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dc.contributor.authorNg, K.C.
dc.contributor.authorMeehan, Conor J.
dc.contributor.authorTorrea, G.
dc.contributor.authorGoeminne, L.
dc.contributor.authorDiels, M.
dc.contributor.authorRigouts, L.
dc.contributor.authorde Jong, B.C.
dc.contributor.authorAndré, E.
dc.date.accessioned2019-09-24T10:31:01Z
dc.date.accessioned2019-11-27T11:20:00Z
dc.date.available2019-09-24T10:31:01Z
dc.date.available2019-11-27T11:20:00Z
dc.date.issued2018-02
dc.identifier.citationNg KC, Meehan CJ, Torrea G et al (2018) Potential application of digitally linked tuberculosis diagnostics for real-time surveillance of drug-resistant tuberculosis transmission: Validation and analysis of test results. JMIR Medical Informatics. 6(1): e12.en_US
dc.identifier.urihttp://hdl.handle.net/10454/17512
dc.descriptionYesen_US
dc.description.abstractBackground: Tuberculosis (TB) is the highest-mortality infectious disease in the world and the main cause of death related to antimicrobial resistance, yet its surveillance is still paper-based. Rifampicin-resistant TB (RR-TB) is an urgent public health crisis. The World Health Organization has, since 2010, endorsed a series of rapid diagnostic tests (RDTs) that enable rapid detection of drug-resistant strains and produce large volumes of data. In parallel, most high-burden countries have adopted connectivity solutions that allow linking of diagnostics, real-time capture, and shared repository of these test results. However, these connected diagnostics and readily available test results are not used to their full capacity, as we have yet to capitalize on fully understanding the relationship between test results and specific rpoB mutations to elucidate its potential application to real-time surveillance. Objective: We aimed to validate and analyze RDT data in detail, and propose the potential use of connected diagnostics and associated test results for real-time evaluation of RR-TB transmission. Methods: We selected 107 RR-TB strains harboring 34 unique rpoB mutations, including 30 within the rifampicin resistance–determining region (RRDR), from the Belgian Coordinated Collections of Microorganisms, Antwerp, Belgium. We subjected these strains to Xpert MTB/RIF, GenoType MTBDRplus v2.0, and Genoscholar NTM + MDRTB II, the results of which were validated against the strains’ available rpoB gene sequences. We determined the reproducibility of the results, analyzed and visualized the probe reactions, and proposed these for potential use in evaluating transmission. Results: The RDT probe reactions detected most RRDR mutations tested, although we found a few critical discrepancies between observed results and manufacturers’ claims. Based on published frequencies of probe reactions and RRDR mutations, we found specific probe reactions with high potential use in transmission studies: Xpert MTB/RIF probes A, Bdelayed, C, and Edelayed; Genotype MTBDRplus v2.0 WT2, WT5, and WT6; and Genoscholar NTM + MDRTB II S1 and S3. Inspection of probe reactions of disputed mutations may potentially resolve discordance between genotypic and phenotypic test results. Conclusions: We propose a novel approach for potential real-time detection of RR-TB transmission through fully using digitally linked TB diagnostics and shared repository of test results. To our knowledge, this is the first pragmatic and scalable work in response to the consensus of world-renowned TB experts in 2016 on the potential of diagnostic connectivity to accelerate efforts to eliminate TB. This is evidenced by the ability of our proposed approach to facilitate comparison of probe reactions between different RDTs used in the same setting. Integrating this proposed approach as a plug-in module to a connectivity platform will increase usefulness of connected TB diagnostics for RR-TB outbreak detection through real-time investigation of suspected RR-TB transmission cases based on epidemiologic linking.en_US
dc.description.sponsorshipKCN was supported by Erasmus Mundus Joint Doctorate Fellowship grant 2016-1346, and BCdJ, LR, and CJM were supported by European Research Council-INTERRUPTB starting grant 311725.en_US
dc.language.isoenen_US
dc.relation.isreferencedbyhttps://doi.org/10.2196/medinform.9309en_US
dc.rights©Kamela Charmaine Ng, Conor Joseph Meehan, Gabriela Torrea, Léonie Goeminne, Maren Diels, Leen Rigouts, Bouke Catherine de Jong, Emmanuel André. Originally published in JMIR Medical Informatics (http://medinform.jmir.org), 27.02.2018. This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Medical Informatics, is properly cited. The complete bibliographic information, a link to the original publication on http://medinform.jmir.org/, as well as this copyright and license information must be included.en_US
dc.subjectTuberculosisen_US
dc.subjectDrug resistanceen_US
dc.subjectRifampicin-resistant tuberculosisen_US
dc.subjectRapid diagnostic testsen_US
dc.subjectXpert MTB/RIFen_US
dc.subjectGenotype MTBDRplus v2.0en_US
dc.subjectGenoscholar NTM + MDRTB IIen_US
dc.subjectRDT probe reactionsen_US
dc.subjectrpoB mutationsen_US
dc.subjectValidation and analysisen_US
dc.subjectReal-time detectionen_US
dc.titlePotential application of digitally linked tuberculosis diagnostics for real-time surveillance of drug-resistant tuberculosis transmission: Validation and analysis of test resultsen_US
dc.status.refereedYesen_US
dc.date.Accepted2018-01-09
dc.date.application2018-02-27
dc.typeArticleen_US
dc.type.versionPublished versionen_US
dc.date.updated2019-09-24T09:31:03Z
refterms.dateFOA2019-11-27T11:20:29Z


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