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Using biomarkers to predict TB treatment duration (Predict TB): a prospective, randomized, noninferiority, treatment shortening clinical trial.
Chen, Ray Y; Via, Laura E; Dodd, Lori E; Walzl, Gerhard; Malherbe, Stephanus T; Loxton, André G; Dawson, Rodney; Wilkinson, Robert J; Thienemann, Friedrich; Tameris, Michele; Hatherill, Mark; Diacon, Andreas H; Liu, Xin; Xing, Jin; Jin, Xiaowei; Ma, Zhenya; Pan, Shouguo; Zhang, Guolong; Gao, Qian; Jiang, Qi; Zhu, Hong; Liang, Lili; Duan, Hongfei; Song, Taeksun; Alland, David; Tartakovsky, Michael; Rosenthal, Alex; Whalen, Christopher; Duvenhage, Michael; Cai, Ying; Goldfeder, Lisa C; Arora, Kriti; Smith, Bronwyn; Winter, Jill; Barry Iii, Clifton E.
Afiliação
  • Chen RY; 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.
  • Via LE; 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.
  • Dodd LE; Wellcome Centre for Infectious Diseases Research in Africa,Institute of Infectious Disease and Molecular Medicine, University of Cape Town (UCT), Cape Town, South Africa.
  • Walzl G; Biostatistics Research Branch, Division of Clinical Research, National Institute of Allergy and Infectious Diseases (NIAID), National Institutes of Health (NIH), Bethesda, MD, USA.
  • Malherbe ST; 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 Scienc
  • Loxton AG; 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 Scienc
  • Dawson R; 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 Scienc
  • Wilkinson RJ; Division of Pulmonology, Department of Medicine, University Of Cape Town Lung Institute, University of Cape Town (UCT), Cape Town, South Africa.
  • Thienemann F; Wellcome Centre for Infectious Diseases Research in Africa,Institute of Infectious Disease and Molecular Medicine, University of Cape Town (UCT), Cape Town, South Africa.
  • Tameris M; Francis Crick Institute, London, NW1 2AT, UK.
  • Hatherill M; Department of Medicine, Imperial College London, London, W2 1PG, UK.
  • Diacon AH; Wellcome Centre for Infectious Diseases Research in Africa,Institute of Infectious Disease and Molecular Medicine, University of Cape Town (UCT), Cape Town, South Africa.
  • Liu X; Department of Internal Medicine, University Hospital Zurich, Zurich, Switzerland.
  • Xing J; South African Tuberculosis Vaccine Initiative, University of Cape Town (UCT), Cape Town, South Africa.
  • Jin X; South African Tuberculosis Vaccine Initiative, University of Cape Town (UCT), Cape Town, South Africa.
  • Ma Z; TASK Applied Science and Stellenbosch University, Cape Town, South Africa.
  • Pan S; Henan Provincial Chest Hospital, Zhengzhou, Henan, China.
  • Zhang G; Henan Provincial Institute of Tuberculosis and Prevention, Henan Center for Disease Control, Zhengzhou, Henan, China.
  • Gao Q; Xinmi City Institute of Tuberculosis Prevention and Control, Xinmi, Henan, China.
  • Jiang Q; Kaifeng City Institute of Tuberculosis Prevention and Control, Kaifeng, Henan, China.
  • Zhu H; Zhongmu County Health and Epidemic Prevention Station, Zhongmu, Henan, China.
  • Liang L; Henan Provincial Institute of Tuberculosis and Prevention, Henan Center for Disease Control, Zhengzhou, Henan, China.
  • Duan H; Fudan University, Shanghai, China.
  • Song T; Fudan University, Shanghai, China.
  • Alland D; Sino-US Tuberculosis Collaborative Research Program, Zhengzhou, Henan, China.
  • Tartakovsky M; TASK Applied Science and Stellenbosch University, Cape Town, South Africa.
  • Rosenthal A; Beijing Chest Hospital, Beijing, China.
  • Whalen C; Institute of Infectious Disease and Molecular Medicine, University of Cape Town (UCT), Cape Town, South Africa.
  • Duvenhage M; Division of Infectious Diseases, Department of Medicine, Rutgers New Jersey Medical School, Newark, NJ, USA.
  • Cai Y; Office of Cyber Infrastructure and Computational Biology, National Institute of Allergy and Infectious Diseases (NIAID), National Institutes of Health (NIH), Bethesda, MD, USA.
  • Goldfeder LC; Office of Cyber Infrastructure and Computational Biology, National Institute of Allergy and Infectious Diseases (NIAID), National Institutes of Health (NIH), Bethesda, MD, USA.
  • Arora K; Office of Cyber Infrastructure and Computational Biology, National Institute of Allergy and Infectious Diseases (NIAID), National Institutes of Health (NIH), Bethesda, MD, USA.
  • Smith B; Office of Cyber Infrastructure and Computational Biology, National Institute of Allergy and Infectious Diseases (NIAID), National Institutes of Health (NIH), Bethesda, MD, USA.
  • Winter J; 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.
  • Barry Iii CE; 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.
Gates Open Res ; 1: 9, 2017 Nov 06.
Article em En | MEDLINE | ID: mdl-29528048
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.
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Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Clinical_trials / Prognostic_studies / Risk_factors_studies Idioma: En Ano de publicação: 2017 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Clinical_trials / Prognostic_studies / Risk_factors_studies Idioma: En Ano de publicação: 2017 Tipo de documento: Article