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Olbrich L, Verghese VP, Franckling-Smith Z, Sabi I, Ntinginya NE, Mfinanga A, Banze D, Viegas S, Khosa C, Semphere R, Nliwasa M, McHugh TD, Larsson L, Razid A, Song R, Corbett EL, Nabeta P, Trollip A, Graham SM, Hoelscher M, Geldmacher C, Zar HJ, Michael JS, Heinrich N. Diagnostic accuracy of a three-gene Mycobacterium tuberculosis host response cartridge using fingerstick blood for childhood tuberculosis: a multicentre prospective study in low-income and middle-income countries. THE LANCET. INFECTIOUS DISEASES 2024; 24:140-149. [PMID: 37918414 PMCID: PMC10808504 DOI: 10.1016/s1473-3099(23)00491-7] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/08/2023] [Revised: 07/22/2023] [Accepted: 07/25/2023] [Indexed: 11/04/2023]
Abstract
BACKGROUND Childhood tuberculosis remains a major cause of morbidity and mortality in part due to missed diagnosis. Diagnostic methods with enhanced sensitivity using easy-to-obtain specimens are needed. We aimed to assess the diagnostic accuracy of the Cepheid Mycobacterium tuberculosis Host Response prototype cartridge (MTB-HR), a candidate test measuring a three-gene transcriptomic signature from fingerstick blood, in children with presumptive tuberculosis disease. METHODS RaPaed-TB was a prospective diagnostic accuracy study conducted at four sites in African countries (Malawi, Mozambique, South Africa, and Tanzania) and one site in India. Children younger than 15 years with presumptive pulmonary or extrapulmonary tuberculosis were enrolled between Jan 21, 2019, and June 30, 2021. MTB-HR was performed at baseline and at 1 month in all children and was repeated at 3 months and 6 months in children on tuberculosis treatment. Accuracy was compared with tuberculosis status based on standardised microbiological, radiological, and clinical data. FINDINGS 5313 potentially eligible children were screened, of whom 975 were eligible. 784 children had MTB-HR test results, of whom 639 had a diagnostic classification and were included in the analysis. MTB-HR differentiated children with culture-confirmed tuberculosis from those with unlikely tuberculosis with a sensitivity of 59·8% (95% CI 50·8-68·4). Using any microbiological confirmation (culture, Xpert MTB/RIF Ultra, or both), sensitivity was 41·6% (34·7-48·7), and using a composite clinical reference standard, sensitivity was 29·6% (25·4-34·2). Specificity for all three reference standards was 90·3% (95% CI 85·5-94·0). Performance was similar in different age groups and by malnutrition status. Among children living with HIV, accuracy against the strict reference standard tended to be lower (sensitivity 50·0%, 15·7-84·3) compared with those without HIV (61·0%, 51·6-69·9), although the difference did not reach statistical significance. Combining baseline MTB-HR result with one Ultra result identified 71·2% of children with microbiologically confirmed tuberculosis. INTERPRETATION MTB-HR showed promising diagnostic accuracy for culture-confirmed tuberculosis in this large, geographically diverse, paediatric cohort and hard-to-diagnose subgroups. FUNDING European and Developing Countries Clinical Trials Partnership, UK Medical Research Council, Swedish International Development Cooperation Agency, Bundesministerium für Bildung und Forschung; German Center for Infection Research (DZIF).
