Gates Open Research (Nov 2017)
Using biomarkers to predict TB treatment duration (Predict TB): a prospective, randomized, noninferiority, treatment shortening clinical trial [version 1; referees: 3 approved]
- Ray Y. Chen,
- Laura E. Via,
- Lori E. Dodd,
- Gerhard Walzl,
- Stephanus T. Malherbe,
- André G. Loxton,
- Rodney Dawson,
- Robert J. Wilkinson,
- Friedrich Thienemann,
- Michele Tameris,
- Mark Hatherill,
- Andreas H. Diacon,
- Xin Liu,
- Jin Xing,
- Xiaowei Jin,
- Zhenya Ma,
- Shouguo Pan,
- Guolong Zhang,
- Qian Gao,
- Qi Jiang,
- Hong Zhu,
- Lili Liang,
- Hongfei Duan,
- Taeksun Song,
- David Alland,
- Michael Tartakovsky,
- Alex Rosenthal,
- Christopher Whalen,
- Michael Duvenhage,
- Ying Cai,
- Lisa C. Goldfeder,
- Kriti Arora,
- Bronwyn Smith,
- Jill Winter,
- Clifton E. Barry III,
- Predict TB Study Group
Affiliations
- Ray Y. Chen
- Tuberculosis Research Section, Laboratory of Clinical Immunology and Microbiology, Division of Intramural Research, National Institute of Allergy and Infectious Diseases (NIAID), National Institutes of Health (NIH), Bethesda, MD, USA
- Laura E. Via
- Tuberculosis Research Section, Laboratory of Clinical Immunology and Microbiology, Division of Intramural Research, National Institute of Allergy and Infectious Diseases (NIAID), National Institutes of Health (NIH), Bethesda, MD, USA
- Lori E. Dodd
- Biostatistics Research Branch, Division of Clinical Research, National Institute of Allergy and Infectious Diseases (NIAID), National Institutes of Health (NIH), Bethesda, MD, USA
- Gerhard Walzl
- South Africa Department of Science and Technology - National Research Foundation Centre of Excellence for Biomedical Tuberculosis Research, South African Medical Research Council Centre for Tuberculosis Research, Division of Molecular Biology and Human Genetics, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa
- Stephanus T. Malherbe
- South Africa Department of Science and Technology - National Research Foundation Centre of Excellence for Biomedical Tuberculosis Research, South African Medical Research Council Centre for Tuberculosis Research, Division of Molecular Biology and Human Genetics, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa
- André G. Loxton
- South Africa Department of Science and Technology - National Research Foundation Centre of Excellence for Biomedical Tuberculosis Research, South African Medical Research Council Centre for Tuberculosis Research, Division of Molecular Biology and Human Genetics, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa
- Rodney Dawson
- Division of Pulmonology, Department of Medicine, University Of Cape Town Lung Institute, University of Cape Town (UCT), Cape Town, South Africa
- Robert J. Wilkinson
- Wellcome Centre for Infectious Diseases Research in Africa,Institute of Infectious Disease and Molecular Medicine, University of Cape Town (UCT), Cape Town, South Africa
- Friedrich Thienemann
- Wellcome Centre for Infectious Diseases Research in Africa,Institute of Infectious Disease and Molecular Medicine, University of Cape Town (UCT), Cape Town, South Africa
- Michele Tameris
- South African Tuberculosis Vaccine Initiative, University of Cape Town (UCT), Cape Town, South Africa
- Mark Hatherill
- South African Tuberculosis Vaccine Initiative, University of Cape Town (UCT), Cape Town, South Africa
- Andreas H. Diacon
- TASK Applied Science and Stellenbosch University, Cape Town, South Africa
- Xin Liu
- Henan Provincial Chest Hospital, Zhengzhou, Henan, China
- Jin Xing
- Henan Provincial Institute of Tuberculosis and Prevention, Henan Center for Disease Control, Zhengzhou, Henan, China
- Xiaowei Jin
- Xinmi City Institute of Tuberculosis Prevention and Control, Xinmi, Henan, China
- Zhenya Ma
- Kaifeng City Institute of Tuberculosis Prevention and Control, Kaifeng, Henan, China
- Shouguo Pan
- Zhongmu County Health and Epidemic Prevention Station, Zhongmu, Henan, China
- Guolong Zhang
- Henan Provincial Institute of Tuberculosis and Prevention, Henan Center for Disease Control, Zhengzhou, Henan, China
- Qian Gao
- Fudan University, Shanghai, China
- Qi Jiang
- Fudan University, Shanghai, China
- Hong Zhu
- Sino-US Tuberculosis Collaborative Research Program, Zhengzhou, Henan, China
- Lili Liang
- TASK Applied Science and Stellenbosch University, Cape Town, South Africa
- Hongfei Duan
- Beijing Chest Hospital, Beijing, China
- Taeksun Song
- Institute of Infectious Disease and Molecular Medicine, University of Cape Town (UCT), Cape Town, South Africa
