Abstract
Background: Due to the excellent prognosis and relatively high incidence of small low-risk thyroid cancers, more conservative management strategies such as active surveillance (AS) or hemithyroidectomy (HT) may be preferable to total thyroidectomy (TT) for patients seeking to balance long-term survival rates with the potential adverse effects of overtreatment. The aim of this review was to synthesize key factors or variables that inform patient decision making about treatment for low-risk thyroid cancer, from current primary investigations that presented participants with information facilitating this choice. Methods: Studies were identified from the Medline, Cochrane, and Embase databases up until March 2022. Study characteristics were extracted into a pre-piloted form. Factors were hypothesized to include treatment-related risks and possible outcomes and identified from a review of studies with consensus by discussion. Results: The search identified 444 unique studies: 397 were excluded on review of abstract and title with 47 studies undergoing a full text review and 6 studies identified to be eligible. Four were cross-sectional: one a prospective cohort study and one a mixed-methods study with both a prospective observational and qualitative component. The decisions addressed included: the choice between AS versus surgery (HT and/or TT) and HT versus TT and enrolled participants ranging from healthy volunteers to thyroid cancer patients. Treatment choice was the primary outcome in five studies. Across the studies, participants who were given the option of AS or surgery predominately chose the more conservative pathway, with a range of 70-84%. The major factors represented by information provision in the studies were risk of cancer recurrence or spread, need for hormone replacement therapy, and voice change. Conclusions: A framework of key factors informing patient treatment choice may be derived from current studies involving information provision for low-risk thyroid cancer management. Further research evaluating the efficacy and optimal timing for decision support interventions would help inform the design and clinical use of these tools to promote shared decision making.
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