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Affiliation(s)
- Laura Olbrich
- Division of Infectious Diseases and Tropical Medicine, LMU University Hospital, LMU Munich, Munich, Germany; German Centre for Infection Research (DZIF), Partner Site Munich, Munich, Germany; Fraunhofer Institute ITMP, Immunology, Infection and Pandemic Research, Munich, Germany; Oxford Vaccine Group, Department of Paediatrics and the NIHR Oxford Biomedical Research Centre, University of Oxford, Oxford, UK
| | - Valsan P Verghese
- Pediatric Infectious Diseases, Department of Pediatrics, Christian Medical College, Vellore, India
| | - Zoe Franckling-Smith
- Department of Paediatrics and Child Health, SA-MRC Unit on Child and Adolescent Health, University of Cape Town, Cape Town, South Africa
| | - Issa Sabi
- Mbeya Medical Research Centre, National Institute for Medical Research, Mbeya, Tanzania
| | - Nyanda E Ntinginya
- Mbeya Medical Research Centre, National Institute for Medical Research, Mbeya, Tanzania
| | - Alfred Mfinanga
- Mbeya Medical Research Centre, National Institute for Medical Research, Mbeya, Tanzania
| | - Denise Banze
- Instituto Nacional de Saúde, Marracuene, Mozambique
| | - Sofia Viegas
- Instituto Nacional de Saúde, Marracuene, Mozambique
| | - Celso Khosa
- Instituto Nacional de Saúde, Marracuene, Mozambique
| | - Robina Semphere
- Helse Nord Tuberculosis Initiative, Department of Pathology, Kamuzu University of Health Sciences, Blantyre, Malawi
| | - Marriott Nliwasa
- Helse Nord Tuberculosis Initiative, Department of Pathology, Kamuzu University of Health Sciences, Blantyre, Malawi
| | - Timothy D McHugh
- Centre for Clinical Microbiology, University College London, London, UK
| | - Leyla Larsson
- Division of Infectious Diseases and Tropical Medicine, LMU University Hospital, LMU Munich, Munich, Germany; German Centre for Infection Research (DZIF), Partner Site Munich, Munich, Germany
| | - Alia Razid
- Division of Infectious Diseases and Tropical Medicine, LMU University Hospital, LMU Munich, Munich, Germany; German Centre for Infection Research (DZIF), Partner Site Munich, Munich, Germany
| | - Rinn Song
- Oxford Vaccine Group, Department of Paediatrics and the NIHR Oxford Biomedical Research Centre, University of Oxford, Oxford, UK
| | - Elizabeth L Corbett
- Helse Nord Tuberculosis Initiative, Department of Pathology, Kamuzu University of Health Sciences, Blantyre, Malawi; Clinical Research Department, London School of Hygiene & Tropical Medicine, London, UK
| | - Pamela Nabeta
- Foundation for Innovative New Diagnostics (FIND), Geneva, Switzerland
| | - Andre Trollip
- Foundation for Innovative New Diagnostics (FIND), Geneva, Switzerland
| | - Stephen M Graham
- Department of Paediatrics, University of Melbourne and Murdoch Children's Research Institute, Melbourne, VIC, Australia
| | - Michael Hoelscher
- Division of Infectious Diseases and Tropical Medicine, LMU University Hospital, LMU Munich, Munich, Germany; CIHLMU Center for International Health, LMU University Hospital, LMU Munich, Munich, Germany; German Centre for Infection Research (DZIF), Partner Site Munich, Munich, Germany; Fraunhofer Institute ITMP, Immunology, Infection and Pandemic Research, Munich, Germany; Unit Global Health, Helmholtz Zentrum München, German Research Center for Environmental Health (HMGU), Neuherberg, Germany
| | - Christof Geldmacher
- Division of Infectious Diseases and Tropical Medicine, LMU University Hospital, LMU Munich, Munich, Germany; German Centre for Infection Research (DZIF), Partner Site Munich, Munich, Germany; Fraunhofer Institute ITMP, Immunology, Infection and Pandemic Research, Munich, Germany
| | - Heather J Zar
- Department of Paediatrics and Child Health, SA-MRC Unit on Child and Adolescent Health, University of Cape Town, Cape Town, South Africa
| | | | - Norbert Heinrich
- Division of Infectious Diseases and Tropical Medicine, LMU University Hospital, LMU Munich, Munich, Germany; CIHLMU Center for International Health, LMU University Hospital, LMU Munich, Munich, Germany; German Centre for Infection Research (DZIF), Partner Site Munich, Munich, Germany; Fraunhofer Institute ITMP, Immunology, Infection and Pandemic Research, Munich, Germany.
