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Comparison of four models predicting the malignancy of pulmonary nodules: A single-center study of Korean adults

OBJECTIVE: Four commonly used clinical models for predicting the probability of malignancy in pulmonary nodules were compared. While three of the models (Mayo Clinic, Veterans Association [VA], and Brock University) are based on clinical and computed tomography (CT) characteristics, one model (Herde...

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Autores principales: Yang, Bumhee, Jhun, Byung Woo, Shin, Sun Hye, Jeong, Byeong-Ho, Um, Sang-Won, Zo, Jae Il, Lee, Ho Yun, Sohn, Insoek, Kim, Hojoong, Kwon, O. Jung, Lee, Kyungjong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6067755/
https://www.ncbi.nlm.nih.gov/pubmed/30063725
http://dx.doi.org/10.1371/journal.pone.0201242
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author Yang, Bumhee
Jhun, Byung Woo
Shin, Sun Hye
Jeong, Byeong-Ho
Um, Sang-Won
Zo, Jae Il
Lee, Ho Yun
Sohn, Insoek
Kim, Hojoong
Kwon, O. Jung
Lee, Kyungjong
author_facet Yang, Bumhee
Jhun, Byung Woo
Shin, Sun Hye
Jeong, Byeong-Ho
Um, Sang-Won
Zo, Jae Il
Lee, Ho Yun
Sohn, Insoek
Kim, Hojoong
Kwon, O. Jung
Lee, Kyungjong
author_sort Yang, Bumhee
collection PubMed
description OBJECTIVE: Four commonly used clinical models for predicting the probability of malignancy in pulmonary nodules were compared. While three of the models (Mayo Clinic, Veterans Association [VA], and Brock University) are based on clinical and computed tomography (CT) characteristics, one model (Herder) additionally includes the (18)F-fluorodeoxyglucose (FDG) uptake value among the positron emission tomography (PET) characteristics. This study aimed to compare the predictive power of these four models in the context of a population drawn from a single center in an endemic area for tuberculosis in Korea. METHODS: A retrospective analysis of 242 pathologically confirmed nodules (4–30 mm in diameter) in 242 patients from January 2015 to December 2015 was performed. The area under the receiver operating characteristic curve (AUC) was used to assess the predictive performance with respect to malignancy. RESULTS: Of 242 nodules, 187 (77.2%) were malignant and 55 (22.8%) were benign, with tuberculosis granuloma being the most common type of benign nodule (23/55). PET was performed for 227 nodules (93.8%). The Mayo, VA, and Brock models showed similar predictive performance for malignant nodules (AUC: 0.6145, 0.6042 and 0.6820, respectively). The performance of the Herder model (AUC: 0.5567) was not significantly different from that of the Mayo (vs. Herder, p = 0.576) or VA models (vs. Herder, p = 0.999), and there were no differences among the three models in determining the probability of malignancy of pulmonary nodules. However, compared with the Brock model, the Herder model showed a significantly lower ability to predict malignancy (adjusted p = 0.0132). CONCLUSIONS: In our study, the Herder model including the (18)FDG uptake value did not perform better than the other models in predicting malignant nodules, suggesting the limited utility of adding PET/CT data to models predicting malignancy in populations within endemic areas for benign inflammatory nodules, such as tuberculosis.
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spelling pubmed-60677552018-08-10 Comparison of four models predicting the malignancy of pulmonary nodules: A single-center study of Korean adults Yang, Bumhee Jhun, Byung Woo Shin, Sun Hye Jeong, Byeong-Ho Um, Sang-Won Zo, Jae Il Lee, Ho Yun Sohn, Insoek Kim, Hojoong Kwon, O. Jung Lee, Kyungjong PLoS One Research Article OBJECTIVE: Four commonly used clinical models for predicting the probability of malignancy in pulmonary nodules were compared. While three of the models (Mayo Clinic, Veterans Association [VA], and Brock University) are based on clinical and computed tomography (CT) characteristics, one model (Herder) additionally includes the (18)F-fluorodeoxyglucose (FDG) uptake value among the positron emission tomography (PET) characteristics. This study aimed to compare the predictive power of these four models in the context of a population drawn from a single center in an endemic area for tuberculosis in Korea. METHODS: A retrospective analysis of 242 pathologically confirmed nodules (4–30 mm in diameter) in 242 patients from January 2015 to December 2015 was performed. The area under the receiver operating characteristic curve (AUC) was used to assess the predictive performance with respect to malignancy. RESULTS: Of 242 nodules, 187 (77.2%) were malignant and 55 (22.8%) were benign, with tuberculosis granuloma being the most common type of benign nodule (23/55). PET was performed for 227 nodules (93.8%). The Mayo, VA, and Brock models showed similar predictive performance for malignant nodules (AUC: 0.6145, 0.6042 and 0.6820, respectively). The performance of the Herder model (AUC: 0.5567) was not significantly different from that of the Mayo (vs. Herder, p = 0.576) or VA models (vs. Herder, p = 0.999), and there were no differences among the three models in determining the probability of malignancy of pulmonary nodules. However, compared with the Brock model, the Herder model showed a significantly lower ability to predict malignancy (adjusted p = 0.0132). CONCLUSIONS: In our study, the Herder model including the (18)FDG uptake value did not perform better than the other models in predicting malignant nodules, suggesting the limited utility of adding PET/CT data to models predicting malignancy in populations within endemic areas for benign inflammatory nodules, such as tuberculosis. Public Library of Science 2018-07-31 /pmc/articles/PMC6067755/ /pubmed/30063725 http://dx.doi.org/10.1371/journal.pone.0201242 Text en © 2018 Yang et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Yang, Bumhee
Jhun, Byung Woo
Shin, Sun Hye
Jeong, Byeong-Ho
Um, Sang-Won
Zo, Jae Il
Lee, Ho Yun
Sohn, Insoek
Kim, Hojoong
Kwon, O. Jung
Lee, Kyungjong
Comparison of four models predicting the malignancy of pulmonary nodules: A single-center study of Korean adults
title Comparison of four models predicting the malignancy of pulmonary nodules: A single-center study of Korean adults
title_full Comparison of four models predicting the malignancy of pulmonary nodules: A single-center study of Korean adults
title_fullStr Comparison of four models predicting the malignancy of pulmonary nodules: A single-center study of Korean adults
title_full_unstemmed Comparison of four models predicting the malignancy of pulmonary nodules: A single-center study of Korean adults
title_short Comparison of four models predicting the malignancy of pulmonary nodules: A single-center study of Korean adults
title_sort comparison of four models predicting the malignancy of pulmonary nodules: a single-center study of korean adults
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6067755/
https://www.ncbi.nlm.nih.gov/pubmed/30063725
http://dx.doi.org/10.1371/journal.pone.0201242
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