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Modified Models for Predicting Malignancy Using Ultrasound Characters Have High Accuracy in Thyroid Nodules With Small Size

To assess the malignancy risk of thyroid nodules, ten ultrasound characteristics are suggested as key diagnostic markers. The European Thyroid Association Guidelines (EU-TIRADS) and 2015 American Thyroid Association Management Guidelines (2015ATA) are mainly used for ultrasound malignancy risk strat...

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Autores principales: Jiang, Shan, Xie, Qingji, Li, Nan, Chen, Haizhen, Chen, Xi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8662815/
https://www.ncbi.nlm.nih.gov/pubmed/34901151
http://dx.doi.org/10.3389/fmolb.2021.752417
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author Jiang, Shan
Xie, Qingji
Li, Nan
Chen, Haizhen
Chen, Xi
author_facet Jiang, Shan
Xie, Qingji
Li, Nan
Chen, Haizhen
Chen, Xi
author_sort Jiang, Shan
collection PubMed
description To assess the malignancy risk of thyroid nodules, ten ultrasound characteristics are suggested as key diagnostic markers. The European Thyroid Association Guidelines (EU-TIRADS) and 2015 American Thyroid Association Management Guidelines (2015ATA) are mainly used for ultrasound malignancy risk stratification, but both are less accurate and do not appropriatetly classify high risk patients in clinical examination. Previous studies focus on papillary thyroid carcinoma (PTC), but follicular thyroid carcinoma (FTC) and medullary thyroid carcinoma (MTC) remained to be characterized. Thus, this study aimed to determine the diagnostic accuracy and establish models using all ultrasound features including the nodule size for predicting the malignancy of thyroid nodules (PTC, FTC, and MTC) in China. We applied logistic regression to the data of 1,500 patients who received medical treatment in Shanghai and Fujian. Ultrasound features including taller-than-wide shape and invasion of the thyroid capsule showed high odds ratio (OR 19.329 and 4.672) for PTC in this dataset. Invasion of the thyroid also showed the highest odds ratio (OR = 8.10) for MTC. For FTC, the halo sign has the highest odds ratio (OR = 13.40). Four ultrasound features revealed distinct OR in PTC nodule groups with different sizes. In this study, we constructed a logistic model with accuracy up to 80%. In addition, this model revealed more accuracy than TIRADS in 4b and 4c category nodules. Hence, this model could well predict malignancy in small nodules and classify high-risk patients.
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spelling pubmed-86628152021-12-11 Modified Models for Predicting Malignancy Using Ultrasound Characters Have High Accuracy in Thyroid Nodules With Small Size Jiang, Shan Xie, Qingji Li, Nan Chen, Haizhen Chen, Xi Front Mol Biosci Molecular Biosciences To assess the malignancy risk of thyroid nodules, ten ultrasound characteristics are suggested as key diagnostic markers. The European Thyroid Association Guidelines (EU-TIRADS) and 2015 American Thyroid Association Management Guidelines (2015ATA) are mainly used for ultrasound malignancy risk stratification, but both are less accurate and do not appropriatetly classify high risk patients in clinical examination. Previous studies focus on papillary thyroid carcinoma (PTC), but follicular thyroid carcinoma (FTC) and medullary thyroid carcinoma (MTC) remained to be characterized. Thus, this study aimed to determine the diagnostic accuracy and establish models using all ultrasound features including the nodule size for predicting the malignancy of thyroid nodules (PTC, FTC, and MTC) in China. We applied logistic regression to the data of 1,500 patients who received medical treatment in Shanghai and Fujian. Ultrasound features including taller-than-wide shape and invasion of the thyroid capsule showed high odds ratio (OR 19.329 and 4.672) for PTC in this dataset. Invasion of the thyroid also showed the highest odds ratio (OR = 8.10) for MTC. For FTC, the halo sign has the highest odds ratio (OR = 13.40). Four ultrasound features revealed distinct OR in PTC nodule groups with different sizes. In this study, we constructed a logistic model with accuracy up to 80%. In addition, this model revealed more accuracy than TIRADS in 4b and 4c category nodules. Hence, this model could well predict malignancy in small nodules and classify high-risk patients. Frontiers Media S.A. 2021-11-26 /pmc/articles/PMC8662815/ /pubmed/34901151 http://dx.doi.org/10.3389/fmolb.2021.752417 Text en Copyright © 2021 Jiang, Xie, Li, Chen and Chen. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Molecular Biosciences
Jiang, Shan
Xie, Qingji
Li, Nan
Chen, Haizhen
Chen, Xi
Modified Models for Predicting Malignancy Using Ultrasound Characters Have High Accuracy in Thyroid Nodules With Small Size
title Modified Models for Predicting Malignancy Using Ultrasound Characters Have High Accuracy in Thyroid Nodules With Small Size
title_full Modified Models for Predicting Malignancy Using Ultrasound Characters Have High Accuracy in Thyroid Nodules With Small Size
title_fullStr Modified Models for Predicting Malignancy Using Ultrasound Characters Have High Accuracy in Thyroid Nodules With Small Size
title_full_unstemmed Modified Models for Predicting Malignancy Using Ultrasound Characters Have High Accuracy in Thyroid Nodules With Small Size
title_short Modified Models for Predicting Malignancy Using Ultrasound Characters Have High Accuracy in Thyroid Nodules With Small Size
title_sort modified models for predicting malignancy using ultrasound characters have high accuracy in thyroid nodules with small size
topic Molecular Biosciences
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8662815/
https://www.ncbi.nlm.nih.gov/pubmed/34901151
http://dx.doi.org/10.3389/fmolb.2021.752417
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