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Faust L, Zimmer AJ, Kohli M, Saha S, Boffa J, Bayot ML, Nsofor I, Campos L, Mashamba-Thompson T, Herrera R, Emeka E, Shrestha S, Ugarte-Gil C, Katamba A, Pambudi I, Bichara D, Calderon RI, Ahmadzada N, Safdar MA, Nikam C, Dos Santos Lázari C, Hussain H, Win MM, Than KZ, Ahumibe A, Waning B, Pai M. SARS-CoV-2 testing in low- and middle-income countries: availability and affordability in the private health sector. Microbes Infect 2020; 22:511-514. [PMID: 33065265 PMCID: PMC7553871 DOI: 10.1016/j.micinf.2020.10.005] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2020] [Revised: 10/05/2020] [Accepted: 10/07/2020] [Indexed: 11/22/2022]
Affiliation(s)
- Lena Faust
- McGill International TB Centre, Montreal, Canada; Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal, Canada
| | - Alexandra J Zimmer
- McGill International TB Centre, Montreal, Canada; Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal, Canada
| | - Mikashmi Kohli
- McGill International TB Centre, Montreal, Canada; Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal, Canada
| | - Senjuti Saha
- Child Health Research Foundation, Dhaka, Bangladesh
| | - Jody Boffa
- Dahdaleh Institute for Global Health, York University, Canada; Centre for Rural Health, University of KwaZulu-Natal, South Africa
| | | | | | | | | | - Rosa Herrera
- Instituto de Servicios de Salud Pública del Estado de Baja California, Mexico
| | - Elom Emeka
- TB Laboratory Services Unit, NTBLCP, Federal Ministry of Health, Dept of Public Health, Federal Capital Territory, Abuja, Nigeria
| | | | - Cesar Ugarte-Gil
- Instituto de Medicina Tropical Alexander von Humboldt, Universidad Peruana Cayetano Heredia, Lima, Peru; School of Medicine, Universidad Peruana Cayetano Heredia, Lima, Peru
| | - Achilles Katamba
- Clinical Epidemiology & Biostatistics Unit, Department of Medicine School of Medicine, Makerere University College of Health Sciences, Uganda; Uganda Tuberculosis Implementation Research Consortium, Kampala, Uganda
| | | | - David Bichara
- Scientific Department of Amaral Costa Laboratory, Belém, PA, Brazil
| | - Roger I Calderon
- Socios En Salud Sucursal Peru, Lima, Peru; Programa Acadêmico de Tuberculose, Faculdade de Medicina, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brazil
| | | | | | | | - Carolina Dos Santos Lázari
- Infectious Disease Medical Department, Grupo Fleury, Brazil; Molecular Biology Section, Central Laboratory Division, University of São Paulo Clinical Hospital, Brazil
| | | | | | | | | | | | - Madhukar Pai
- McGill International TB Centre, Montreal, Canada; Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal, Canada.
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Computer aided detection of tuberculosis on chest radiographs: An evaluation of the CAD4TB v6 system. Sci Rep 2020; 10:5492. [PMID: 32218458 PMCID: PMC7099074 DOI: 10.1038/s41598-020-62148-y] [Citation(s) in RCA: 59] [Impact Index Per Article: 14.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2019] [Accepted: 03/06/2020] [Indexed: 11/11/2022] Open
Abstract
There is a growing interest in the automated analysis of chest X-Ray (CXR) as a sensitive and inexpensive means of screening susceptible populations for pulmonary tuberculosis. In this work we evaluate the latest version of CAD4TB, a commercial software platform designed for this purpose. Version 6 of CAD4TB was released in 2018 and is here tested on a fully independent dataset of 5565 CXR images with GeneXpert (Xpert) sputum test results available (854 Xpert positive subjects). A subset of 500 subjects (50% Xpert positive) was reviewed and annotated by 5 expert observers independently to obtain a radiological reference standard. The latest version of CAD4TB is found to outperform all previous versions in terms of area under receiver operating curve (ROC) with respect to both Xpert and radiological reference standards. Improvements with respect to Xpert are most apparent at high sensitivity levels with a specificity of 76% obtained at a fixed 90% sensitivity. When compared with the radiological reference standard, CAD4TB v6 also outperformed previous versions by a considerable margin and achieved 98% specificity at the 90% sensitivity setting. No substantial difference was found between the performance of CAD4TB v6 and any of the various expert observers against the Xpert reference standard. A cost and efficiency analysis on this dataset demonstrates that in a standard clinical situation, operating at 90% sensitivity, users of CAD4TB v6 can process 132 subjects per day at an average cost per screen of $5.95 per subject, while users of version 3 process only 85 subjects per day at a cost of $8.38 per subject. At all tested operating points version 6 is shown to be more efficient and cost effective than any other version.
