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Computed tomography-guided cutting needle biopsy for lung nodules: when the biopsy-based benign results are real benign
BACKGROUND: Computed tomography (CT)-guided cutting needle biopsy (CNB) is an effective diagnostic method for lung nodules (LNs). The false-negative rate of CT-guided lung biopsy is reported to be up to 16%. This study aimed to determine the predictors of true-negative results in LNs with CNB-based...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9166573/ https://www.ncbi.nlm.nih.gov/pubmed/35659681 http://dx.doi.org/10.1186/s12957-022-02647-6 |
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author | Hui, Hui Ma, Gao-Lei Yin, Hai-Tao Zhou, Yun Xie, Xiao-Mei Gao, Yong-Guang |
author_facet | Hui, Hui Ma, Gao-Lei Yin, Hai-Tao Zhou, Yun Xie, Xiao-Mei Gao, Yong-Guang |
author_sort | Hui, Hui |
collection | PubMed |
description | BACKGROUND: Computed tomography (CT)-guided cutting needle biopsy (CNB) is an effective diagnostic method for lung nodules (LNs). The false-negative rate of CT-guided lung biopsy is reported to be up to 16%. This study aimed to determine the predictors of true-negative results in LNs with CNB-based benign results. METHODS: From January 2011 to December 2015, 96 patients with CNB-based nonspecific benign results were included in this study as the training group to detect predictors of true-negative results. From January 2016 to December 2018, an additional 57 patients were included as a validation group to test the reliability of the predictors. RESULTS: In the training group, a total of 96 patients underwent CT-guided CNB for 96 LNs. The CNB-based results were true negatives for 82 LNs and false negatives for 14 LNs. The negative predictive value of the CNB-based benign results was 85.4% (82/96). Univariate and multivariate logistic regression analyses revealed that CNB-based granulomatous inflammation (P = 0.013, hazard ratio = 0.110, 95% confidential interval = 0.019–0.625) was the independent predictor of true-negative results. The area under the receiver operator characteristic (ROC) curve was 0.697 (P = 0.019). In the validation group, biopsy results for 47 patients were true negative, and 10 were false negative. When the predictor was used on the validation group, the area under the ROC curve was 0.759 (P = 0.011). CONCLUSIONS: Most of the CNB-based benign results were true negatives, and CNB-based granulomatous inflammation could be considered a predictor of true-negative results. |
format | Online Article Text |
id | pubmed-9166573 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-91665732022-06-05 Computed tomography-guided cutting needle biopsy for lung nodules: when the biopsy-based benign results are real benign Hui, Hui Ma, Gao-Lei Yin, Hai-Tao Zhou, Yun Xie, Xiao-Mei Gao, Yong-Guang World J Surg Oncol Research BACKGROUND: Computed tomography (CT)-guided cutting needle biopsy (CNB) is an effective diagnostic method for lung nodules (LNs). The false-negative rate of CT-guided lung biopsy is reported to be up to 16%. This study aimed to determine the predictors of true-negative results in LNs with CNB-based benign results. METHODS: From January 2011 to December 2015, 96 patients with CNB-based nonspecific benign results were included in this study as the training group to detect predictors of true-negative results. From January 2016 to December 2018, an additional 57 patients were included as a validation group to test the reliability of the predictors. RESULTS: In the training group, a total of 96 patients underwent CT-guided CNB for 96 LNs. The CNB-based results were true negatives for 82 LNs and false negatives for 14 LNs. The negative predictive value of the CNB-based benign results was 85.4% (82/96). Univariate and multivariate logistic regression analyses revealed that CNB-based granulomatous inflammation (P = 0.013, hazard ratio = 0.110, 95% confidential interval = 0.019–0.625) was the independent predictor of true-negative results. The area under the receiver operator characteristic (ROC) curve was 0.697 (P = 0.019). In the validation group, biopsy results for 47 patients were true negative, and 10 were false negative. When the predictor was used on the validation group, the area under the ROC curve was 0.759 (P = 0.011). CONCLUSIONS: Most of the CNB-based benign results were true negatives, and CNB-based granulomatous inflammation could be considered a predictor of true-negative results. BioMed Central 2022-06-04 /pmc/articles/PMC9166573/ /pubmed/35659681 http://dx.doi.org/10.1186/s12957-022-02647-6 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Hui, Hui Ma, Gao-Lei Yin, Hai-Tao Zhou, Yun Xie, Xiao-Mei Gao, Yong-Guang Computed tomography-guided cutting needle biopsy for lung nodules: when the biopsy-based benign results are real benign |
title | Computed tomography-guided cutting needle biopsy for lung nodules: when the biopsy-based benign results are real benign |
title_full | Computed tomography-guided cutting needle biopsy for lung nodules: when the biopsy-based benign results are real benign |
title_fullStr | Computed tomography-guided cutting needle biopsy for lung nodules: when the biopsy-based benign results are real benign |
title_full_unstemmed | Computed tomography-guided cutting needle biopsy for lung nodules: when the biopsy-based benign results are real benign |
title_short | Computed tomography-guided cutting needle biopsy for lung nodules: when the biopsy-based benign results are real benign |
title_sort | computed tomography-guided cutting needle biopsy for lung nodules: when the biopsy-based benign results are real benign |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9166573/ https://www.ncbi.nlm.nih.gov/pubmed/35659681 http://dx.doi.org/10.1186/s12957-022-02647-6 |
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