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September 10, 2025American Journal of Cancer Research

Establishment and validation of a recurrence risk model in early-stage tongue squamous cell carcinoma patients incorporating immune-inflammatory biomarkers and clinicopathological parameters

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Authors

XLXiangxiang LiaoXinyu University HWHongwen WuFirst Affiliated Hospital of Jiangxi Medical College HYHui YangHebei Medical University

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Implication

Retrospective analysis identifies recurrence risk factors in tongue squamous cell carcinoma patients, suggesting clinical utility through machine learning.

Key Points

The predictive model showed an AUC of 0.902 in the training cohort, indicating strong predictive ability.
Recurrence was noted in 31.07% of 515 early-stage tongue squamous cell carcinoma patients across both cohorts.
Feature selection utilized machine learning algorithms like LASSO, Xgboost, and SVM to identify key risk factors.
Integration of immuno-inflammatory markers and clinicopathological parameters enhances the model's predictive performance.

Cite This Study

Liao et al. (2025) studied this question.

synapsesocial.com/papers/68c1a25a54b1d3bfb60dd36b https://doi.org/10.62347/cmxu1610

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Implication

Retrospective analysis identifies recurrence risk factors in tongue squamous cell carcinoma patients, suggesting clinical utility through machine learning.

Establishment and validation of a recurrence risk model in early-stage tongue squamous cell carcinoma patients incorporating immune-inflammatory biomarkers and clinicopathological parameters

Discussion

Member takes

Implication

Key Points

Cite This Study

Establishment and validation of a recurrence risk model in early-stage tongue squamous cell carcinoma patients incorporating immune-inflammatory biomarkers and clinicopathological parameters

Discussion

Member takes

Implication

Key Points

Cite This Study

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