{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T13:23:39Z","timestamp":1788269019655,"version":"build-2803163510"},"reference-count":56,"publisher":"American Society for Microbiology","issue":"9","license":[{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.asm.org\/non-commercial-tdm-license"}],"funder":[{"name":"Research fund of Sichuan Academy of Medical Sciences and Sichuan Provincial People\u2019s Hospital","award":["2022QN21"],"award-info":[{"award-number":["2022QN21"]}]},{"name":"Research fund of Sichuan Academy of Medical Sciences and Sichuan Provincial People\u2019s Hospital","award":["2022QN51"],"award-info":[{"award-number":["2022QN51"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["81702064, 81670893, 82372339"],"award-info":[{"award-number":["81702064, 81670893, 82372339"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["journals.asm.org"],"crossmark-restriction":true},"short-container-title":["Microbiol Spectr"],"published-print":{"date-parts":[[2026,9,1]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:sec>\n                    <jats:title\/>\n                    <jats:p>\n                      Metagenomic next-generation sequencing (mNGS) is a promising tool for diagnosing challenging infections like tuberculosis (TB). However, previous studies largely focused on case-specific application of mNGS in TB diagnosis. Thus, we conducted a retrospective observational study to first systematically evaluate the diagnostic performance and cost-effectiveness of mNGS for TB diagnosis. We retrieved a total of 16,776 results of the seven TB diagnostic assays, including mNGS, tuberculosis IgG antibody, TB interferon-\u03b3 release assay (TB-IGRA), TB-DNA, Xpert MTB\/RIF (Xpert), culture, and acid-fast bacilli staining (AFS) from 3,757 participants with suspected TB infection at Sichuan Provincial People\u2019s Hospital from September 2021 to July 2024. Diagnostic metrics were compared against a composite reference standard. Microbial composition and a cost-utility analysis were performed. Among seven TB assays studied, the World Health Organization (WHO)-recommended assays AFS, culture, and Xpert, as well as TB-IGRA, were requested most frequently for TB diagnosis, whereas mNGS ranked last. mNGS demonstrated the highest specificity (100%), accuracy (72.3%), and area under the curve (AUC) (0.795). Its sensitivity in bronchoalveolar lavage fluid and tissue was 71.0% and 72.7%, respectively. Sequential use of mNGS after initial WHO-recommended tests (Xpert\/Culture\/AFS) significantly improved diagnostic performance (sensitivity, 70.4%; AUC, 0.823). Microbial analysis associated\n                      <jats:italic toggle=\"yes\">Candida albicans<\/jats:italic>\n                      with TB. Cost-utility analysis showed sequential mNGS became cost-effective at higher willingness-to-pay thresholds (&gt;200,000 RMB per correct diagnosis). mNGS offers superior specificity for TB diagnosis. A sequential strategy applying mNGS to conventional-test-negative cases provides enhanced diagnostic performance and is cost-effective at higher healthcare investment values, supporting its utility for diagnostically challenging TB.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>IMPORTANCE<\/jats:title>\n                    <jats:p>\n                      This study systematically assesses the diagnostic performance and cost utility of metagenomic next-generation sequencing (mNGS) for tuberculosis (TB) in a large real-world cohort of 3,757 suspected patients, comparing it against six conventional assays (tuberculosis IgG antibody, TB interferon-\u03b3 release assay, TB-DNA, Xpert, culture, and acid-fast bacilli staining). mNGS demonstrated the highest specificity (100%), accuracy (72.3%), and area under the curve (AUC) (0.795), with sensitivities of 71.0% in bronchoalveolar lavage fluid and 72.7% in tissue. Notably, sequential use of mNGS after the World Health Organization-recommended tests significantly improved sensitivity to 70.4% and AUC to 0.823.\n                      <jats:italic toggle=\"yes\">Candida albicans<\/jats:italic>\n                      showed significant differences among the three groups. The sequential mNGS strategy was cost-effective compared with no mNGS, and its cost-effectiveness increased with a rising willingness-to-pay threshold. Overall, these results highlight mNGS as a valuable supplementary tool for challenging TB cases, especially when conventional tests are inconclusive, and provide strong evidence for integrating it into diagnostic algorithms to optimize clinical decision-making and resource allocation.\n                    <\/jats:p>\n                  <\/jats:sec>","DOI":"10.1128\/spectrum.00970-26","type":"journal-article","created":{"date-parts":[[2026,7,29]],"date-time":"2026-07-29T13:00:19Z","timestamp":1785330019000},"update-policy":"https:\/\/doi.org\/10.1128\/asmj-crossmark-policy-page","source":"Crossref","is-referenced-by-count":0,"title":["Metagenomic next-generation sequencing for tuberculosis diagnosis: enhanced performance and cost-effectiveness"],"prefix":"10.1128","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5506-7729","authenticated-orcid":true,"given":"Xiaoli","family":"Zhou","sequence":"first","affiliation":[{"id":[{"id":"https:\/\/ror.org\/04qr3zq92","id-type":"ROR","asserted-by":"publisher"}],"name":"Department of Laboratory Medicine, Sichuan Provincial People\u2019s Hospital, School of Medicine, University of Electronic Science and Technology of China","place":["Chengdu, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Guo","family":"Wei","sequence":"additional","affiliation":[{"id":[{"id":"https:\/\/ror.org\/04qr3zq92","id-type":"ROR","asserted-by":"publisher"}],"name":"Department of Clinical Research Center, Sichuan Provincial People\u2019s Hospital, School of Medicine, University of Electronic Science and Technology of China","place":["Chengdu, 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