4.7 Article

Revisiting susceptibility testing in MDR-TB by a standardized quantitative phenotypic assessment in a European multicentre study

Journal

JOURNAL OF ANTIMICROBIAL CHEMOTHERAPY
Volume 70, Issue 3, Pages 686-696

Publisher

OXFORD UNIV PRESS
DOI: 10.1093/jac/dku438

Keywords

antibiotic susceptibility testing; DST; antituberculous drugs; TB eXiST; MGIT

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Objectives: Treatment outcome of MDR-TB is critically dependent on the proper use of second-line drugs as per the result of in vitro drug susceptibility testing (DST). We aimed to establish a standardized DST procedure based on quantitative determination of drug resistance and compared the results with those of genotypes associated with drug resistance. Methods: The protocol, based on MGIT 960 and the TB eXiST software, was evaluated in nine European reference laboratories. Resistance detection at a screening drug concentration was followed by determination of resistance levels and estimation of the resistance proportion. Mutations in 14 gene regions were investigated using established techniques. Results: A total of 139 Mycobacterium tuberculosis isolates from patients with MDR-TB and resistance beyond MDR-TB were tested for 13 antituberculous drugs: isoniazid, rifampicin, rifabutin, ethambutol, pyrazinamide, streptomycin, para-aminosalicylic acid, ethionamide, amikacin, capreomycin, ofloxacin, moxifloxacin and linezolid. Concordance between phenotypic and genotypic resistance was >80%, except for ethambutol. Time to results was short (median 10 days). High-level resistance, which precludes the therapeutic use of an antituberculous drug, was observed in 49% of the isolates. The finding of a low or intermediate resistance level in 16% and 35% of the isolates, respectively, may help in designing an efficient personalized regimen for the treatment of MDR-TB patients. Conclusions: The automated DST procedure permits accurate and rapid quantitative resistance profiling of first- and second-line antituberculous drugs. Prospective validation is warranted to determine the impact on patient care.

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