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Construction and validation of BRAF mutation diagnostic model based on ultrasound examination and clinical features of patients with thyroid nodules
Introduction: Fine Needle Aspiration (FNA) is currently the most popular method for identifying benign and malignant thyroid nodules. However, its diagnostic sensitivity is sometimes limited, which makes it necessary to apply genetic testing and other modalities as a secondary diagnostic method. The...
Autores principales: | , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9498827/ https://www.ncbi.nlm.nih.gov/pubmed/36160023 http://dx.doi.org/10.3389/fgene.2022.973272 |
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author | Xu, Chan Fang, Jianqiang Li, Wanying Sun, Chenyu Li, Yaru Lowe, Scott Bentley, Rachel Chen, Shuya He, Cunyu Li, Xinxin Wang, Bing Yin, Chengliang Li, Wenxian Li, Wenle |
author_facet | Xu, Chan Fang, Jianqiang Li, Wanying Sun, Chenyu Li, Yaru Lowe, Scott Bentley, Rachel Chen, Shuya He, Cunyu Li, Xinxin Wang, Bing Yin, Chengliang Li, Wenxian Li, Wenle |
author_sort | Xu, Chan |
collection | PubMed |
description | Introduction: Fine Needle Aspiration (FNA) is currently the most popular method for identifying benign and malignant thyroid nodules. However, its diagnostic sensitivity is sometimes limited, which makes it necessary to apply genetic testing and other modalities as a secondary diagnostic method. The diagnostic accuracy of thyroid nodule can be improved by combining mutations in the B-Raf proto-oncogene serine/threonine kinase (BRAF) with FNA. Thus, this study was conducted to create a nomogram diagnostic model based on the clinical and ultrasonic characteristics of patients with BRAF mutations to aid in the identification of benign and malignant thyroid nodules using FNA. Methods: From April 2018 to December 2021, 275 patients with thyroid nodules who underwent ultrasonography and BRAF gene testing (137 positive and 138 negative) were included from Xianyang Central Hospital. The clinical and ultrasonic characteristics of the patients were used to develop a nomographic, diagnostic model of BRAF gene mutation, and to validate and evaluate the usefulness of the model. Results: Independent risk factors for BRAF mutations included: focal strong echogenicity (microcalcifications, OR = 3.04, 95%CI = 1.41–6.58, p = 0.005), hypoechogenicity (OR = 3.8, 95%CI = 1.14–12.61, p = 0.029), lymph node metastases (OR = 3.54, 95%CI = 1.43–8.75, p = 0.006), margin (lobulated, OR = 3.7, 95%CI = 1.66–8.23, p = 0.001; extrathyroidal invasion, OR = 2.81, 95%CI = 1.11–7.06, p = 0.029), and shape (vertical position, OR = 2.7, 95%CI = 1.11–6.59, p = 0.029). The area under the curve (AUC) of the receiver operating characteristic (ROC) curve of the BRAF mutation diagnostic model constructed on these factors was 0.806 (95% CI = 0.754–0.851), and 39.5% was set as the threshold probability of making a clinical decision. The results of the validation and clinical utility evaluation showed that our model had good predictive performance and clinical application value. Conclusion: Our nomogram diagnostic model based on clinical and ultrasound features of patients accurately predicted the possibility of BRAF gene mutations in patients with thyroid nodules. |
format | Online Article Text |
id | pubmed-9498827 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-94988272022-09-23 Construction and validation of BRAF mutation diagnostic model based on ultrasound examination and clinical features of patients with thyroid nodules Xu, Chan Fang, Jianqiang Li, Wanying Sun, Chenyu Li, Yaru Lowe, Scott Bentley, Rachel Chen, Shuya He, Cunyu Li, Xinxin Wang, Bing Yin, Chengliang Li, Wenxian Li, Wenle Front Genet Genetics Introduction: Fine Needle Aspiration (FNA) is currently the most popular method for identifying benign and malignant thyroid nodules. However, its diagnostic sensitivity is sometimes limited, which makes it necessary to apply genetic testing and other modalities as a secondary diagnostic method. The diagnostic accuracy of thyroid nodule can be improved by combining mutations in the B-Raf proto-oncogene serine/threonine kinase (BRAF) with FNA. Thus, this study was conducted to create a nomogram diagnostic model based on the clinical and ultrasonic characteristics of patients with BRAF mutations to aid in the identification of benign and malignant thyroid nodules using FNA. Methods: From April 2018 to December 2021, 275 patients with thyroid nodules who underwent ultrasonography and BRAF gene testing (137 positive and 138 negative) were included from Xianyang Central Hospital. The clinical and ultrasonic characteristics of the patients were used to develop a nomographic, diagnostic model of BRAF gene mutation, and to validate and evaluate the usefulness of the model. Results: Independent risk factors for BRAF mutations included: focal strong echogenicity (microcalcifications, OR = 3.04, 95%CI = 1.41–6.58, p = 0.005), hypoechogenicity (OR = 3.8, 95%CI = 1.14–12.61, p = 0.029), lymph node metastases (OR = 3.54, 95%CI = 1.43–8.75, p = 0.006), margin (lobulated, OR = 3.7, 95%CI = 1.66–8.23, p = 0.001; extrathyroidal invasion, OR = 2.81, 95%CI = 1.11–7.06, p = 0.029), and shape (vertical position, OR = 2.7, 95%CI = 1.11–6.59, p = 0.029). The area under the curve (AUC) of the receiver operating characteristic (ROC) curve of the BRAF mutation diagnostic model constructed on these factors was 0.806 (95% CI = 0.754–0.851), and 39.5% was set as the threshold probability of making a clinical decision. The results of the validation and clinical utility evaluation showed that our model had good predictive performance and clinical application value. Conclusion: Our nomogram diagnostic model based on clinical and ultrasound features of patients accurately predicted the possibility of BRAF gene mutations in patients with thyroid nodules. Frontiers Media S.A. 2022-09-08 /pmc/articles/PMC9498827/ /pubmed/36160023 http://dx.doi.org/10.3389/fgene.2022.973272 Text en Copyright © 2022 Xu, Fang, Li, Sun, Li, Lowe, Bentley, Chen, He, Li, Wang, Yin, Li and Li. 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 | Genetics Xu, Chan Fang, Jianqiang Li, Wanying Sun, Chenyu Li, Yaru Lowe, Scott Bentley, Rachel Chen, Shuya He, Cunyu Li, Xinxin Wang, Bing Yin, Chengliang Li, Wenxian Li, Wenle Construction and validation of BRAF mutation diagnostic model based on ultrasound examination and clinical features of patients with thyroid nodules |
title | Construction and validation of BRAF mutation diagnostic model based on ultrasound examination and clinical features of patients with thyroid nodules |
title_full | Construction and validation of BRAF mutation diagnostic model based on ultrasound examination and clinical features of patients with thyroid nodules |
title_fullStr | Construction and validation of BRAF mutation diagnostic model based on ultrasound examination and clinical features of patients with thyroid nodules |
title_full_unstemmed | Construction and validation of BRAF mutation diagnostic model based on ultrasound examination and clinical features of patients with thyroid nodules |
title_short | Construction and validation of BRAF mutation diagnostic model based on ultrasound examination and clinical features of patients with thyroid nodules |
title_sort | construction and validation of braf mutation diagnostic model based on ultrasound examination and clinical features of patients with thyroid nodules |
topic | Genetics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9498827/ https://www.ncbi.nlm.nih.gov/pubmed/36160023 http://dx.doi.org/10.3389/fgene.2022.973272 |
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