ArticleDiscover oncology2025
Developing a prognostic nomogram for primary thyroid lymphoma: insights from a large retrospective study.
Article in Discover oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
2 citing papers in PubMed.
- Construction and validation of nomogram for the cancer-specific death in children and adolescents‑onset lymphoma.Discover oncology · 2026Article
- An interpretable machine learning model for predicting brain metastasis in breast cancer.Frontiers in medicine · 2026Article
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Authors and funding
8 authors.
Funding
Abstract
backgroundPrimary 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.
methodsWe 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.
resultsThe 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.
conclusionsThe 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.
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