RT Journal Article
SR Electronic
T1 Prediction of anti-tuberculosis treatment duration based on a 22-gene transcriptomic model
JF European Respiratory Journal
JO Eur Respir J
FD European Respiratory Society
SP 2003492
DO 10.1183/13993003.03492-2020
VO 58
IS 3
A1 Heyckendorf, Jan
A1 Marwitz, Sebastian
A1 Reimann, Maja
A1 Avsar, Korkut
A1 DiNardo, Andrew R.
A1 Günther, Gunar
A1 Hoelscher, Michael
A1 Ibraim, Elmira
A1 Kalsdorf, Barbara
A1 Kaufmann, Stefan H.E.
A1 Kontsevaya, Irina
A1 van Leth, Frank
A1 Mandalakas, Anna M.
A1 Maurer, Florian P.
A1 Müller, Marius
A1 Nitschkowski, Dörte
A1 Olaru, Ioana D.
A1 Popa, Cristina
A1 Rachow, Andrea
A1 Rolling, Thierry
A1 Rybniker, Jan
A1 Salzer, Helmut J.F.
A1 Sanchez-Carballo, Patricia
A1 Schuhmann, Maren
A1 Schaub, Dagmar
A1 Spinu, Victor
A1 Suárez, Isabelle
A1 Terhalle, Elena
A1 Unnewehr, Markus
A1 Weiner, January
A1 Goldmann, Torsten
A1 Lange, Christoph
YR 2021
UL http://erj.ersjournals.com/content/58/3/2003492.abstract
AB 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.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