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Novel biomarker analysis of pleural effusion enhances differentiation of tuberculous from malignant pleural effusion

Overview of attention for article published in International Journal of General Medicine, June 2016
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Title
Novel biomarker analysis of pleural effusion enhances differentiation of tuberculous from malignant pleural effusion
Published in
International Journal of General Medicine, June 2016
DOI 10.2147/ijgm.s100237
Pubmed ID
Authors

Kuan-Yuan Chen, Po-Hao Feng, Chih-Cheng Chang, Tzu-Tao Chen, Hsiao-Chi Chuang, Chun-Nin Lee, Chien-Ling Su, Lian-Yu Lin, Kang-Yun Lee

Abstract

Lymphocytic pleurisy is commonly observed in tuberculosis and cancer. Noninvasive biomarkers are needed to distinguish tuberculous pleural effusion (TPE) from malignant pleural effusion (MPE) because current clinical diagnostic procedures are often invasive. We identified immune response biomarkers that can discriminate between TPE and MPE. Fourteen pleural effusion biomarkers were compared in 22 MPE patients and five TPE patients. Of the innate immunity biomarkers, the median levels of interleukin (IL)-1β and interferon-induced protein-10 (IP-10) were higher in TPE patients than in MPE patients (P<0.05 and P<0.01, respectively). Of the adaptive immunity biomarkers, the median levels of IL-13 and interferon-γ (IFN-γ) were higher in TPE patients than in MPE patients (P<0.05). In addition, the levels of basic fibroblast growth factor were higher in MPE patients than in TPE patients (P<0.05). Receiver operator characteristic analysis of these biomarkers was performed, resulting in the highest area under the curve (AUC) for IP-10 (AUC =0.95, 95% confidence interval, P<0.01), followed by IL-13 (AUC =0.86, 95% confidence interval, P<0.05). Our study shows that five biomarkers (IL-1β, IP-10, IFN-γ, IL-13, and basic fibroblast growth factor) have a potential diagnostic role in differentiating TPE from MPE, particularly in lung cancer-related MPE.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 27 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 27 100%

Demographic breakdown

Readers by professional status Count As %
Student > Postgraduate 5 19%
Student > Ph. D. Student 4 15%
Researcher 3 11%
Other 2 7%
Professor > Associate Professor 2 7%
Other 6 22%
Unknown 5 19%
Readers by discipline Count As %
Medicine and Dentistry 11 41%
Biochemistry, Genetics and Molecular Biology 4 15%
Agricultural and Biological Sciences 3 11%
Nursing and Health Professions 1 4%
Immunology and Microbiology 1 4%
Other 1 4%
Unknown 6 22%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 30 June 2016.
All research outputs
#22,758,309
of 25,373,627 outputs
Outputs from International Journal of General Medicine
#1,309
of 1,653 outputs
Outputs of similar age
#309,346
of 353,659 outputs
Outputs of similar age from International Journal of General Medicine
#11
of 12 outputs
Altmetric has tracked 25,373,627 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
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We're also able to compare this research output to 12 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.