Table 1_Comparison and evaluation of metagenomic next-generation sequencing (mNGS) and real-time PCR for the detection of Mycobacterium tuberculosis.docx

ObjectiveThis study aimed to evaluate and compare the performance of metagenomic next-generation sequencing (mNGS) and real-time polymerase chain reaction (RT-PCR) for the detection of Mycobacterium tuberculosis (MTB) in patients with suspected tuberculosis (TB).
MethodsSamples from patients undergoing routine clinical testing for MTB using both mNGS and RT-PCR were included. The diagnostic agreement between the two methods was assessed. Discordant results were further validated using the Xpert MTB/RIF assay on cryopreserved aliquots.
ResultsA total of 556 samples from suspected TB patients were analyzed. The majority were lower respiratory tract specimens, including bronchoalveolar lavage fluid (BALF; 94.06%), sputum (3.24%), and extrapulmonary samples (2.70%). Compared with Xpert MTB/RIF and clinical diagnosis as composite reference standard, both mNGS and RT-PCR showed high sensitivity (92.31% and 90.38%, respectively) and perfect specificity (100%). There was a high level of agreement between mNGS and RT-PCR, with a positive agreement of 82.69%, negative agreement of 98.25%, overall agreement of 98.38%, and a kappa value of 0.896 (P < 0.001). Concordance was higher in samples with lower RT-PCR cycle threshold (Ct) values: 100% at Ct ≤ 15, 100% at 15r = -0.668, P < 0.001). Analysis of nine discordant cases identified five mNGS-positive/RT-PCR-negative samples with low SMRNs (median: 7 vs. 1788 in concordant positives), four of which were confirmed by Xpert MTB/RIF to have extremely low bacterial loads. The remaining four mNGS-negative/RT-PCR-positive samples exhibited higher Ct values (median: 22.97 vs. 17.06 in concordant positives), and three of these were also verified by Xpert MTB/RIF to contain extremely low bacterial concentrations.
ConclusionBoth RT-PCR and mNGS demonstrate high overall agreement for MTB detection, with concordance strongly influenced by microbial burden. These findings support the complementary use of these methods in the diagnosis of TB.