Endocrine Abstracts

Introduction: Differentiated thyroid cancer (DTC) is the most common endocrine malignancy, with a notable increase in incidence over recent decades. Despite the generally positive prognosis, managing DTC remains intricate, often involving thyroidectomy followed by radioactive iodine (RAI) therapy. The response to RAI varies significantly among patients, underscoring the need for reliable predictors of treatment efficacy. New guidelines emphasize the importance of personalized follow-up plans, fueling research into predictive models to enhance prognostic precision.

Methods: This retrospective study analyzed 744 DTC patients treated at a single center, focusing on the predictive value of clinicopathological factors and thyroid biomarkers. We developed multivariate logistic regression models to evaluate the efficacy of different biomarkers in predicting RAI response, adjusting for variables such as age, sex, and disease stage. Optimal cut-off values for these biomarkers were determined to assess their predictive capability.

Results: Our analysis found that no single biomarker outperformed others significantly in predicting RAI treatment outcomes. However, stimulated thyroglobulin (sTg) emerged as a reliable predictor, with a mean cut-off value of 7.22 ng/ml. The presence of chronic lymphocytic thyroiditis (CLT) also appeared to enhance the accuracy of the predictive models, though the improvement was not statistically significant.

Conclusions: This study underscores the potential of sTg as a key predictor for RAI efficacy in DTC patients, with a defined cut-off value that can aid in clinical decision-making. Incorporating CLT status into predictive models may further improve their accuracy, suggesting a direction for future research. These findings contribute to the advancement of personalized treatment approaches for DTC patients undergoing RAI therapy, ultimately aiming to improve patient outcomes by tailoring management strategies to individual patient profiles.