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Nat Microbiol. 2019 Feb 25. doi: 10.1038/s41564-019-0380-2. [Epub ahead of print]

A systematic review of biomarkers to detect active tuberculosis.

Author information

1
Department of Epidemiology, Biostatistics, and Occupational Health, McGill University, Montreal, Québec, Canada.
2
FIND, Geneva, Switzerland.
3
McGill International TB Centre, Research Institute of the McGill University Health Centre, Montreal, Québec, Canada.
4
FIND, Geneva, Switzerland. cdenki@gmail.com.

Abstract

Millions of cases of tuberculosis (TB) go undiagnosed each year. Better diagnostic tools are urgently needed. Biomarker-based or multiple marker biosignature-based tests, ideally performed on blood or urine, for the detection of active TB might help to meet target product profiles proposed by the World Health Organization for point-of-care testing. We conducted a systematic review to summarize evidence on proposed biomarkers and biosignatures and evaluate their quality and level of evidence. We screened the titles and abstracts of 7,631 citations and included 443 publications that fulfilled the inclusion criteria and were published in 2010-2017. The types of biomarkers identified included antibodies, cytokines, metabolic activity markers, mycobacterial antigens and volatile organic compounds. Only 47% of studies reported a culture-based reference standard and diagnostic sensitivity and specificity. Forty-four biomarkers (4%) were identified in high-quality studies and met the target product profile minimum criteria, of which two have been incorporated into commercial assays. Of the 44 highest-quality biomarkers, 24 (55%) were multiple marker biosignatures. No meta-analyses were performed owing to between-study heterogeneity. In conclusion, TB biomarker discovery studies are often poorly designed and findings are rarely confirmed in independent studies. Few markers progress to a further developmental stage. More validation studies that consider the intended diagnostic use cases and apply rigorous design are needed. The extracted data from this review are currently being used by FIND as the foundation of a dynamic database in which biomarker data and developmental status will be presented.

PMID:
30804546
DOI:
10.1038/s41564-019-0380-2

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