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

Heyckendorf, Jan; Marwitz, Sebastian; Reimann, Maja; Avsar, Korkut; DiNardo, Andrew R.; Günther, Gunar; Hoelscher, Michael; Ibraim, Elmira; Kalsdorf, Barbara; Kaufmann, Stefan H.E.; Kontsevaya, Irina; van Leth, Frank; Mandalakas, Anna M.; Maurer, Florian P.; Müller, Marius; Nitschkowski, Dörte; Olaru, Ioana D.; Popa, Cristina; Rachow, Andrea; Rolling, Thierry; Rybniker, Jan; Salzer, Helmut J.F.; Sanchez-Carballo, Patricia; Schuhmann, Maren; Schaub, Dagmar; Spinu, Victor; Suárez, Isabelle; Terhalle, Elena; Unnewehr, Markus; Weiner 3rd, January; Goldmann, Torsten; Lange, Christoph

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

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Item Type:	Article
Title:	Prediction of anti-tuberculosis treatment duration based on a 22-gene transcriptomic model
Creators Name:	Heyckendorf, Jan, Marwitz, Sebastian, Reimann, Maja, Avsar, Korkut, DiNardo, Andrew R., Günther, Gunar, Hoelscher, Michael, Ibraim, Elmira, Kalsdorf, Barbara, Kaufmann, Stefan H.E., Kontsevaya, Irina, van Leth, Frank, Mandalakas, Anna M., Maurer, Florian P., Müller, Marius, Nitschkowski, Dörte, Olaru, Ioana D., Popa, Cristina, Rachow, Andrea, Rolling, Thierry, Rybniker, Jan, Salzer, Helmut J.F., Sanchez-Carballo, Patricia, Schuhmann, Maren, Schaub, Dagmar, Spinu, Victor, Suárez, Isabelle, Terhalle, Elena, Unnewehr, Markus, Weiner 3rd, January, Goldmann, Torsten and Lange, Christoph
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.
Keywords:	Antitubercular Agents, Duration of Therapy, Multidrug-Resistant Tuberculosis, Pulmonary Tuberculosis, Transcriptome
Source:	European Respiratory Journal
ISSN:	0903-1936
Publisher:	European Respiratory Society
Volume:	58
Number:	3
Page Range:	2003492
Number of Pages:	1
Date:	September 2021
Official Publication:	https://doi.org/10.1183/13993003.03492-2020
PubMed:	View item in PubMed

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