Predicting lymph node metastasis in papillary thyroid carcinoma with Hashimoto’s thyroiditis using regression and network analysis

Abstract The comprehensive study of the relationship between lymph node metastasis (LNM) and its associated factors in patients with concurrent papillary thyroid carcinoma (PTC) and Hashimoto’s thyroiditis (HT) remains insufficient. Building upon the initial investigation of factors associated with...

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Main Authors: Lirong Wang, Peng Cheng, Lian Zhu, Hailong Tan, Bo Wei, Ning Li, Neng Tang, Shi Chang
Format: Article
Language:English
Published: Nature Portfolio 2024-11-01
Series:Scientific Reports
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Online Access:https://doi.org/10.1038/s41598-024-78179-8
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author Lirong Wang
Peng Cheng
Lian Zhu
Hailong Tan
Bo Wei
Ning Li
Neng Tang
Shi Chang
author_facet Lirong Wang
Peng Cheng
Lian Zhu
Hailong Tan
Bo Wei
Ning Li
Neng Tang
Shi Chang
author_sort Lirong Wang
collection DOAJ
description Abstract The comprehensive study of the relationship between lymph node metastasis (LNM) and its associated factors in patients with concurrent papillary thyroid carcinoma (PTC) and Hashimoto’s thyroiditis (HT) remains insufficient. Building upon the initial investigation of factors associated with LNM in patients with concurrent PTC and HT, we further analyzed the complex relationships between different severity indicators of LNM and these associated factors. This study included patients confirmed PTC with HT who underwent total thyroidectomy at Xiangya Hospital, from January 2020 to December 2021. A total of 271 patients from 2020 were used as the training set, and 300 patients from 2021 as the validation set. Univariate analysis and regression modeling were used to identify key factors associated with LNM. Model reliability was assessed using the area under the receiver operating characteristic curve (AUC). Network analysis was employed to explore associations between LNM severity and its related factors. The regression model indicated that age, calcification, free triiodothyronine (FT3), and tumor maximum diameter (TMD) are independent factors for LNM. The severity model showed free thyroxine (FT4) and hemoglobin (Hb) are independent protective factors for the region and quantity of LNM, respectively, while TMD is an independent risk factor for both. Network analysis revealed TMD has a closer relationship with LNM severity compared to other associated factors. This study innovatively combined regression models and network analysis to investigate factors related to LNM in patients with PTC and HT, providing a theoretical basis for predicting preoperative LNM in future clinical practice.
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spelling doaj-art-6a9d6f7a7a954699aac67a23a31dc1702024-11-17T12:25:44ZengNature PortfolioScientific Reports2045-23222024-11-0114111210.1038/s41598-024-78179-8Predicting lymph node metastasis in papillary thyroid carcinoma with Hashimoto’s thyroiditis using regression and network analysisLirong Wang0Peng Cheng1Lian Zhu2Hailong Tan3Bo Wei4Ning Li5Neng Tang6Shi Chang7Division of Thyroid Surgery, General Surgery Department, Xiangya Hospital, Central South UniversityDepartment of Psychiatry, National Center for Mental Disorders, National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South UniversityDivision of Thyroid Surgery, General Surgery Department, Xiangya Hospital, Central South UniversityDivision of Thyroid Surgery, General Surgery Department, Xiangya Hospital, Central South UniversityDivision of Thyroid Surgery, General Surgery Department, Xiangya Hospital, Central South UniversityDivision of Thyroid Surgery, General Surgery Department, Xiangya Hospital, Central South UniversityDivision of Thyroid Surgery, General Surgery Department, Xiangya Hospital, Central South UniversityDivision of Thyroid Surgery, General Surgery Department, Xiangya Hospital, Central South UniversityAbstract The comprehensive study of the relationship between lymph node metastasis (LNM) and its associated factors in patients with concurrent papillary thyroid carcinoma (PTC) and Hashimoto’s thyroiditis (HT) remains insufficient. Building upon the initial investigation of factors associated with LNM in patients with concurrent PTC and HT, we further analyzed the complex relationships between different severity indicators of LNM and these associated factors. This study included patients confirmed PTC with HT who underwent total thyroidectomy at Xiangya Hospital, from January 2020 to December 2021. A total of 271 patients from 2020 were used as the training set, and 300 patients from 2021 as the validation set. Univariate analysis and regression modeling were used to identify key factors associated with LNM. Model reliability was assessed using the area under the receiver operating characteristic curve (AUC). Network analysis was employed to explore associations between LNM severity and its related factors. The regression model indicated that age, calcification, free triiodothyronine (FT3), and tumor maximum diameter (TMD) are independent factors for LNM. The severity model showed free thyroxine (FT4) and hemoglobin (Hb) are independent protective factors for the region and quantity of LNM, respectively, while TMD is an independent risk factor for both. Network analysis revealed TMD has a closer relationship with LNM severity compared to other associated factors. This study innovatively combined regression models and network analysis to investigate factors related to LNM in patients with PTC and HT, providing a theoretical basis for predicting preoperative LNM in future clinical practice.https://doi.org/10.1038/s41598-024-78179-8Papillary thyroid carcinoma (PTC)Hashimoto’s Thyroiditis (HT)Lymph Node Metastasis (LNM)Biochemical markersRegression modelingNetwork Analysis
spellingShingle Lirong Wang
Peng Cheng
Lian Zhu
Hailong Tan
Bo Wei
Ning Li
Neng Tang
Shi Chang
Predicting lymph node metastasis in papillary thyroid carcinoma with Hashimoto’s thyroiditis using regression and network analysis
Scientific Reports
Papillary thyroid carcinoma (PTC)
Hashimoto’s Thyroiditis (HT)
Lymph Node Metastasis (LNM)
Biochemical markers
Regression modeling
Network Analysis
title Predicting lymph node metastasis in papillary thyroid carcinoma with Hashimoto’s thyroiditis using regression and network analysis
title_full Predicting lymph node metastasis in papillary thyroid carcinoma with Hashimoto’s thyroiditis using regression and network analysis
title_fullStr Predicting lymph node metastasis in papillary thyroid carcinoma with Hashimoto’s thyroiditis using regression and network analysis
title_full_unstemmed Predicting lymph node metastasis in papillary thyroid carcinoma with Hashimoto’s thyroiditis using regression and network analysis
title_short Predicting lymph node metastasis in papillary thyroid carcinoma with Hashimoto’s thyroiditis using regression and network analysis
title_sort predicting lymph node metastasis in papillary thyroid carcinoma with hashimoto s thyroiditis using regression and network analysis
topic Papillary thyroid carcinoma (PTC)
Hashimoto’s Thyroiditis (HT)
Lymph Node Metastasis (LNM)
Biochemical markers
Regression modeling
Network Analysis
url https://doi.org/10.1038/s41598-024-78179-8
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