Clinical implications of molecular drug resistance testing for Mycobacterium tuberculosis : a 2023 TBnet/RESIST-TB consensus statement
Copyright © 2023 Elsevier Ltd. All rights reserved..
Drug-resistant tuberculosis is a substantial health-care concern worldwide. Despite culture-based methods being considered the gold standard for drug susceptibility testing, molecular methods provide rapid information about the Mycobacterium tuberculosis mutations associated with resistance to anti-tuberculosis drugs. This consensus document was developed on the basis of a comprehensive literature search, by the TBnet and RESIST-TB networks, about reporting standards for the clinical use of molecular drug susceptibility testing. Review and the search for evidence included hand-searching journals and searching electronic databases. The panel identified studies that linked mutations in genomic regions of M tuberculosis with treatment outcome data. Implementation of molecular testing for the prediction of drug resistance in M tuberculosis is key. Detection of mutations in clinical isolates has implications for the clinical management of patients with multidrug-resistant or rifampicin-resistant tuberculosis, especially in situations when phenotypic drug susceptibility testing is not available. A multidisciplinary team including clinicians, microbiologists, and laboratory scientists reached a consensus on key questions relevant to molecular prediction of drug susceptibility or resistance to M tuberculosis, and their implications for clinical practice. This consensus document should help clinicians in the management of patients with tuberculosis, providing guidance for the design of treatment regimens and optimising outcomes.
| Errataetall: |
ErratumIn: Lancet Infect Dis. 2023 Mar 28;:. - PMID 37001542 |
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| Medienart: |
E-Artikel |
| Erscheinungsjahr: |
2023 |
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| Erschienen: |
2023 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:23 |
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| Enthalten in: |
The Lancet. Infectious diseases - 23(2023), 4 vom: 06. Apr., Seite e122-e137 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Domínguez, José [VerfasserIn] |
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| Links: |
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| Themen: |
Antitubercular Agents |
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| Anmerkungen: |
Date Completed 28.03.2023 Date Revised 13.04.2023 published: Print-Electronic ErratumIn: Lancet Infect Dis. 2023 Mar 28;:. - PMID 37001542 Citation Status MEDLINE |
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| doi: |
10.1016/S1473-3099(22)00875-1 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| PPN (Katalog-ID): |
NLM353741493 |
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| 520 | |a Drug-resistant tuberculosis is a substantial health-care concern worldwide. Despite culture-based methods being considered the gold standard for drug susceptibility testing, molecular methods provide rapid information about the Mycobacterium tuberculosis mutations associated with resistance to anti-tuberculosis drugs. This consensus document was developed on the basis of a comprehensive literature search, by the TBnet and RESIST-TB networks, about reporting standards for the clinical use of molecular drug susceptibility testing. Review and the search for evidence included hand-searching journals and searching electronic databases. The panel identified studies that linked mutations in genomic regions of M tuberculosis with treatment outcome data. Implementation of molecular testing for the prediction of drug resistance in M tuberculosis is key. Detection of mutations in clinical isolates has implications for the clinical management of patients with multidrug-resistant or rifampicin-resistant tuberculosis, especially in situations when phenotypic drug susceptibility testing is not available. A multidisciplinary team including clinicians, microbiologists, and laboratory scientists reached a consensus on key questions relevant to molecular prediction of drug susceptibility or resistance to M tuberculosis, and their implications for clinical practice. This consensus document should help clinicians in the management of patients with tuberculosis, providing guidance for the design of treatment regimens and optimising outcomes | ||
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| 700 | 1 | |a Cox, Vivian |e investigator |4 oth | |
| 700 | 1 | |a Dheda, Keertan |e investigator |4 oth | |
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| 700 | 1 | |a Gröschel, Matthias I |e investigator |4 oth | |
| 700 | 1 | |a Guglielmetti, Lorenzo |e investigator |4 oth | |
| 700 | 1 | |a Kontsevaya, Irina |e investigator |4 oth | |
| 700 | 1 | |a Lange, Berit |e investigator |4 oth | |
| 700 | 1 | |a van Leth, Frank |e investigator |4 oth | |
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| 700 | 1 | |a Lange, Christoph |e investigator |4 oth | |
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