Prediction of anti-tuberculosis treatment duration based on a 22-gene transcriptomic model

  • Jan Heyckendorf (Shared first author)
  • Sebastian Marwitz (Shared first author)
  • Maja Reimann (Shared first author)
  • Korkut Avsar
  • Andrew DiNardo
  • Gunar Günther
  • Michael Hoelscher
  • Elmira Ibraim
  • Barbara Kalsdorf
  • Stefan H E Kaufmann
  • Irina Kontsevaya
  • Frank van Leth
  • Anna Maria Mandalakas
  • Florian P Maurer
  • Marius Müller
  • Dörte Nitschkowski
  • Ioana D Olaru
  • Cristina Popa
  • Andrea Rachow
  • Thierry Rolling
  • Jan Rybniker
  • Helmut J F Salzer
  • Patricia Sanchez-Carballo
  • Maren Schuhmann
  • Dagmar Schaub
  • Victor Spinu
  • Isabelle Suárez
  • Elena Terhalle
  • Markus Unnewehr
  • January Weiner
  • Torsten Goldmann (Shared last author)
  • Christoph Lange (Shared last author)

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.

Bibliographical data

Original languageEnglish
ISSN0903-1936
DOIs
Publication statusPublished - 09.2021
PubMed 33574078