A Nomogram for Distinction and Potential Prediction of Lung Metastasis in Thyroid Cancer Patients

Abstract

\n Background:The prognosis of thyroid cancer with lung metastasis is poor. Our aim is to develop a reliable tool to identify and predict lung metastasis (LM) in patients with thyroid cancer (TC), thereby assisting in clinical diagnosis and treatment. The aim of this study was to establish an effective Nomogram method for predicting overall survival (OS) and cancer-specific survival (CSS) in TC patients with LM. Methods: A total of 544 patients with known distant metastatic status and epidemiological variables from the SEER database were enrolled and assigned randomly to training and validating groups in this study. Logistic regression was used to screen variables and a nomogram was established. After multivariate logistic regression age, histologic type, grade, tumor size, liver metastasis, Radiotherapy, Surgery were the important variables to construct the nomogram. Results: The nomogram used to identify and predict the OS and CSS in TCLM patients passed the calibration and validation steps. The calibration curve and receiver operating characteristic curves(ROC) indicated the good performance of the nomogram.Conclusions: Our nomogram is a reliable and robust tool for the identification and prediction of LM in TC patients, thus helping to better select medical examinations and optimize treatment in collaboration with medical oncologists and surgeons.