Personalised Medicine for Thyroid Cancer

Abstract

Background: Thyroid cancer incidence is increasing worldwide, including both indolent and advanced thyroid cancer. Radioactive iodine (RAI) is frequently used after total thyroidectomy to treat remnant thyroid tissue as well as microscopic and residual disease. Risk stratification is vital in thyroid cancer management to guide treatment decisions and to avoid over or under treatment.

Method: Assess the changes in RAI administration at a quaternary centre over the past decade. Identify those factors associated with risk of thyroid cancer recurrence and develop a predictive model to personalise risk stratification. Establish the role of functional imaging techniques in radio-iodine refractory disease. Determine the utility of liquid biopsies in thyroid cancer.

Results: Chapter Two describes a reduction in RAI activity prescription in a quaternary centre over the past decade, without evidence of a negative impact on cancer recurrence. Chapter Three identifies that factors additional to those described in current international guidelines are associated with thyroid cancer recurrence. A predictive risk model was built incorporating these risk factors into the algorithm. Chapter Four describes the development of an online clinical support tool to translate the predictive risk model into clinical practice. The tool was shown to have high clinical utility in a pilot study and was non inferior to expert clinical opinion. Chapter Five demonstrates the development of the I-PET score, which combines whole body iodine scans and FDG PET scans to aid prognostication and potentially identify candidates for redifferentiation therapy. Finally, Chapter Six demonstrates the utility of ctDNA to detect cancer driver mutations, monitor treatment response and potentially identify treatment resistance using a simple non-invasive blood test.

Conclusion: This thesis provides a comprehensive body of research focused on providing personalised management for patients with thyroid cancer.