Abstract
Molecular testing for thyroid nodules has been rapidly developed in recent years, aiming to predict the presence of malignancy and aggressive features. While commonly utilized to predict malignancy, its role in guiding the management approach is still developing. The high cost of genetic tests and long-term sequences of thyroid cancer is limiting to real-life studies. Objective: To evaluate the cost effectiveness of molecular testing for low-risk differentiated thyroid cancer (lrDTC). Methods: We developed a Markovian decision tree model of a simulated lrDTC cohort, comparing two management strategies: (I) Conducting genetic tests (GT)-patients are stratified into three risk groups for distant metastasis by the identified molecular markers: low-, intermediate- and high-risk molecular profile; followed by management accordingly: patients with low-risk will undergo hemithyroidectomy (HT), patients with intermediate-risk will undergo total thyroidectomy (TT), and high-risk patients will undergo TT with central neck dissection; (II) Without genetic tests (wGT)-all patients will undergo HT according to the ATA recommendations for lrDTC. Outcomes were measured as quality-adjusted life years (QALYs) and costs of each strategy. Results: GT was found as cost effective, leading to a gain of 1.7 QALYs with an additional cost of $327 per patient compared to wGT strategy. This yielded an incremental cost-effectiveness ratio of $190 per QALY. Sensitivity analysis demonstrated robust results across the variables' ranges. The most impactful variable was the benefit from performing TT rather than HT for intermediate to high-risk patients. Conclusions: Our model found that molecular testing for lrDTC is cost-effective, allowing tailored management according to the patient's personal risk level reflected in the genetic profile, hence improving outcomes.