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Establishment of an Ultrasound Malignancy Risk Stratification Model for Thyroid Nodules Larger Than 4 cm

BACKGROUND: The incidence and mortality of thyroid cancer, including thyroid nodules > 4 cm, have been increasing in recent years. The current evaluation methods are based mostly on studies of patients with thyroid nodules < 4 cm. The aim of the current study was to establish a risk stratifica...

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Autores principales: Xi, Xuehua, Wang, Ying, Gao, Luying, Jiang, Yuxin, Liang, Zhiyong, Ren, Xinyu, Gao, Qing, Lai, Xingjian, Yang, Xiao, Zhu, Shenling, Zhao, Ruina, Zhang, Xiaoyan, Zhang, Bo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8276053/
https://www.ncbi.nlm.nih.gov/pubmed/34268104
http://dx.doi.org/10.3389/fonc.2021.592927
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author Xi, Xuehua
Wang, Ying
Gao, Luying
Jiang, Yuxin
Liang, Zhiyong
Ren, Xinyu
Gao, Qing
Lai, Xingjian
Yang, Xiao
Zhu, Shenling
Zhao, Ruina
Zhang, Xiaoyan
Zhang, Bo
author_facet Xi, Xuehua
Wang, Ying
Gao, Luying
Jiang, Yuxin
Liang, Zhiyong
Ren, Xinyu
Gao, Qing
Lai, Xingjian
Yang, Xiao
Zhu, Shenling
Zhao, Ruina
Zhang, Xiaoyan
Zhang, Bo
author_sort Xi, Xuehua
collection PubMed
description BACKGROUND: The incidence and mortality of thyroid cancer, including thyroid nodules > 4 cm, have been increasing in recent years. The current evaluation methods are based mostly on studies of patients with thyroid nodules < 4 cm. The aim of the current study was to establish a risk stratification model to predict risk of malignancy in thyroid nodules > 4 cm. METHODS: A total of 279 thyroid nodules > 4 cm in 267 patients were retrospectively analyzed. Nodules were randomly assigned to a training dataset (n = 140) and a validation dataset (n = 139). Multivariable logistic regression analysis was applied to establish a nomogram. The risk stratification of thyroid nodules > 4 cm was established according to the nomogram. The diagnostic performance of the model was evaluated and compared with the American College Radiology Thyroid Imaging Reporting and Data System (ACR TI-RADS), Kwak TI-RADS and 2015 ATA guidelines using the area under the receiver operating characteristic curve (AUC). RESULTS: The analysis included 279 nodules (267 patients, 50.6 ± 13.2 years): 229 were benign and 50 were malignant. Multivariate regression revealed microcalcification, solid mass, ill-defined border and hypoechogenicity as independent risk factors. Based on the four factors, a risk stratified clinical model was developed for evaluating nodules > 4 cm, which includes three categories: high risk (risk value = 0.8-0.9, with more than 3 factors), intermediate risk (risk value = 0.3-0.7, with 2 factors or microcalcification) and low risk (risk value = 0.1-0.2, with 1 factor except microcalcification). In the validation dataset, the malignancy rate of thyroid nodules > 4 cm that were classified as high risk was 88.9%; as intermediate risk, 35.7%; and as low risk, 6.9%. The new model showed greater AUC than ACR TI-RADS (0.897 vs. 0.855, p = 0.040), but similar sensitivity (61.9% vs. 57.1%, p = 0.480) and specificity (91.5% vs. 93.2%, p = 0.680). CONCLUSION: Microcalcification, solid mass, ill-defined border and hypoechogenicity on ultrasound may be signs of malignancy in thyroid nodules > 4 cm. A risk stratification model for nodules > 4 cm may show better diagnostic performance than ACR TI-RADS, which may lead to better preoperative decision-making.
