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Prediction of malignancy in mediastinal lymph nodes during endobronchial ultrasound: A comparative validation study

BACKGROUND: In this study, we aimed to compare the diagnostic performances of three existing prediction tools in visually identifying a malignant lymph node. METHODS: Between April 2016 and January 2021, a total of 827 lymph nodes of 259 patients (211 males, 48 females; mean age: 61.1±7.2 years; ran...

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Autores principales: Şafak Alıcı, Nur, Alıcı, İbrahim Onur
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Bayçınar Medical Publishing 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10012973/
https://www.ncbi.nlm.nih.gov/pubmed/36926164
http://dx.doi.org/10.5606/tgkdc.dergisi.2023.22276
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author Şafak Alıcı, Nur
Alıcı, İbrahim Onur
author_facet Şafak Alıcı, Nur
Alıcı, İbrahim Onur
author_sort Şafak Alıcı, Nur
collection PubMed
description BACKGROUND: In this study, we aimed to compare the diagnostic performances of three existing prediction tools in visually identifying a malignant lymph node. METHODS: Between April 2016 and January 2021, a total of 827 lymph nodes of 259 patients (211 males, 48 females; mean age: 61.1±7.2 years; range, 41 to 79 years) who underwent endobronchial ultrasound procedure for diagnosis and/or staging of lung cancer and diagnosis of mediastinal lymphadenopathy of unknown origin were retrospectively analyzed. This external validation study was designed to compare the diagnostic yields of the prediction tools developed by Shafiek et al., Alici et al., and Canada Lymph Node Score (CLNS). Endobronchial ultrasoundguided transbronchial needle aspiration results and predictions were compared to gold-standard tool. RESULTS: Overall, endobronchial ultrasound-guided transbronchial needle aspiration had a sensitivity, specificity, positive and negative predictive value, and accuracy of 95.6%, 100%, 100%, 97.6%, and 98.4%, respectively. Diagnostic performances of proposed tools were quite remarkable. Among them, Alici algorithm had a higher sensitivity and negative predictive value, which were matched by excellent specificity and positive predictive value offered by CLNS ≥3 and Shafiek tool. The area under the curve value of CLNS ≥3 was higher than Shafiek tool and CLNS ≥2. CONCLUSION: Conventional prediction tools relying on simple real-time sonographic features were found to be consistent by the means of diagnostic performance in this external validation dataset. Despite being inferior to cytology, their superior performance was proven with defined individual strengths and weaknesses.
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spelling pubmed-100129732023-03-15 Prediction of malignancy in mediastinal lymph nodes during endobronchial ultrasound: A comparative validation study Şafak Alıcı, Nur Alıcı, İbrahim Onur Turk Gogus Kalp Damar Cerrahisi Derg Original Article BACKGROUND: In this study, we aimed to compare the diagnostic performances of three existing prediction tools in visually identifying a malignant lymph node. METHODS: Between April 2016 and January 2021, a total of 827 lymph nodes of 259 patients (211 males, 48 females; mean age: 61.1±7.2 years; range, 41 to 79 years) who underwent endobronchial ultrasound procedure for diagnosis and/or staging of lung cancer and diagnosis of mediastinal lymphadenopathy of unknown origin were retrospectively analyzed. This external validation study was designed to compare the diagnostic yields of the prediction tools developed by Shafiek et al., Alici et al., and Canada Lymph Node Score (CLNS). Endobronchial ultrasoundguided transbronchial needle aspiration results and predictions were compared to gold-standard tool. RESULTS: Overall, endobronchial ultrasound-guided transbronchial needle aspiration had a sensitivity, specificity, positive and negative predictive value, and accuracy of 95.6%, 100%, 100%, 97.6%, and 98.4%, respectively. Diagnostic performances of proposed tools were quite remarkable. Among them, Alici algorithm had a higher sensitivity and negative predictive value, which were matched by excellent specificity and positive predictive value offered by CLNS ≥3 and Shafiek tool. The area under the curve value of CLNS ≥3 was higher than Shafiek tool and CLNS ≥2. CONCLUSION: Conventional prediction tools relying on simple real-time sonographic features were found to be consistent by the means of diagnostic performance in this external validation dataset. Despite being inferior to cytology, their superior performance was proven with defined individual strengths and weaknesses. Bayçınar Medical Publishing 2023-01-30 /pmc/articles/PMC10012973/ /pubmed/36926164 http://dx.doi.org/10.5606/tgkdc.dergisi.2023.22276 Text en Copyright © 2023, Turkish Society of Cardiovascular Surgery https://creativecommons.org/licenses/by-nc/4.0/This is an open access article under the terms of the Creative Commons Attribution-NonCommercial License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.
spellingShingle Original Article
Şafak Alıcı, Nur
Alıcı, İbrahim Onur
Prediction of malignancy in mediastinal lymph nodes during endobronchial ultrasound: A comparative validation study
title Prediction of malignancy in mediastinal lymph nodes during endobronchial ultrasound: A comparative validation study
title_full Prediction of malignancy in mediastinal lymph nodes during endobronchial ultrasound: A comparative validation study
title_fullStr Prediction of malignancy in mediastinal lymph nodes during endobronchial ultrasound: A comparative validation study
title_full_unstemmed Prediction of malignancy in mediastinal lymph nodes during endobronchial ultrasound: A comparative validation study
title_short Prediction of malignancy in mediastinal lymph nodes during endobronchial ultrasound: A comparative validation study
title_sort prediction of malignancy in mediastinal lymph nodes during endobronchial ultrasound: a comparative validation study
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10012973/
https://www.ncbi.nlm.nih.gov/pubmed/36926164
http://dx.doi.org/10.5606/tgkdc.dergisi.2023.22276
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