4.7 Article

Microbiological Diagnostic Performance of Metagenomic Next-generation Sequencing When Applied to Clinical Practic

Journal

CLINICAL INFECTIOUS DISEASES
Volume 67, Issue -, Pages S231-S240

Publisher

OXFORD UNIV PRESS INC
DOI: 10.1093/cid/ciy693

Keywords

mNGS; interpretation; sensitivity; diagnostic; infection

Funding

  1. BGI China

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Background. Metagenomic next-generation sequencing (mNGS) was suggested to potentially replace traditional microbiological methodology because of its comprehensiveness. However, clinical experience with application of the test is relatively limited. Methods. From April 2017 to December 2017, 511 specimens were collected, and their retrospective diagnoses were classified into infectious disease (347 [67.9%]), noninfectious disease (119 [23.3%]), and unknown cases (45 [8.8%]). The diagnostic performance of pathogens was compared between mNGS and culture. The effect of antibiotic exposure on detection rate was also assessed. Results. The sensitivity and specificity of mNGS for diagnosing infectious disease were 50.7% and 85.7%, respectively, and these values outperformed those of culture, especially for Mycobacterium tuberculosis (odds ratio [OR], 4 [95% confidence interval {CI}, 1.7-10.8]; P < .01), viruses (mNGS only; P < .01), anaerobes (OR, infinity [95% CI, 1.71-infinity 0]; P < .01) and fungi (OR, 4.0 [95% CI, 1.6-10.3]; P < .01). Importantly, for mNGS-positive cases where the conventional method was inconclusive, 43 (61%) cases led to diagnosis modification, and 41 (58%) cases were not covered by empirical antibiotics. For cases where viruses were identified, broad-spectrum antibiotics were commonly administered (14/27), and 10 of 27 of these cases were suspected to be inappropriate. Interestingly, the sensitivity of mNGS was superior to that of culture (52.5% vs 34.2%; P < .01) in cases with, but not without, antibiotic exposure. Conclusions. mNGS could yield a higher sensitivity for pathogen identification and is less affected by prior antibiotic exposure, thereby emerging as a promising technology for detecting infectious diseases.

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