ArticleThe Lancet regional health. Southeast Asia2026
Targeted next-generation sequencing for direct drug-resistant tuberculosis detection in sputum samples in Indonesia: an implementation study (2024-25).
Article in The Lancet regional health. Southeast Asia, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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14 authors.
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Abstract
Background: The availability of targeted Next Generation Sequencing (tNGS) for drug-resistant tuberculosis (DRTB) is a major advance in TB diagnostics, but its optimal implementation, yield, and cost in high TB-incidence settings remain unclear. We aimed to evaluate tNGS in relation to laboratory workflow, implementation cascade, turnaround time, and unit cost. Methods: We prospectively evaluated tNGS implementation with Deeplex Myc-TB for sputum samples at the provincial reference laboratory in West Java, Indonesia, from 1 August 2024 to 10 October 2025. We included patients with Xpert-diagnosed rifampicin-resistant TB (RRTB) at 32 hospitals and 15 community health centres, collectively catering to 51.0% of RRTB patients in the province. Findings: From 1210 RRTB sputum samples collected, 812 (67.1%) samples completed sequencing, with 429/812 (52.8%) yielding complete and 164/812 (20.2%) partial reads. Success of tNGS depended on bacterial load, ranging from 88.8% for Xpert high to 0% for very low samples. Majority samples were confirmed as RR/MDR TB (89.2%), with pre-XDR and XDR TB recorded in 10.6% and 0.2%, respectively. Workflow optimisation improved sequencing performance, with final workflow reaching a laboratory success of 82.4% (201/244). The median turnaround time for tNGS from sample reception until sequencing results was eight days (IQR 6-10). The total tNGS unit cost per sample was $263.6 for iSeq and $239.6 for MiSeq. Interpretation: tNGS performed well in those with high DNA sputum load with relatively rapid turnaround time. Its optimisation for wide adoption should consider DRTB burden, sample selection, sequencing platform, and costs. Funding: Gates Foundation and FIND.
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