Innovo GenMax MTB-RIF/INH: a moderate-complexity automated NAAT for rapid simultaneous detection of Mycobacterium tuberculosis complex and rifampin/isoniazid resistance - Ou, Xichao; Zhao, Bing; Zheng, Huiwen; Xing, Ruida; Sun, Qian; Qin, Zhonghua; Zhang, Lixia; Cui, Kai; Song, Yuanyuan; Zheng, Yang; Zhou, Yang; Wang, Shengfen; et al. (Frontiers in Cellular and Infection Microbiology, 2025)
ObjectiveGiven the increase of treatment failure, relapse and acquired resistance observed in isoniazid (INH) resistance, there is an urgent to improve rifampin (RIF) -priority based diagnostic strategies. Therefore, we evaluated the performance of Innovo GenMax MTB-RIF/INH (GenMax), a moderate- complexity automated nucleic acid amplification test (NAAT), for detecting Mycobacterium tuberculosis complex (MTBC) and resistance to RIF and INH.MethodsAnalytical sensitivity (limit of detection, LOD) was determined using serial dilutions of Mycobacterium tuberculosis H37Rv (ATCC 27249) strains. Diagnostic accuracy was assessed in clinical sputum specimens against microbiological reference standards (MRS: positive by smear microscopy, culture or Xpert MTB/RIF for diagnosis of TB) and phenotypic drug susceptibility testing (DST). Discordant results were resolved by sequencing resistance genes (IS6110, rpoB, katG, inhA, ahpC) and follow-up diagnosis results.ResultsGenMax demonstrated a calculated LOD of 8.8 CFU/mL (95% CI: 7.4-11.4) for MTBC, 674.1 CFU/mL (95% CI: 578.8-923.5) for RIF resistance, and 747.3 CFU/mL (95% CI: 613.7-1081.3) for INH resistance. In clinical evaluation, the sensitivity and specificity for MTBC detection were 97.52% (95% CI: 92.38–99.36) and 93.65% (95% CI: 88.91–96.53), respectively. For RIF and INH resistance, sensitivities were 88.46% (95% CI: 68.72–96.97) and 85.19% (95% CI: 65.39–95.14), with specificity of 92.42% (95% CI: 82.50-97.18) and 94.12% (95% CI: 84.86-98.10).ConclusionInnovo GenMax MTB-RIF/INH is a rapid and automated assay with high sensitivity for MTBC detection, suitable for decentralized settings. While its performance for RIF/INH resistance detection is competitive with existing assays, its sensitivity remains gaps relative to WHO targets. Further optimization, particularly through expanded probe coverage, is needed to bridge this gap and ensure reliable detection in clinical settings.