Prediction of anti-tuberculosis treatment duration based on a 22-gene transcriptomic model.
Journal
The European respiratory journal
ISSN: 1399-3003
Titre abrégé: Eur Respir J
Pays: England
ID NLM: 8803460
Informations de publication
Date de publication:
09 2021
09 2021
Historique:
received:
14
09
2020
accepted:
20
01
2021
pubmed:
13
2
2021
medline:
28
10
2021
entrez:
12
2
2021
Statut:
epublish
Résumé
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. 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. 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). Biomarker-guided management may substantially shorten the duration of therapy for many patients with MDR-TB.
Sections du résumé
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.
Identifiants
pubmed: 33574078
pii: 13993003.03492-2020
doi: 10.1183/13993003.03492-2020
pii:
doi:
Substances chimiques
Antitubercular Agents
0
Banques de données
ClinicalTrials.gov
['NCT02597621']
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Informations de copyright
Copyright ©The authors 2021. For reproduction rights and permissions contact permissions@ersnet.org.
Déclaration de conflit d'intérêts
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.