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spelling pubmed-82760532021-07-14 Establishment of an Ultrasound Malignancy Risk Stratification Model for Thyroid Nodules Larger Than 4 cm Xi, Xuehua Wang, Ying Gao, Luying Jiang, Yuxin Liang, Zhiyong Ren, Xinyu Gao, Qing Lai, Xingjian Yang, Xiao Zhu, Shenling Zhao, Ruina Zhang, Xiaoyan Zhang, Bo Front Oncol Oncology BACKGROUND: The incidence and mortality of thyroid cancer, including thyroid nodules > 4 cm, have been increasing in recent years. The current evaluation methods are based mostly on studies of patients with thyroid nodules < 4 cm. The aim of the current study was to establish a risk stratification model to predict risk of malignancy in thyroid nodules > 4 cm. METHODS: A total of 279 thyroid nodules > 4 cm in 267 patients were retrospectively analyzed. Nodules were randomly assigned to a training dataset (n = 140) and a validation dataset (n = 139). Multivariable logistic regression analysis was applied to establish a nomogram. The risk stratification of thyroid nodules > 4 cm was established according to the nomogram. The diagnostic performance of the model was evaluated and compared with the American College Radiology Thyroid Imaging Reporting and Data System (ACR TI-RADS), Kwak TI-RADS and 2015 ATA guidelines using the area under the receiver operating characteristic curve (AUC). RESULTS: The analysis included 279 nodules (267 patients, 50.6 ± 13.2 years): 229 were benign and 50 were malignant. Multivariate regression revealed microcalcification, solid mass, ill-defined border and hypoechogenicity as independent risk factors. Based on the four factors, a risk stratified clinical model was developed for evaluating nodules > 4 cm, which includes three categories: high risk (risk value = 0.8-0.9, with more than 3 factors), intermediate risk (risk value = 0.3-0.7, with 2 factors or microcalcification) and low risk (risk value = 0.1-0.2, with 1 factor except microcalcification). In the validation dataset, the malignancy rate of thyroid nodules > 4 cm that were classified as high risk was 88.9%; as intermediate risk, 35.7%; and as low risk, 6.9%. The new model showed greater AUC than ACR TI-RADS (0.897 vs. 0.855, p = 0.040), but similar sensitivity (61.9% vs. 57.1%, p = 0.480) and specificity (91.5% vs. 93.2%, p = 0.680). CONCLUSION: Microcalcification, solid mass, ill-defined border and hypoechogenicity on ultrasound may be signs of malignancy in thyroid nodules > 4 cm. A risk stratification model for nodules > 4 cm may show better diagnostic performance than ACR TI-RADS, which may lead to better preoperative decision-making. Frontiers Media S.A. 2021-06-29 /pmc/articles/PMC8276053/ /pubmed/34268104 http://dx.doi.org/10.3389/fonc.2021.592927 Text en Copyright © 2021 Xi, Wang, Gao, Jiang, Liang, Ren, Gao, Lai, Yang, Zhu, Zhao, Zhang and Zhang 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 Oncology
Xi, Xuehua
Wang, Ying
Gao, Luying
Jiang, Yuxin
Liang, Zhiyong
Ren, Xinyu
Gao, Qing
Lai, Xingjian
Yang, Xiao
Zhu, Shenling
Zhao, Ruina
Zhang, Xiaoyan
Zhang, Bo
Establishment of an Ultrasound Malignancy Risk Stratification Model for Thyroid Nodules Larger Than 4 cm
title Establishment of an Ultrasound Malignancy Risk Stratification Model for Thyroid Nodules Larger Than 4 cm
title_full Establishment of an Ultrasound Malignancy Risk Stratification Model for Thyroid Nodules Larger Than 4 cm
title_fullStr Establishment of an Ultrasound Malignancy Risk Stratification Model for Thyroid Nodules Larger Than 4 cm
title_full_unstemmed Establishment of an Ultrasound Malignancy Risk Stratification Model for Thyroid Nodules Larger Than 4 cm
title_short Establishment of an Ultrasound Malignancy Risk Stratification Model for Thyroid Nodules Larger Than 4 cm
title_sort establishment of an ultrasound malignancy risk stratification model for thyroid nodules larger than 4 cm
topic Oncology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8276053/
https://www.ncbi.nlm.nih.gov/pubmed/34268104
http://dx.doi.org/10.3389/fonc.2021.592927
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