Development and validation of a prognostic nomogram for predicting liver metastasis in thyroid cancer: a study based on the surveillance, epidemiology, and end results database.

Abstract

This study aimed to create a prognostic nomogram to predict the risk of liver metastasis (LM) in thyroid cancer (TC) patients and assess survival outcomes for those with LM. Data were collected from the SEER database, covering TC patients from 2010 to 2020, totaling 110,039 individuals, including 142 with LM. Logistic regression and stepwise regression based on the Akaike information criterion (AIC) identified significant factors influencing LM occurrence: age, histological type, tumor size, bone metastasis, lung metastasis, and T stage (p < 0.05). A nomogram was constructed using these factors, achieving a Cindex of 0.977, with ROC curve analysis showing an area under the curve (AUC) of 0.977. For patients with TCLM, follicular TC, medullary TC, papillary TC, and examined regional nodes were associated with better prognosis (p < 0.001, HR < 1), while concurrent brain metastasis indicated poorer outcomes (HR = 2.747, p = 0.037). In conclusion, this nomogram effectively predicts LM risk and evaluates prognosis for TCLM patients, aiding clinicians in personalized treatment decisions.