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Mycobactericidal Effects of Different Regimens Measured by Molecular Bacterial Load Assay Among People Treated for Multidrug-Resistant Tuberculosis in Tanzania

Abstract

Rifampin or multidrug-resistant tuberculosis (RR/MDR-TB) treatment has largely transitioned to regimens free of the injectable aminoglycoside component, despite the drug class' purported bactericidal activity early in treatment. We tested whether killing rates measured by tuberculosis molecular bacterial load assay (TB-MBLA) in sputa correlate with composition of the RR/MDR-TB regimen. Serial sputa were collected from patients with RR/MDR- and drug-sensitive TB at days 0, 3, 7, and 14, and then monthly for 4 months of anti-TB treatment. TB-MBLA was used to quantify viable 16S rRNA in sputum for estimation of colony forming units per ml (eCFU/ml). killing rates were compared among regimens using nonlinear-mixed-effects modeling of repeated measures. Thirty-seven patients produced 296 serial sputa and received treatment as follows: 13 patients received an injectable bedaquiline-free reference regimen, 9 received an injectable bedaquiline-containing regimen, 8 received an all-oral bedaquiline-based regimen, and 7 patients were treated for drug-sensitive TB with conventional rifampin/isoniazid/pyrazinamide/ethambutol (RHZE). Compared to the adjusted killing of -0.17 (95% confidence interval [CI] -0.23 to -0.12) for the injectable bedaquiline-free reference regimen, the killing rates were -0.62 (95% CI -1.05 to -0.20) log eCFU/ml for the injectable bedaquiline-containing regimen ( = 0.019), -0.35 (95% CI -0.65 to -0.13) log eCFU/ml for the all-oral bedaquiline-based regimen ( = 0.054), and -0.29 (95% CI -0.78 to +0.22) log eCFU/ml for the RHZE regimen ( = 0.332). Thus, killing rates from sputa were higher among patients who received bedaquiline but were further improved with the addition of an injectable aminoglycoside.

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References
1.
Nicol M . Xpert MTB/RIF: monitoring response to tuberculosis treatment. Lancet Respir Med. 2014; 1(6):427-8. DOI: 10.1016/S2213-2600(13)70133-4. View

2.
Diriba G, Kebede A, Yaregal Z, Getahun M, Tadesse M, Meaza A . Performance of Mycobacterium Growth Indicator Tube BACTEC 960 with Lowenstein-Jensen method for diagnosis of Mycobacterium tuberculosis at Ethiopian National Tuberculosis Reference Laboratory, Addis Ababa, Ethiopia. BMC Res Notes. 2017; 10(1):181. PMC: 5424417. DOI: 10.1186/s13104-017-2497-9. View

3.
van Zyl-Smit R, Binder A, Meldau R, Mishra H, Semple P, Theron G . Comparison of quantitative techniques including Xpert MTB/RIF to evaluate mycobacterial burden. PLoS One. 2012; 6(12):e28815. PMC: 3245241. DOI: 10.1371/journal.pone.0028815. View

4.
Doan T, Cao P, Emeto T, McCaw J, McBryde E . Predicting the Outcomes of New Short-Course Regimens for Multidrug-Resistant Tuberculosis Using Intrahost and Pharmacokinetic-Pharmacodynamic Modeling. Antimicrob Agents Chemother. 2018; 62(12). PMC: 6256788. DOI: 10.1128/AAC.01487-18. View

5.
Li R, Tun H, Jahan M, Zhang Z, Kumar A, Fernando W . Comparison of DNA-, PMA-, and RNA-based 16S rRNA Illumina sequencing for detection of live bacteria in water. Sci Rep. 2017; 7(1):5752. PMC: 5515937. DOI: 10.1038/s41598-017-02516-3. View