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Ma J, Song Y, Tian X, Hua Y, Zhang R, Wu J. Survey on deep learning for pulmonary medical imaging. Front Med 2019; 14:450-469. [PMID: 31840200 DOI: 10.1007/s11684-019-0726-4] [Citation(s) in RCA: 34] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2019] [Accepted: 10/12/2019] [Indexed: 12/27/2022]
Abstract
As a promising method in artificial intelligence, deep learning has been proven successful in several domains ranging from acoustics and images to natural language processing. With medical imaging becoming an important part of disease screening and diagnosis, deep learning-based approaches have emerged as powerful techniques in medical image areas. In this process, feature representations are learned directly and automatically from data, leading to remarkable breakthroughs in the medical field. Deep learning has been widely applied in medical imaging for improved image analysis. This paper reviews the major deep learning techniques in this time of rapid evolution and summarizes some of its key contributions and state-of-the-art outcomes. The topics include classification, detection, and segmentation tasks on medical image analysis with respect to pulmonary medical images, datasets, and benchmarks. A comprehensive overview of these methods implemented on various lung diseases consisting of pulmonary nodule diseases, pulmonary embolism, pneumonia, and interstitial lung disease is also provided. Lastly, the application of deep learning techniques to the medical image and an analysis of their future challenges and potential directions are discussed.
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Affiliation(s)
| | - Yang Song
- Dalian Municipal Central Hospital Affiliated to Dalian Medical University, Dalian, 116033, China
| | - Xi Tian
- InferVision, Beijing, 100020, China
| | | | | | - Jianlin Wu
- Affiliated Zhongshan Hospital of Dalian University, Dalian, 116001, China.
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Cazabon D, Pande T, Kik S, Van Gemert W, Sohn H, Denkinger C, Qin ZZ, Waning B, Pai M. Market penetration of Xpert MTB/RIF in high tuberculosis burden countries: A trend analysis from 2014 - 2016. Gates Open Res 2018; 2:35. [PMID: 30234198 PMCID: PMC6139378 DOI: 10.12688/gatesopenres.12842.2] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 09/14/2018] [Indexed: 11/20/2022] Open
Abstract
Background: Xpert® MTB/RIF, a rapid tuberculosis (TB) molecular test, was endorsed by the World Health Organization in 2010. Since then, 34.4 million cartridges have been procured under concessional pricing. Although the roll out of this diagnostic is promising, previous studies showed low market penetration. Methods: To assess 3-year trends of market penetration of Xpert MTB/RIF in the public sector, smear and Xpert MTB/RIF volumes for the year 2016 were evaluated and policies from 2014-2016 within 22 high-burden countries (HBCs) were studied. A structured questionnaire was sent to representatives of 22 HBCs. The questionnaires assessed the total smear and Xpert MTB/RIF volumes, number of modules and days of operation of GeneXpert machines in National TB Programs (NTPs). Data regarding the use of NTP GeneXpert machines for other diseases and GeneXpert procurement by other disease control programs were collected. Market penetration was estimated by the ratio of total sputum smear volume for initial diagnosis divided by the number of Xpert MTB/RIF tests procured in the public sector. Results: The survey response rate was 21/22 (95%). Smear/Xpert ratios decreased in 17/21 countries and increased in four countries, since 2014. The median ratio decreased from 32.6 (IQR: 44.6) in 2014 to 6.0 (IQR: 15.4) in 2016. In 2016, the median GeneXpert utilization was 20%, however seven countries (7/19; 37%) were running tests for other diseases on their NTP-procured GeneXpert systems in 2017, such as HIV, hepatitis-C virus (HCV),
Chlamydia trachomatis, and
Neisseria gonorrhoeae. Five (5/15; 33%) countries reported GeneXpert procurement by HIV or HCV programs in 2016 and/or 2017. Conclusions: Our results show a positive trend for Xpert MTB/RIF market penetration in 21 HBC public sectors. However, GeneXpert machines were under-utilized for TB, and inadequately exploited as a multi disease technology.
