- Syed, Rehan R;
- Catanzaro, Donald G;
- Colman, Rebecca E;
- Cooney, Christopher G;
- Linger, Yvonne;
- Kukhtin, Alexander V;
- Holmberg, Rebecca C;
- Norville, Ryan;
- Crudu, Valeriu;
- Ciobanu, Nelly;
- Codreanu, Alexandru;
- Seifert, Marva;
- Hillery, Naomi;
- Chiles, Peter;
- Catanzaro, Antonino;
- Rodwell, Timothy C
- Editor(s): Turenne, Christine Y
While the goal of universal drug susceptibility testing has been a key component of the WHO End TB Strategy, in practice, this remains inaccessible to many. Rapid molecular tests for tuberculosis (TB) and antituberculosis drug resistance could significantly improve access to testing. In this study, we evaluated the accuracy of the Akonni Biosystems XDR-TB (extensively drug-resistant TB) TruArray and lateral-flow-cell (XDR-LFC) assay (Akonni Biosystems, Inc., Frederick, MD, USA), a novel assay that detects mutations in seven genes associated with resistance to antituberculosis drugs: katG, the inhA promoter, and the ahpC promoter for isoniazid; rpoB for rifampin; gyrA for fluoroquinolones; rrs and the eis promoter for kanamycin; and rrs for capreomycin and amikacin. We evaluated assay performance using direct sputum samples from 566 participants recruited in a prospective cohort in Moldova over 2 years. The sensitivity and specificity against the phenotypic reference were both 100% for isoniazid, 99.2% and 97.9% for rifampin, 84.8% and 99.1% for fluoroquinolones, 87.0% and 84.1% for kanamycin, 54.3% and 100% for capreomycin, and 79.2% and 100% for amikacin, respectively. Whole-genome sequencing data for a subsample of 272 isolates showed 95 to 99% concordance with the XDR-LFC-reported suspected mutations. The XDR-LFC assay demonstrated a high level of accuracy for multiple drugs and met the WHO's minimum target product profile criteria for isoniazid and rifampin, while the sensitivity for fluoroquinolones and amikacin fell below target thresholds, likely due to the absence of a gyrB target in the assay. With optimization, the XDR-LFC shows promise as a novel near-patient technology to rapidly diagnose drug-resistant tuberculosis.