Abstract
Background The World Health Organization recommends standardised treatment durations for patients with tuberculosis (TB). We identified and validated a host-RNA signature as a biomarker for individualised therapy durations for patients with drug-susceptible (DS)- and multidrug-resistant (MDR)-TB.
Methods Adult patients with pulmonary TB were prospectively enrolled into five independent cohorts in Germany and Romania. Clinical and microbiological data and whole blood for RNA transcriptomic analysis were collected at pre-defined time points throughout therapy. Treatment outcomes were ascertained by TBnet criteria (6-month culture status/1-year follow-up). A whole-blood RNA therapy-end model was developed in a multistep process involving a machine-learning algorithm to identify hypothetical individual end-of-treatment time points.
Results 50 patients with DS-TB and 30 patients with MDR-TB were recruited in the German identification cohorts (DS-GIC and MDR-GIC, respectively); 28 patients with DS-TB and 32 patients with MDR-TB in the German validation cohorts (DS-GVC and MDR-GVC, respectively); and 52 patients with MDR-TB in the Romanian validation cohort (MDR-RVC). A 22-gene RNA model (TB22) that defined cure-associated end-of-therapy time points was derived from the DS- and MDR-GIC data. The TB22 model was superior to other published signatures to accurately predict clinical outcomes for patients in the DS-GVC (area under the curve 0.94, 95% CI 0.9–0.98) and suggests that cure may be achieved with shorter treatment durations for TB patients in the MDR-GIC (mean reduction 218.0 days, 34.2%; p<0.001), the MDR-GVC (mean reduction 211.0 days, 32.9%; p<0.001) and the MDR-RVC (mean reduction of 161.0 days, 23.4%; p=0.001).
Conclusion Biomarker-guided management may substantially shorten the duration of therapy for many patients with MDR-TB.
Abstract
A 22-gene RNA-based model predicts individual durations of antimicrobial therapy for patients treated for tuberculosis. Application of this model will potentially shorten treatment duration in the majority of patients with MDR-TB. https://bit.ly/36dZOq0
Footnotes
This article has supplementary material available from erj.ersjournals.com
This work is registered at ClinicalTrials.gov as NCT02597621. RNA data is publicly available on the Gene Expression Omnibus database (GSE147690, GSE147689, GSE147691).
The 22-gene model has been filed for patenting (EP20158652.6).
Conflict of interest: J. Heyckendorf reports no conflicts of interest; the Research Center Borstel has a patent EP20158652.6.
Conflict of interest: S. Marwitz has nothing to disclose.
Conflict of interest: M. Reimann has nothing to disclose.
Conflict of interest: K. Avsar has nothing to disclose.
Conflict of interest: A.R. DiNardo has nothing to disclose.
Conflict of interest: G. Günther has nothing to disclose.
Conflict of interest: M. Hoelscher has nothing to disclose.
Conflict of interest: E. Ibraim reports grants, personal fees and non-financial support from Deutsches Zentrum fur Infektionsforschung (DZIF), during the conduct of the study.
Conflict of interest: B. Kalsdorf has nothing to disclose.
Conflict of interest: S.H.E. Kaufmann has nothing to disclose.
Conflict of interest: I. Kontsevaya reports grants from German Center for Infectious Research (DZIF) and German Center for Lung Research (DZL), during the conduct of the study; grants from EU Horizon 2020 AnTBiotic (733079) and CARE (825673), outside the submitted work.
Conflict of interest: F. van Leth has nothing to disclose.
Conflict of interest: A.M. Mandalakas has nothing to disclose.
Conflict of interest: F.P. Maurer has nothing to disclose.
Conflict of interest: M. Müller has nothing to disclose.
Conflict of interest: D. Nitschkowski has nothing to disclose.
Conflict of interest: I.D. Olaru has nothing to disclose.
Conflict of interest: C. Popa has nothing to disclose.
Conflict of interest: A. Rachow has nothing to disclose.
Conflict of interest: T. Rolling has nothing to disclose.
Conflict of interest: J. Rybniker has nothing to disclose.
Conflict of interest: H.J.F. Salzer has nothing to disclose.
Conflict of interest: P. Sanchez-Carballo has nothing to disclose.
Conflict of interest: M. Schuhmann has nothing to disclose.
Conflict of interest: D. Schaub has nothing to disclose.
Conflict of interest: V. Spinu reports grants, personal fees and non-financial support from Deutsches Zentrum fur Infektionsforschung (DZIF), during the conduct of the study.
Conflict of interest: I. Suárez has nothing to disclose.
Conflict of interest: E. Terhalle has nothing to disclose.
Conflict of interest: M. Unnewehr has nothing to disclose.
Conflict of interest: J. Weiner 3rd has nothing to disclose.
Conflict of interest: T. Goldmann has a patent pending.
Conflict of interest: C. Lange reports personal fees for lectures from Chiesi, Gilead, Janssen, Lucane, Novartis, Oxoid, Berlin Chemie and Thermofisher, and personal fees for meeting attendance from Oxford Immunotec, outside the submitted work.
Support statement: This study was supported by the German Center for Infection Research (DZIF) and the German Center for Lung Research (DZL). F.P. Maurer reports grant support from Joachim Herz Foundation (Biomedical Physics of Infection Consortium). The funders had no influence on the study results. Funding information for this article has been deposited with the Crossref Funder Registry.
- Received September 14, 2020.
- Accepted January 20, 2021.
- Copyright ©The authors 2021. For reproduction rights and permissions contact permissions{at}ersnet.org