Title |
Urine IP-10 as a biomarker of therapeutic response in patients with active pulmonary tuberculosis
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Published in |
BMC Infectious Diseases, May 2018
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DOI | 10.1186/s12879-018-3144-3 |
Pubmed ID | |
Authors |
Song Yee Kim, Jungho Kim, Deok Ryun Kim, Young Ae Kang, Sungyoung Bong, Jonghee Lee, Suyeon Kim, Nam Suk Lee, Bora Sim, Sang-Nae Cho, Young Sam Kim, Hyejon Lee |
Abstract |
Prior to clinical trials of new TB drugs or therapeutic vaccines, it is necessary to develop monitoring tools to predict treatment outcomes in TB patients. Urine interferon gamma inducible protein 10 (IP-10) is a potential biomarker of treatment response in chronic hepatitis C virus infection and lung diseases, including tuberculosis. In this study, we assessed IP-10 levels in urine samples from patients with active TB at diagnosis, during treatment, and at completion, and compared these with levels in serum samples collected in parallel from matched patients to determine whether urine IP-10 can be used to monitor treatment response in patients with active TB. IP-10 was measured using enzyme-linked immunosorbent assays in urine and serum samples collected concomitantly from 23 patients with active TB and 21 healthy adults (44 total individuals). The Mann-Whitney U test and Wilcoxon matched-pairs signed rank test were used for comparisons among healthy controls and patients at three time points, and LOESS regression was used for longitudinal data. The levels of IP-10 in urine increased significantly after 2 months of treatment (P = 0.0163), but decreased by the completion of treatment (P = 0.0035). Serum IP-10 levels exhibited a similar trend, but did not increase significantly after 2 months of treatment in patients with active TB. Unstimulated IP-10 in urine can be used as a biomarker to monitor treatment response in patients with active pulmonary TB. |
X Demographics
Geographical breakdown
Country | Count | As % |
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Venezuela, Bolivarian Republic of | 1 | 50% |
Unknown | 1 | 50% |
Demographic breakdown
Type | Count | As % |
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Scientists | 1 | 50% |
Practitioners (doctors, other healthcare professionals) | 1 | 50% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 80 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Master | 12 | 15% |
Student > Bachelor | 10 | 13% |
Researcher | 8 | 10% |
Student > Postgraduate | 6 | 8% |
Student > Ph. D. Student | 5 | 6% |
Other | 10 | 13% |
Unknown | 29 | 36% |
Readers by discipline | Count | As % |
---|---|---|
Medicine and Dentistry | 18 | 23% |
Immunology and Microbiology | 11 | 14% |
Biochemistry, Genetics and Molecular Biology | 8 | 10% |
Agricultural and Biological Sciences | 5 | 6% |
Nursing and Health Professions | 3 | 4% |
Other | 6 | 8% |
Unknown | 29 | 36% |