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DNA Sequencing Predicts 1st-Line Tuberculosis Drug Susceptibility Profiles

BACKGROUND: The World Health Organization recommends universal drug susceptibility testing for Mycobacterium tuberculosis complex to guide treatment decisions and improve outcomes. We assessed whether DNA sequencing can accurately predict antibiotic susceptibility profiles for first-line anti-tuberc...

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Detalles Bibliográficos
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Massachusetts Medical Society 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6121966/
https://www.ncbi.nlm.nih.gov/pubmed/30280646
http://dx.doi.org/10.1056/NEJMoa1800474
Descripción
Sumario:BACKGROUND: The World Health Organization recommends universal drug susceptibility testing for Mycobacterium tuberculosis complex to guide treatment decisions and improve outcomes. We assessed whether DNA sequencing can accurately predict antibiotic susceptibility profiles for first-line anti-tuberculosis drugs. METHODS: Whole-genome sequences and associated phenotypes to isoniazid, rifampicin, ethambutol and pyrazinamide were obtained for isolates from 16 countries across six continents. For each isolate, mutations associated with drug-resistance and drug-susceptibility were identified across nine genes, and individual phenotypes were predicted unless mutations of unknown association were also present. To identify how whole-genome sequencing might direct first-line drug therapy, complete susceptibility profiles were predicted. These were predicted to be pan-susceptible if predicted susceptible to isoniazid and to other drugs, or contained mutations of unknown association in genes affecting these other drugs. We simulated how negative predictive value changed with drug-resistance prevalence. RESULTS: 10,209 isolates were analysed. The greatest proportion of phenotypes were predicted for rifampicin (9,660/10,130; (95.4%)) and the lowest for ethambutol (8,794/9,794; (89.8%)). Isoniazid, rifampicin, ethambutol and pyrazinamide resistance was correctly predicted with 97.1%, 97.5% 94.6% and 91.3% sensitivity, and susceptibility with 99.0%, 98.8%, 93.6% and 96.8% specificity, respectively. 5,250 (89.5%) drug profiles were correctly predicted for 5,865/7,516 (78.0%) isolates with complete phenotypic profiles. Among these, 3,952/4,037 (97.9%) predictions of pan-susceptibility were correct. The negative predictive value for 97.5% of simulated drug profiles exceeded 95% where the prevalence of drug-resistance was below 47.0%. CONCLUSIONS: Phenotypic testing for first-line drugs can be phased down in favour of DNA sequencing to guide anti- tuberculosis drug therapy.