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Combining ADA, Protein and IFN- γ Best Allows Discrimination Between Tuberculous and Malignant Pleural Effusion

BACKGROUND: The purpose of this study is to assess the usefulness of various enzymes, cytokines and biochemical studies of pleural fluid for the differential diagnosis of tuberculosis from malignant pleural effusions, and to clarify the role of combining diagnostic tests. METHODS: The study group in...

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Autores principales: Kim, Young-Chul, Park, Kyung-Ok, Bom, Hee-Seung, Lim, Sung-Chul, Park, Hyung-Kwan, Na, Hyun-Ju, Park, Jae-Hee
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Korean Association of Internal Medicine 1997
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4531991/
https://www.ncbi.nlm.nih.gov/pubmed/9439159
http://dx.doi.org/10.3904/kjim.1997.12.2.225
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author Kim, Young-Chul
Park, Kyung-Ok
Bom, Hee-Seung
Lim, Sung-Chul
Park, Hyung-Kwan
Na, Hyun-Ju
Park, Jae-Hee
author_facet Kim, Young-Chul
Park, Kyung-Ok
Bom, Hee-Seung
Lim, Sung-Chul
Park, Hyung-Kwan
Na, Hyun-Ju
Park, Jae-Hee
author_sort Kim, Young-Chul
collection PubMed
description BACKGROUND: The purpose of this study is to assess the usefulness of various enzymes, cytokines and biochemical studies of pleural fluid for the differential diagnosis of tuberculosis from malignant pleural effusions, and to clarify the role of combining diagnostic tests. METHODS: The study group included 39 cases with tuberculous effusions and 31 cases with malignant effusions, whose diagnoses were confirmed by pleural biopsy, cytology or microbiological methods. We compared pleural fluid levels of ADA, TNF-α, IFN-γ, IL-2, IL-6, IL-8, pH, protein, glucose, cholesterol, triglyceride, amylase and lactic dehydrogenase between tuberculous and malignant effusions. Using stepwise logistic regression analysis, we evaluated the benefit of combining various parameters. Receiver operating characteristic (ROC) curves of ADA, cytokines and equations generated from regression analyses were plotted and compared with the area under curve (AUC). Cut-off values showing the best diagnostic accuracy were selected and compared. RESULTS: Compared to malignant effusion, tuberculous effusion showed significantly higher levels of ADA, IFN-γ, TNF-α and IL-2. There was a good correlation between IFN-γ and TNF-α. By stepwise logistic regression analysis, IFN-γ, protein and ADA were independent variables predicting tuberculous from malignant effusions. The diagnostic accuracy and AUC of regression equation was greater than any other single parameters. CONCLUSION: For the differential diagnosis of tuberculosis and malignant pleural effusions, combining ADA, protein and IFN-γ best allows discrimination.
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spelling pubmed-45319912015-10-02 Combining ADA, Protein and IFN- γ Best Allows Discrimination Between Tuberculous and Malignant Pleural Effusion Kim, Young-Chul Park, Kyung-Ok Bom, Hee-Seung Lim, Sung-Chul Park, Hyung-Kwan Na, Hyun-Ju Park, Jae-Hee Korean J Intern Med Original Article BACKGROUND: The purpose of this study is to assess the usefulness of various enzymes, cytokines and biochemical studies of pleural fluid for the differential diagnosis of tuberculosis from malignant pleural effusions, and to clarify the role of combining diagnostic tests. METHODS: The study group included 39 cases with tuberculous effusions and 31 cases with malignant effusions, whose diagnoses were confirmed by pleural biopsy, cytology or microbiological methods. We compared pleural fluid levels of ADA, TNF-α, IFN-γ, IL-2, IL-6, IL-8, pH, protein, glucose, cholesterol, triglyceride, amylase and lactic dehydrogenase between tuberculous and malignant effusions. Using stepwise logistic regression analysis, we evaluated the benefit of combining various parameters. Receiver operating characteristic (ROC) curves of ADA, cytokines and equations generated from regression analyses were plotted and compared with the area under curve (AUC). Cut-off values showing the best diagnostic accuracy were selected and compared. RESULTS: Compared to malignant effusion, tuberculous effusion showed significantly higher levels of ADA, IFN-γ, TNF-α and IL-2. There was a good correlation between IFN-γ and TNF-α. By stepwise logistic regression analysis, IFN-γ, protein and ADA were independent variables predicting tuberculous from malignant effusions. The diagnostic accuracy and AUC of regression equation was greater than any other single parameters. CONCLUSION: For the differential diagnosis of tuberculosis and malignant pleural effusions, combining ADA, protein and IFN-γ best allows discrimination. Korean Association of Internal Medicine 1997-06 /pmc/articles/PMC4531991/ /pubmed/9439159 http://dx.doi.org/10.3904/kjim.1997.12.2.225 Text en Copyright © 1997 The Korean Association of Internal Medicine This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0/) which permits unrestricted noncommercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Article
Kim, Young-Chul
Park, Kyung-Ok
Bom, Hee-Seung
Lim, Sung-Chul
Park, Hyung-Kwan
Na, Hyun-Ju
Park, Jae-Hee
Combining ADA, Protein and IFN- γ Best Allows Discrimination Between Tuberculous and Malignant Pleural Effusion
title Combining ADA, Protein and IFN- γ Best Allows Discrimination Between Tuberculous and Malignant Pleural Effusion
title_full Combining ADA, Protein and IFN- γ Best Allows Discrimination Between Tuberculous and Malignant Pleural Effusion
title_fullStr Combining ADA, Protein and IFN- γ Best Allows Discrimination Between Tuberculous and Malignant Pleural Effusion
title_full_unstemmed Combining ADA, Protein and IFN- γ Best Allows Discrimination Between Tuberculous and Malignant Pleural Effusion
title_short Combining ADA, Protein and IFN- γ Best Allows Discrimination Between Tuberculous and Malignant Pleural Effusion
title_sort combining ada, protein and ifn- γ best allows discrimination between tuberculous and malignant pleural effusion
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4531991/
https://www.ncbi.nlm.nih.gov/pubmed/9439159
http://dx.doi.org/10.3904/kjim.1997.12.2.225
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