Biomedical and Biotechnology Research Journal (Jan 2017)

Predictable repeatability issues with GeneXpert-Xpert MTB/RIF (version 4) derived rifampicin resistant tuberculosis results from South India: Appreciating the limits of a technological marvel!

  • Praveen Sanker,
  • Ramya Puthukkudi Kottuthodi,
  • Anusree Puthenveettil Ambika,
  • Vishnu T Santhosh,
  • Ravikrishnan Balakrishnan,
  • Sunil Kumar Mrithunjayan,
  • Hisham Moosan

DOI
https://doi.org/10.4103/bbrj.bbrj_6_17
Journal volume & issue
Vol. 1, no. 1
pp. 76 – 80

Abstract

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Background: GeneXpert MTB/RIF (Xpert), the fully automated cartridge-based nucleic acid amplification test for simultaneous identification of Mycobacterium tuberculosis complex and rifampicin resistance (RR), directly from samples is considered as a game changer for tuberculosis (TB) control programs worldwide. Methods: We are reporting serious issues with repeatability among a subgroup of Xpert (Version 4) identified RR results from South Indian state recently switched to Xpert by the National TB control program. Results: We have demonstrated that poor repeatability is frequently associated with those Xpert derived RR results, identified by detection of delayed amplification of any probe in the presence of positive analyte results for all probes. Another significant contributing factor was found to be lower bacterial loads in samples. The repeat tests were done by Xpert and/or by line probe assay depending on smear positivity. The finding is worrying as Xpert is recommended over other tests due to its reportedly better performance among low bacterial load samples such as pediatric, extra-pulmonary, HIV-TB co-infected, and smear negative pulmonary TB and the same samples, it seems are more likely to cause error prone RR results. Conclusions: We recommend for additional genotypic tests with specific mutant probes for detecting mutations at rpoB hot sites and growth based tests for all Xpert derived RR-TB cases identified by the above algorithm for confirmation of the presence of mutation, based on our available data.

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