Browsing by Author "Bunyasi, Erick Wekesa"

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    Performance of Host Blood Transcriptomic Signatures for Diagnosing and Predicting Progression to Tuberculosis Disease in HIV-Negative Adults and Adolescents: A Systematic Review Protocol
    (BMJ open, 2019) Mulenga, Humphrey; Bunyasi, Erick Wekesa; Mbandi, Stanley Kimbung; Kagina, Benjamin; Scriba, Thomas; Hatherill, Mark
    One-quarter of the global population, including the majority of adults in tuberculosis (TB) endemic countries, are estimated to be Mycobacterium tuberculosis (MTB) infected. An estimated 10 million new TB cases occurred in 2017. One of the biggest challenges confronting TB control is the lack of accurate diagnosis and prediction of prevalent and incident TB disease, respectively. Several host blood transcriptomic messenger RNA (mRNA) signatures that reflect the host immune response following infection with MTB and progression to TB disease in different study populations have recently been published, but these TB biomarkers have not been systematically described. We will conduct a systematic review of the performance of host blood transcriptional signatures for TB diagnosis and prediction of progression to TB disease. This systematic review will involve conducting a comprehensive literature search of cohort, case–control, cross-sectional and randomised-controlled studies of the performance of host blood transcriptomic signatures for TB diagnosis and prediction of progression to TB disease. We will search Medline via PubMed, Scopus, Web of Science and EBSCO libraries, complemented by a search of bibliographies of selected articles for other relevant articles. The literature search will be restricted to studies published in English from 2005 to 2018 and conducted in HIV-uninfected adults and adolescents (≥12 years old). Forest plots and a narrative synthesis of the findings will be provided. The primary outcomes will be sensitivity, specificity, as well as true/false positives and true/false negatives. Heterogeneity resulting from differences in the design, composition and structure of individual signatures will preclude meta-analysis and pooling of results.