Background: We developed a predictive risk model which improved the ATA modified initial risk stratification by including stimulated thyroglobulin, histological assessment of extrathyroidal extension, and tumour size. The model was validated on a retrospective dataset1. The aim of our study was to prospectively validate this model as a decision support tool to guide the use of radioactive iodine(RAI).
Methods: An online clinical support tool was developed to allow for easy application of our risk model. After input of variables, the tool produced a four-tiered outcome: very low, low, intermediate, and high risk. The model was extended to provide RAI recommendations; no RAI for very low risk disease, 1GBq for low risk, 4GBq for intermediate risk and 6GBq for high risk. Clinicians were surveyed whether they agreed with the treatment recommendation. Patients over ≥18 y with new diagnosis of DTC treated between August 2021-2022 were included.
Results: 132 patients were prospectively included. Median age of patients was 50y(IQR 39-66), and 38% were male(50/132). Majority of patients had papillary thyroid cancer 85/132(64%), followed by follicular thyroid cancer 18/132(15%) and follicular variant 16/132(12%). Remaining patients were Hurthle cell(9/132, 7%), diffuse sclerosing variant (2/132, 1%) and tall cell (2/132, 1%). Using the decision support tool, 19/132(14%) were assessed as high risk, 82/132 (62%) intermediate risk, 26/132(20%) low risk and 5/132(4%) very low risk. 90 clinicians completed the survey and most agreed with the dosing recommendation; 86% of high risk(12/14), 97% of intermediate risk(57/59) and 100% in low(15/15) and very low risk(2/2).
Conclusion: Our risk model can be readily translated into clinical practice via our online clinical support tool. Our tool had high utilisation and demonstrated its capacity to guide risk stratification and RAI activity. Longer term analysis will be required to determine the impact of our risk model and therapy recommendation on cancer outcomes.