- David Alland
- Division of Infectious Diseases, Department of Medicine, Rutgers New Jersey Medical School, Newark, NJ, USA
- Michael Tartakovsky
- Office of Cyber Infrastructure and Computational Biology, National Institute of Allergy and Infectious Diseases (NIAID), National Institutes of Health (NIH), Bethesda, MD, USA
- Alex Rosenthal
- Office of Cyber Infrastructure and Computational Biology, National Institute of Allergy and Infectious Diseases (NIAID), National Institutes of Health (NIH), Bethesda, MD, USA
- Christopher Whalen
- Office of Cyber Infrastructure and Computational Biology, National Institute of Allergy and Infectious Diseases (NIAID), National Institutes of Health (NIH), Bethesda, MD, USA
- Michael Duvenhage
- Office of Cyber Infrastructure and Computational Biology, National Institute of Allergy and Infectious Diseases (NIAID), National Institutes of Health (NIH), Bethesda, MD, USA
- Ying Cai
- Tuberculosis Research Section, Laboratory of Clinical Immunology and Microbiology, Division of Intramural Research, National Institute of Allergy and Infectious Diseases (NIAID), National Institutes of Health (NIH), Bethesda, MD, USA
- Lisa C. Goldfeder
- Tuberculosis Research Section, Laboratory of Clinical Immunology and Microbiology, Division of Intramural Research, National Institute of Allergy and Infectious Diseases (NIAID), National Institutes of Health (NIH), Bethesda, MD, USA
- Kriti Arora
- Tuberculosis Research Section, Laboratory of Clinical Immunology and Microbiology, Division of Intramural Research, National Institute of Allergy and Infectious Diseases (NIAID), National Institutes of Health (NIH), Bethesda, MD, USA
- Bronwyn Smith
- South Africa Department of Science and Technology - National Research Foundation Centre of Excellence for Biomedical Tuberculosis Research, South African Medical Research Council Centre for Tuberculosis Research, Division of Molecular Biology and Human Genetics, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa
- Jill Winter
- Catalysis Foundation for Health, Emeryville, CA, USA
- Clifton E. Barry III
- Tuberculosis Research Section, Laboratory of Clinical Immunology and Microbiology, Division of Intramural Research, National Institute of Allergy and Infectious Diseases (NIAID), National Institutes of Health (NIH), Bethesda, MD, USA
- Predict TB Study Group
- DOI
- https://doi.org/10.12688/gatesopenres.12750.1
- Journal volume & issue
-
Vol. 1
Abstract
Background: By the early 1980s, tuberculosis treatment was shortened from 24 to 6 months, maintaining relapse rates of 1-2%. Subsequent trials attempting shorter durations have failed, with 4-month arms consistently having relapse rates of 15-20%. One trial shortened treatment only among those without baseline cavity on chest x-ray and whose month 2 sputum culture converted to negative. The 4-month arm relapse rate decreased to 7% but was still significantly worse than the 6-month arm (1.6%, P<0.01). We hypothesize that PET/CT characteristics at baseline, PET/CT changes at one month, and markers of residual bacterial load will identify patients with tuberculosis who can be cured with 4 months (16 weeks) of standard treatment. Methods: This is a prospective, multicenter, randomized, phase 2b, noninferiority clinical trial of pulmonary tuberculosis participants. Those eligible start standard of care treatment. PET/CT scans are done at weeks 0, 4, and 16 or 24. Participants who do not meet early treatment completion criteria (baseline radiologic severity, radiologic response at one month, and GeneXpert-detectable bacilli at four months) are placed in Arm A (24 weeks of standard therapy). Those who meet the early treatment completion criteria are randomized at week 16 to continue treatment to week 24 (Arm B) or complete treatment at week 16 (Arm C). The primary endpoint compares the treatment success rate at 18 months between Arms B and C. Discussion: Multiple biomarkers have been assessed to predict TB treatment outcomes. This study uses PET/CT scans and GeneXpert (Xpert) cycle threshold to risk stratify participants. PET/CT scans are not applicable to global public health but could be used in clinical trials to stratify participants and possibly become a surrogate endpoint. If the Predict TB trial is successful, other immunological biomarkers or transcriptional signatures that correlate with treatment outcome may be identified. Trial Registration: NCT02821832
Keywords
