TY - JOUR T1 - Prediction of anti-tuberculosis treatment duration based on a 22-gene transcriptomic model JF - European Respiratory Journal JO - Eur Respir J DO - 10.1183/13993003.03492-2020 VL - 58 IS - 3 SP - 2003492 AU - Jan Heyckendorf AU - Sebastian Marwitz AU - Maja Reimann AU - Korkut Avsar AU - Andrew R. DiNardo AU - Gunar Günther AU - Michael Hoelscher AU - Elmira Ibraim AU - Barbara Kalsdorf AU - Stefan H.E. Kaufmann AU - Irina Kontsevaya AU - Frank van Leth AU - Anna M. Mandalakas AU - Florian P. Maurer AU - Marius Müller AU - Dörte Nitschkowski AU - Ioana D. Olaru AU - Cristina Popa AU - Andrea Rachow AU - Thierry Rolling AU - Jan Rybniker AU - Helmut J.F. Salzer AU - Patricia Sanchez-Carballo AU - Maren Schuhmann AU - Dagmar Schaub AU - Victor Spinu AU - Isabelle Suárez AU - Elena Terhalle AU - Markus Unnewehr AU - January Weiner, 3rd AU - Torsten Goldmann AU - Christoph Lange Y1 - 2021/09/01 UR - http://erj.ersjournals.com/content/58/3/2003492.abstract N2 - 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 ER -