Developing a prognostic nomogram for primary thyroid lymphoma: insights from a large retrospective study.

IF 2.8 4区 医学 Q3 ENDOCRINOLOGY & METABOLISM
Ying Gao, Jinmiao Wang, Weijie Tao, Shoujun Wang, Hai Xie, Ran Duan, Jie Hao, Ming Gao
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引用次数: 0

Abstract

Background: Primary thyroid lymphoma (PTL) is a rare and aggressive malignancy with a need for more precise prognostication tools due to the limitations of existing staging systems. This study aims to develop a nomogram to predict overall survival (OS) rates in PTL patients, addressing the gap in personalized treatment protocols.

Methods: We analyzed 1469 PTL cases. Cox regression analyses were used to identify key prognostic factors and construct a survival prognostic nomogram. The nomogram's performance was evaluated using receiver operating characteristic (ROC) curves and decision curve analysis. Additionally, a web-based dynamic nomogram was developed to estimate mortality risk for PTL patients.

Results: The nomogram exhibited high clinical utility and precision as determined by decision curve analysis and ROC curves. Furthermore, a novel risk stratification system was introduced. Kaplan-Meier survival curves illustrated significant differences among various risk groups, reinforcing the nomogram's substantial clinical value in predicting OS for PTL patients (P < 0.0001). SHAP value analysis clarified each variable's specific impact on the outcome.

Conclusions: The nomogram provides a valuable instrument for clinicians to individualize OS predictions for PTL patients, addressing the unmet need for personalized prognostication in this rare malignancy.

发展原发性甲状腺淋巴瘤的预后图:来自一项大型回顾性研究的见解。
背景:原发性甲状腺淋巴瘤(PTL)是一种罕见的侵袭性恶性肿瘤,由于现有分期系统的局限性,需要更精确的预后工具。本研究旨在开发一种nomogram预测PTL患者的总生存率(OS),以弥补个性化治疗方案的不足。方法:对1469例PTL病例进行分析。Cox回归分析用于确定关键预后因素并构建生存预后nomogram。采用受试者工作特征(ROC)曲线和决策曲线分析来评价nomogram的表现。此外,开发了基于网络的动态图来估计PTL患者的死亡风险。结果:经决策曲线分析和ROC曲线分析,nomogram具有较高的临床实用性和准确性。此外,还提出了一种新的风险分层系统。Kaplan-Meier生存曲线显示了不同风险组之间的显著差异,强化了nomogram预测PTL患者生存期的重要临床价值(P结论:nomogram为临床医生提供了一种有价值的工具,可以对PTL患者进行个体化生存期预测,解决了这种罕见恶性肿瘤对个性化预后的需求。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Discover. Oncology
Discover. Oncology Medicine-Endocrinology, Diabetes and Metabolism
CiteScore
2.40
自引率
9.10%
发文量
122
审稿时长
5 weeks
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