thyroid specialists' recommendations for thyroid cancer treatment, investigators found significant variation between physicians' risk estimates and their treatment recommendations. This illustrated that patients may receive inconsistent counseling regarding their diagnosis and treatment options from different providers. Worse yet, other studies have shown that patients often do not perceive a choice in their treatment. When patients undergo treatments that do not align with their own priorities and values, they may experience regret and low satisfaction. Decision aids have been shown to help patients feel more educated about their options but have not had an effect on their treatment choice, decision regret, or satisfaction. The aim of this study is to use an ethnographic approach to map the patient decision-making process and develop a Decision Navigation Tool to improve decision outcomes for thyroid cancer patients. An ethnographic approach seeks to understand the social norms, culture, and context that influence these decisions. Investigators will do so in 3 phases: 1) elicit patient decision criteria in selecting initial treatment for thyroid cancer, 2) construction and validation of decision-tree model for initial treatment of thyroid cancer, and 3) pilot randomized controlled trial of a Decision Navigation Tool. To construct the decision model, investigators will recruit a diverse sample of patients with varying age, gende
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