alexa Discrimination of exudative pleural effusions based on multiple biological parameters.
Bioinformatics & Systems Biology

Bioinformatics & Systems Biology

Metabolomics:Open Access

Author(s): Daniil ZD, Zintzaras E, Kiropoulos T, Papaioannou AI, Koutsokera A,

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Abstract Pleural effusion is a common complication of various diseases. Conventional methods are not always capable of establishing the cause of pleural effusion, so alternative tests are needed. The aim of this study was to explore means of discriminating between different pleural effusion groups, malignant, parapneumonic and tuberculous, based on the combined function of seven biological markers. Adenosine deaminase (ADA), interferon-gamma, C-reactive protein (CRP), carcinoembryonic antigen, interleukin-6, tumour necrosis factor-alpha and vascular endothelial growth factor concentration levels were measured in pleural fluid from 45 patients with malignant, 15 with parapneumonic and 12 with tuberculous pleural effusion. Receiver operating characteristic curve analysis, multinomial logit modelling and canonical variate analysis were applied to discriminate the pleural effusion groups. The three groups could be discriminated successfully using the measured markers. The most important parameters for discrimination were ADA and CRP concentration levels. An individual with an ADA concentration level of >45 U.L(-1) and a CRP concentration of <4 mg.dL(-1) was more likely to belong to the tuberculous pleural effusion group, whereas one with an ADA concentration level of <40 U.L(-1) and a CRP concentration of >6 mg.dL(-1) was more likely to belong to the parapneumonic pleural effusion group, and one with a CRP concentration of <4 mg.dL(-1) to the malignant pleural effusion group. The combination of adenosine deaminase and C-reactive protein levels might be sufficient for discriminating between the three different groups of exudative pleural effusion: malignant, tuberculous and parapneumonic. This article was published in Eur Respir J and referenced in Metabolomics:Open Access

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