甲状腺癌伴肺转移患者总体生存率和癌症特异性生存率的Nomogram模型建立及验证

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

目的:本研究的目的是开发一种有效的Nomogram来识别和预测甲状腺癌伴肺转移(thyroid cancer lung metastasis)患者,预测TCLM患者的总生存期(overall survival)和癌症特异性生存期(cancer specific survival),从而协助临床诊断和治疗。方法:本研究从SEER数据库共纳入544名已知甲状腺癌伴肺部转移的患者,并随机分配到训练组和验证组。采用Logistic回归筛选变量,并建立Nomogram模型。经过统计学分析我们发现年龄、组织学类型、肿瘤等级、肿瘤大小、肝转移、放疗、手术是构建Nomogram的重要变量。结果:用于识别和预测TCLM患者OS和CSS的Nomogram模型在校准曲线和受试者工作特征曲线(ROC)上得到了很好的检验。结论:本研究首先建立并验证TCLM患者预后相关的Nomogram模型,其中诊断年龄、组织学类型、肿瘤等级、肿瘤大小、肝转移、放疗、手术是影响该病预后的独立危险因素,帮助TCLM患者临床治疗及治疗后随访提供科学依据。

Objective: 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 and 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.