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Background <p>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.</p> Methods <p>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.</p> Results <p>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 (<i>P</i> &lt; 0.0001). SHAP value analysis clarified each variable’s specific impact on the outcome.</p> Conclusions <p>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.</p>

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

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年4月6日

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  • Ying Gao,
  • Jinmiao Wang,
  • Weijie Tao,
  • Shoujun Wang,
  • Hai Xie,
  • Ran Duan,
  • Jie Hao,
  • Ming Gao

摘要

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.