1. Prediction of anti-tuberculosis treatment duration based on a 22-gene transcriptomic model
- Author
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Sebastian Marwitz, January Weiner, Thierry Rolling, Victor Spinu, Dörte Nitschkowski, Florian P. Maurer, Marius Müller, Jan Heyckendorf, Anna M. Mandalakas, Jan Rybniker, Torsten Goldmann, Maja Reimann, Michael Hoelscher, Markus Unnewehr, Korkut Avsar, Helmut J. F. Salzer, Elmira Ibraim, Ioana D. Olaru, Andrea Rachow, Gunar Günther, Frank van Leth, Maren Schuhmann, Dagmar Schaub, Christoph Lange, Barbara Kalsdorf, Cristina Popa, Elena Terhalle, Patricia Sanchez-Carballo, Irina Kontsevaya, Isabelle Suárez, Stefan H. E. Kaufmann, Andrew R. DiNardo, Global Health, AII - Infectious diseases, APH - Global Health, APH - Methodology, and Health Economics and Health Technology Assessment
- Subjects
Adult ,Pulmonary and Respiratory Medicine ,medicine.medical_specialty ,Tuberculosis ,Antitubercular Agents/therapeutic use ,Treatment duration ,Antitubercular Agents ,MEDLINE ,Multidrug-Resistant/drug therapy ,610 Medicine & health ,Transcriptome ,Anti tuberculosis ,Internal medicine ,Tuberculosis, Multidrug-Resistant ,medicine ,Humans ,Tuberculosis, Pulmonary ,Gene ,Duration of Therapy ,business.industry ,Area under the curve ,medicine.disease ,Tuberculosis, Pulmonary/drug therapy ,Biomarker (medicine) ,Tuberculosis, Multidrug-Resistant/drug therapy ,business ,Pulmonary/drug therapy - Abstract
BackgroundThe 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.MethodsAdult 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.Results50 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%; pConclusionBiomarker-guided management may substantially shorten the duration of therapy for many patients with MDR-TB.
- Published
- 2021
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