The performance of Xpert MTB/RIF and MTBDRplus within a Programmatic setting at TB Laboratory in Rio de Janeiro, Brazil.

Thiago da Silva Santos Malaquias, Eunice Petris Ribeiro, Tatiana Cristina Pereira Dutra, Marina Ricardo, Richard Salvato, Marcela Bhering, Daniella Castanheira Bartholomeu, Elis Regina Dalla-Costa, Miguel Viveiros, Elisangela Costa da Silva, Afr��nio Kritski
Author Information
  1. Thiago da Silva Santos Malaquias: Universidade Federal do Rio de Janeiro, Faculdade de Medicina, Programa Acad��mico de Tuberculose, Rio de Janeiro, RJ, Brasil. ORCID
  2. Eunice Petris Ribeiro: Universidade Federal do Rio de Janeiro, Faculdade de Medicina, Programa Acad��mico de Tuberculose, Rio de Janeiro, RJ, Brasil. ORCID
  3. Tatiana Cristina Pereira Dutra: Universidade Federal do Rio de Janeiro, Faculdade de Medicina, Programa Acad��mico de Tuberculose, Rio de Janeiro, RJ, Brasil. ORCID
  4. Marina Ricardo: Universidade Federal do Rio de Janeiro, Faculdade de Medicina, Programa Acad��mico de Tuberculose, Rio de Janeiro, RJ, Brasil. ORCID
  5. Richard Salvato: Secretaria Estadual da Sa��de do Rio Grande do Sul, Centro de Desenvolvimento Cient��fico e Tecnol��gico, Porto Alegre, RS, Brasil. ORCID
  6. Marcela Bhering: Universidade Federal do Rio de Janeiro, Faculdade de Medicina, Programa Acad��mico de Tuberculose, Rio de Janeiro, RJ, Brasil. ORCID
  7. Daniella Castanheira Bartholomeu: Universidade Federal de Minas Gerais, Instituto de Ci��ncias Biol��gica, Departamento de Parasitologia, Belo Horizonte, MG, Brasil. ORCID
  8. Elis Regina Dalla-Costa: Universidade Federal do Rio de Janeiro, Faculdade de Medicina, Programa Acad��mico de Tuberculose, Rio de Janeiro, RJ, Brasil. ORCID
  9. Miguel Viveiros: Universidade Nova de Lisboa, Instituto de Higiene e Medicina Tropical, Lisboa, Portugal. ORCID
  10. Elisangela Costa da Silva: Universidade Federal do Rio de Janeiro, Faculdade de Medicina, Programa Acad��mico de Tuberculose, Rio de Janeiro, RJ, Brasil. ORCID
  11. Afr��nio Kritski: Universidade Federal do Rio de Janeiro, Faculdade de Medicina, Programa Acad��mico de Tuberculose, Rio de Janeiro, RJ, Brasil. ORCID

Abstract

BACKGROUND: Few studies in routine settings have confirmed the high accuracy of the Xpert MTB/RIF assay for detecting rifampicin resistance (RR) and the first-line probe assay (FL-LPA) for detecting both RR and isoniazid resistance (INHR).
METHODS: The performance of Xpert MTB/RIF and MTBDRplus VER 2.0 LPA was evaluated in 180 Mycobacterium tuberculosis samples collected from January 2018 to December 2019 in Rio de Janeiro, Brazil. The results were compared with those from BACTEC MGIT 960 culture and drug susceptibility testing (DST). Whole-genome sequencing was performed on the samples with discordant results.
RESULTS: The Xpert MTB/RIF assay showed a sensitivity (Se) of 93.3% and a specificity (Sp) of 97.6%, detecting RR. The performance of FL-LPA to identify RIF and INH resistance was, respectively, (Se) 100% and 83.3% and (Sp) 98.8% and 100%. Among 18 clinical isolates with INHR detected by FL-LPA, mutations in the katG gene were observed in 100% of samples, of which only two (11.1%) had mutations in both katG and inhA genes. Overall, the discordant results were identified in 9 (5%) samples. Among the four Xpert RIF-resistant and DST-sensitive, two harbored mutations in rpoB Leu430Pro. Among the four FL-LPA-sensitive and DST-resistant, one had a mutation in inhA 17G>T. FL-LPA showed high accuracy in detecting RR and INHR.
CONCLUSIONS: The MTBDRplus test demonstrated excellent performance in detecting RR, and INHR in clinical isolates under routine conditions at a reference laboratory in Rio de Janeiro, Brazil. Incorporating both tests can improve drug-resistant tuberculosis treatment outcomes and monitor the INHR incidence.

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MeSH Term

Mycobacterium tuberculosis
Humans
Rifampin
Sensitivity and Specificity
Microbial Sensitivity Tests
Tuberculosis, Multidrug-Resistant
Isoniazid
Brazil
Antibiotics, Antitubercular
Antitubercular Agents
Mutation
Whole Genome Sequencing

Chemicals

Rifampin
Isoniazid
Antibiotics, Antitubercular
Antitubercular Agents

Word Cloud

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