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预测甲状腺癌肝转移的预后列线图的开发与验证:一项基于监测、流行病学和最终结果数据库的研究

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.

作者信息

Ruan Cong, Chen Xiaogang

机构信息

Department of Head and Neck Tumor Surgery, GuangFu Oncology Hospital, Jinhua, China.

出版信息

Comput Methods Biomech Biomed Engin. 2024 Oct 3:1-13. doi: 10.1080/10255842.2024.2410233.

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 ( < 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 ( < 0.001, HR < 1), while concurrent brain metastasis indicated poorer outcomes (HR = 2.747, = 0.037). In conclusion, this nomogram effectively predicts LM risk and evaluates prognosis for TCLM patients, aiding clinicians in personalized treatment decisions.

摘要

本研究旨在创建一种预后列线图,以预测甲状腺癌(TC)患者发生肝转移(LM)的风险,并评估发生LM患者的生存结局。数据来自监测、流行病学和最终结果(SEER)数据库,涵盖2010年至2020年的TC患者,共计110,039例,其中142例发生LM。基于赤池信息准则(AIC)的逻辑回归和逐步回归确定了影响LM发生的显著因素:年龄、组织学类型、肿瘤大小、骨转移、肺转移和T分期(P<0.05)。使用这些因素构建了列线图,C指数为0.977,ROC曲线分析显示曲线下面积(AUC)为0.977。对于TC-LM患者,滤泡状TC、髓样TC、乳头状TC和检查的区域淋巴结与较好的预后相关(P<0.001,HR<1),而同时发生脑转移则提示预后较差(HR = 2.747,P = 0.037)。总之,该列线图可有效预测LM风险并评估TC-LM患者的预后,有助于临床医生做出个性化治疗决策。

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