B Lange1, P Khan2, G Kalmambetova3, H A Al-Darraji4, D Alland5, U Antonenka6, T Brown7, M E Balcells8, R Blakemore9, C M Denkinger10, K Dheda7, H Hoffmann6, A Kadyrov3, N Lemaitre11, M B Miller12, V Nikolayevskyy13, E N Ntinginya14, N Ozkutuk15, J J Palacios16, E B Popowitch12, J M Porcel17, J Teo18, G Theron18, K Kranzer19. 1. Centre for Chronic Immunodeficiency, Division of Infectious Diseases, Department of Internal Medicine II, Faculty of Medicine, Medical Center-University of Freiburg, Freiburg, Germany. 2. London School of Hygiene & Tropical Medicine, London, UK. 3. National TB Reference Laboratory, National Centre of Phthisiology, Bishkek, Kyrgyzstan. 4. Centre of Excellence for Research in AIDS, Faculty of Medicine, University of Malaya, Kuala Lumpur, Malaysia, Centre for International Health, Department of Preventive and Social Medicine, University of Otago, Dunedin, New Zealand. 5. Division of Infectious Disease, Department of Medicine, Rutgers New Jersey Medical School, Newark, New Jersey, USA. 6. Synlab MVZ Gauting, Institute of Microbiology and Laboratory Medicine, World Health Organization Supranational Reference Laboratory of Tuberculosis, Gauting, Germany. 7. Lung Infection and Immunity Unit, Division of Pulmonology, Department of Medicine, University of Cape Town, Cape Town, South Africa. 8. Department of Infectious Diseases, School of Medicine, Pontificia Universidad Católica de Chile, Santiago, Chile. 9. Centre for International Health, Department of Preventive and Social Medicine, University of Otago, Dunedin, New Zealand. 10. Foundation for Innovative New Diagnostics, Geneva, Switzerland. 11. Laboratoire de Bactériologie-Hygiène, Centre Hospitalier Universitaire, Université de Lille-Nord de France, Unité Mixte de Recherche 8204, F-59021, Institut National de la Santé et de la Recherche Médicale U1019, Lille, France. 12. Department of Pathology and Laboratory Medicine, University of North Carolina School of Medicine, Chapel Hill, North Carolina, USA. 13. Synlab MVZ Gauting, Institute of Microbiology and Laboratory Medicine, World Health Organization Supranational Reference Laboratory of Tuberculosis, Gauting, Germany, Department of Medicine, Imperial College London, UK. 14. Mbeya Medical Research Centre, National Institute for Medical Research, Dar es Salaam, Tanzania. 15. Celal Bayar University Faculty of Medicine, Department of Medical Microbiology, Manisa, Turkey. 16. Regional Mycobacteria Reference Center, Hospital Universitario Central de Asturias, Oviedo. 17. Pleural Medicine Unit, Department of Internal Medicine, Arnau de Vilanova University Hospital, Biomedical Research Institute of Lleida, Lleida, Spain. 18. Microbiology Unit, Department of Laboratory Medicine, National University Hospital, Singapore. 19. Department of Science & Technology/National Research Foundation of Excellence for Biomedical Tuberculosis Research, and South African Medical Research Council Centre for Molecular and Cellular Biology, Division of Molecular Biology and Human Genetics, Faculty of Medicine and Health Sciences, Stellenbosch University, Tygerberg, South Africa, National Reference Laboratory for Mycobacteria, FZ Borstel, Germany.
Abstract
SETTING: Xpert® MTB/RIF is the most widely used molecular assay for rapid diagnosis of tuberculosis (TB). The number of polymerase chain reaction cycles after which detectable product is generated (cycle threshold value, CT) correlates with the bacillary burden.OBJECTIVE To investigate the association between Xpert CT values and smear status through a systematic review and individual-level data meta-analysis. DESIGN: Studies on the association between CT values and smear status were included in a descriptive systematic review. Authors of studies including smear, culture and Xpert results were asked for individual-level data, and receiver operating characteristic curves were calculated. RESULTS: Of 918 citations, 10 were included in the descriptive systematic review. Fifteen data sets from studies potentially relevant for individual-level data meta-analysis provided individual-level data (7511 samples from 4447 patients); 1212 patients had positive Xpert results for at least one respiratory sample (1859 samples overall). ROC analysis revealed an area under the curve (AUC) of 0.85 (95%CI 0.82-0.87). Cut-off CT values of 27.7 and 31.8 yielded sensitivities of 85% (95%CI 83-87) and 95% (95%CI 94-96) and specificities of 67% (95%CI 66-77) and 35% (95%CI 30-41) for smear-positive samples. CONCLUSION: Xpert CT values and smear status were strongly associated. However, diagnostic accuracy at set cut-off CT values of 27.7 or 31.8 would not replace smear microscopy. How CT values compare with smear microscopy in predicting infectiousness remains to be seen.
SETTING: Xpert® MTB/RIF is the most widely used molecular assay for rapid diagnosis of tuberculosis (TB). The number of polymerase chain reaction cycles after which detectable product is generated (cycle threshold value, CT) correlates with the bacillary burden.OBJECTIVE To investigate the association between Xpert CT values and smear status through a systematic review and individual-level data meta-analysis. DESIGN: Studies on the association between CT values and smear status were included in a descriptive systematic review. Authors of studies including smear, culture and Xpert results were asked for individual-level data, and receiver operating characteristic curves were calculated. RESULTS: Of 918 citations, 10 were included in the descriptive systematic review. Fifteen data sets from studies potentially relevant for individual-level data meta-analysis provided individual-level data (7511 samples from 4447 patients); 1212 patients had positive Xpert results for at least one respiratory sample (1859 samples overall). ROC analysis revealed an area under the curve (AUC) of 0.85 (95%CI 0.82-0.87). Cut-off CT values of 27.7 and 31.8 yielded sensitivities of 85% (95%CI 83-87) and 95% (95%CI 94-96) and specificities of 67% (95%CI 66-77) and 35% (95%CI 30-41) for smear-positive samples. CONCLUSION: Xpert CT values and smear status were strongly associated. However, diagnostic accuracy at set cut-off CT values of 27.7 or 31.8 would not replace smear microscopy. How CT values compare with smear microscopy in predicting infectiousness remains to be seen.
Authors: Palwasha Y Khan; Tom A Yates; Muhammad Osman; Robin M Warren; Yuri van der Heijden; Nesri Padayatchi; Edward A Nardell; David Moore; Barun Mathema; Neel Gandhi; Vegard Eldholm; Keertan Dheda; Anneke C Hesseling; Valerie Mizrahi; Roxana Rustomjee; Alexander Pym Journal: Lancet Infect Dis Date: 2018-12-13 Impact factor: 25.071
Authors: David J Horne; Mikashmi Kohli; Jerry S Zifodya; Ian Schiller; Nandini Dendukuri; Deanna Tollefson; Samuel G Schumacher; Eleanor A Ochodo; Madhukar Pai; Karen R Steingart Journal: Cochrane Database Syst Rev Date: 2019-06-07
Authors: Edith E Machowski; Matebogo Letutu; Limakatso Lebina; Ziyaad Waja; Reginah Msandiwa; Minja Milovanovic; Bhavna G Gordhan; Kennedy Otwombe; Sven O Friedrich; Richard Chaisson; Andreas H Diacon; Bavesh Kana; Neil Martinson Journal: BMC Infect Dis Date: 2021-05-22 Impact factor: 3.090