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  • https://doi.org/10.71321/5r3ppj45Copy DOI Icon

A Predictive Model for Lateral Cervical Lymph Node Metastasis in Thyroid Cancer

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Abstract

Objective: To investigate the predictive factors for lateral lymph node metastasis (LLNM) in patients with papillary thyroid carcinoma (PTC) and to develop an individualized prediction model.Methods: Clinical data from 241 PTC patients who underwent lateral neck dissection were analyzed. Logistic regression and machine learning methods were employed to identify predictive factors and construct a model. The predictive value of three-dimensional morphological parameters (total tumor surface area and total tumor volume) was also evaluated.Results: Maximum tumor diameter, central lymph node metastasis, preoperative Thyroid-Stimulating Hormone (TSH), and tumor location were identified as independent predictors of LLNM. A baseline combined model based on maximum tumor diameter showed good predictive performance (AUC 0.832). Furthermore, three-dimensional parameters (total surface area and total volume) demonstrated complementary predictive potential compared to the baseline model.Conclusion: An effective clinical prediction model for assessing LLNM risk was successfully developed. Three-dimensional morphological parameters represent promising predictive indicators with potential complementary value.

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