Statistical Analysis of Interferon-γ for the Effectiveness of an Anti-Tuberculous Treatment
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Statistical Analysis of Interferon-γ for the Effectiveness of an Anti-Tuberculous Treatment

Authors: Shishen Xie, Yingda L. Xie

Abstract:

Tuberculosis (TB) is a potentially serious infectious disease that remains a health concern. The Interferon Gamma Release Assay (IGRA) is a blood test to find out if an individual is tuberculous positive or negative. This study applies statistical analysis to the clinical data of interferon-gamma levels of seventy-three subjects who diagnosed pulmonary TB in an anti-tuberculous treatment. Data analysis is performed to determine if there is a significant decline in interferon-gamma levels for the subjects during a period of six months, and to infer if the anti-tuberculous treatment is effective.

Keywords: Data analysis, interferon gamma release assay, statistical methods, tuberculosis infection.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1125833

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References:


[1] Centers for Disease Control & Prevention, Tuberculosis (TB) Fact Sheets: Tuberculin Skin Testing, Atlanta, GA, U.S. Retrieved Sept. 29, 2015, http://www.cdc.gov/tb/publications/factsheets/testing/ skintesting.htm.
[2] ECDC (Europe Center for Disease Prevention and Control) GUIDANCE: Use of interferon-gamma release assays in support of TB diagnosis, Stockholm, March 2011. ISBN 978-92-9193-240-5.
[3] Kobashi, Y., Mouri, K., Yagi, S., Obase, Y., Miyashita, N., and Oka, M., “Transitional changes in T-cell responses to Mycobacterium tuberculosis-specific antigens during treatment”, Journal of Infection, vol. 58, no. 3, pp. 197–204, 2009.
[4] Madigan, Michael T., et al. Brock Biology of Microorganisms: Thirteenth edition. Benjamin Cummings: Boston, 2012.
[5] Menzies, D., “Interpretation of repeated tuberculin tests. Boosting, conversion, and reversion”, Am J Respir Crit Care Med, 1999. 159(1): p. 15-21.
[6] Ronald P. Cody and Jefferey K. Smith, Applied Statiistics and the SAS Programming Language, 5th ed. Pearson Prentice Hall; 2006.
[7] Sauzullo, I., Mengoni, F., Lichtner, M. et al., “In vivo and in vitro effects of antituberculosis treatment on mycobacterial interferon-γ T cell response,” PLoS ONE, vol. 4, no. 4, Article ID e5187, 2009.
[8] World Health Organization Global Tuberculosis Report 2015, Executive Summary pp 1 – 3. 2015.