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Affiliation(s)
- Danielle Cazabon
- McGill International TB Centre, McGill University, Montreal, QC, Canada
| | - Tripti Pande
- McGill International TB Centre, McGill University, Montreal, QC, Canada
| | - Sandra Kik
- Foundation for Innovative New Diagnostics, FIND, Geneva, Switzerland
| | | | - Hojoon Sohn
- Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA
| | - Claudia Denkinger
- Foundation for Innovative New Diagnostics, FIND, Geneva, Switzerland
| | | | | | - Madhukar Pai
- McGill International TB Centre, McGill University, Montreal, QC, Canada.,Epidemiology & Biostatistics, McGill University, Montreal, QC, Canada
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6
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Cazabon D, Pande T, Kik S, Van Gemert W, Sohn H, Denkinger C, Qin ZZ, Waning B, Pai M. Market penetration of Xpert MTB/RIF in high tuberculosis burden countries: A trend analysis from 2014 - 2016. Gates Open Res 2018; 2:35. [PMID: 30234198 DOI: 10.12688/gatesopenres.12842.1] [Citation(s) in RCA: 33] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/19/2018] [Indexed: 01/18/2023] Open
Abstract
Background: Xpert® MTB/RIF, a rapid tuberculosis (TB) molecular test, was endorsed by the World Health Organization in 2010. Since then, 34.4 million cartridges have been procured under concessional pricing. Although the roll out of this diagnostic is promising, previous studies showed low market penetration. Methods: To assess 3-year trends of market penetration of Xpert MTB/RIF in the public sector, smear and Xpert MTB/RIF volumes for the year 2016 were evaluated and policies from 2014-2016 within 22 high-burden countries (HBCs) were studied. A structured questionnaire was sent to representatives of 22 HBCs. The questionnaires assessed the total smear and Xpert MTB/RIF volumes, number of modules and days of operation of GeneXpert machines in National TB Programs (NTPs). Data regarding the use of NTP GeneXpert machines for other diseases and GeneXpert procurement by other disease control programs were collected. Market penetration was estimated by the ratio of total sputum smear volume for initial diagnosis divided by the number of Xpert MTB/RIF tests procured in the public sector. Results: The survey response rate was 21/22 (95%). Smear/Xpert ratios decreased in 17/21 countries and increased in four countries, since 2014. The median ratio decreased from 32.6 (IQR: 44.6) in 2014 to 6.0 (IQR: 15.4) in 2016. In 2016, the median GeneXpert utilization was 20%, however seven countries (7/19; 37%) were running tests for other diseases on their NTP-procured GeneXpert systems in 2017, such as HIV, hepatitis-C virus (HCV), Chlamydia trachomatis, and Neisseria gonorrhoeae. Five (5/15; 33%) countries reported GeneXpert procurement by HIV or HCV programs in 2016 and/or 2017. Conclusions: Our results show a positive trend for Xpert MTB/RIF market penetration in 21 HBC public sectors. However, GeneXpert machines were under-utilized for TB, and inadequately exploited as a multi disease technology.
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Affiliation(s)
- Danielle Cazabon
- McGill International TB Centre, McGill University, Montreal, QC, Canada
| | - Tripti Pande
- McGill International TB Centre, McGill University, Montreal, QC, Canada
| | - Sandra Kik
- Foundation for Innovative New Diagnostics, FIND, Geneva, Switzerland
| | | | - Hojoon Sohn
- Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA
| | - Claudia Denkinger
- Foundation for Innovative New Diagnostics, FIND, Geneva, Switzerland
| | | | | | - Madhukar Pai
- McGill International TB Centre, McGill University, Montreal, QC, Canada.,Epidemiology & Biostatistics, McGill University, Montreal, QC, Canada
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