Paper
21 May 2012 Breath-based biomarkers for tuberculosis
Arend H. J. Kolk, Joep J. B. N. van Berkel, Mareli M. Claassens, Elisabeth Walters, Sjoukje Kuijper, Jan W. Dallinga, Fredrik-Jan van Schooten
Author Affiliations +
Abstract
We investigated the potential of breath analysis by gas chromatography - mass spectrometry (GC-MS) to discriminate between samples collected prospectively from patients with suspected tuberculosis (TB). Samples were obtained in a TB endemic setting in South Africa where 28% of the culture proven TB patients had a Ziehl-Neelsen (ZN) negative sputum smear. A training set of breath samples from 50 sputum culture proven TB patients and 50 culture negative non-TB patients was analyzed by GC-MS. A classification model with 7 compounds resulted in a training set with a sensitivity of 72%, specificity of 86% and accuracy of 79% compared with culture. The classification model was validated with an independent set of breath samples from 21 TB and 50 non-TB patients. A sensitivity of 62%, specificity of 84% and accuracy of 77% was found. We conclude that the 7 volatile organic compounds (VOCs) that discriminate breath samples from TB and non-TB patients in our study population are probably host-response related VOCs and are not derived from the VOCs secreted by M. tuberculosis. It is concluded that at present GC-MS breath analysis is able to differentiate between TB and non-TB breath samples even among patients with a negative ZN sputum smear but a positive culture for M. tuberculosis. Further research is required to improve the sensitivity and specificity before this method can be used in routine laboratories.
© (2012) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Arend H. J. Kolk, Joep J. B. N. van Berkel, Mareli M. Claassens, Elisabeth Walters, Sjoukje Kuijper, Jan W. Dallinga, and Fredrik-Jan van Schooten "Breath-based biomarkers for tuberculosis", Proc. SPIE 8371, Sensing Technologies for Global Health, Military Medicine, Disaster Response, and Environmental Monitoring II; and Biometric Technology for Human Identification IX, 83710A (21 May 2012); https://doi.org/10.1117/12.918376
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KEYWORDS
Statistical analysis

Microscopy

Control systems

Diagnostic tests

Analytical research

Chest imaging

Chromatography

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