Diagnostic yield as an important metric for the evaluation of novel tuberculosis tests

• Verfasst von: Broger, Tobias [VerfasserIn]
• Verfasst von: Marx, Florian [VerfasserIn]
• Verfasst von: Theron, Grant [VerfasserIn]
• Verfasst von: Marais, Ben J [VerfasserIn]
• Verfasst von: Nicol, Mark P [VerfasserIn]
• Verfasst von: Kerkhoff, Andrew D [VerfasserIn]
• Verfasst von: Nathavitharana, Ruvandhi [VerfasserIn]
• Verfasst von: Huerga, Helena [VerfasserIn]
• Verfasst von: Gupta-Wright, Ankur [VerfasserIn]
• Verfasst von: Kohli, Mikashmi [VerfasserIn]
• Verfasst von: Nichols, Brooke E [VerfasserIn]
• Verfasst von: Muyoyeta, Monde [VerfasserIn]
• Verfasst von: Meintjes, Graeme [VerfasserIn]
• Verfasst von: Ruhwald, Morten [VerfasserIn]
• Verfasst von: Peeling, Rosanna W [VerfasserIn]
• Verfasst von: Pai, Nitika Pant [VerfasserIn]
• Verfasst von: Pollock, Nira R [VerfasserIn]
• Verfasst von: Pai, Madhukar [VerfasserIn]
• Verfasst von: Cattamanchi, Adithya [VerfasserIn]
• Verfasst von: Dowdy, David W [VerfasserIn]
• Verfasst von: Dewan, Puneet [VerfasserIn]
• Verfasst von: Denkinger, Claudia M. [VerfasserIn]
• Titel: Diagnostic yield as an important metric for the evaluation of novel tuberculosis tests
• Titelzusatz: rationale and guidance for future research
• Verf.angabe: Tobias Broger, Florian M Marx, Grant Theron, Ben J Marais, Mark P Nicol, Andrew D Kerkhoff, Ruvandhi Nathavitharana, Helena Huerga, Ankur Gupta-Wright, Mikashmi Kohli, Brooke E Nichols, Monde Muyoyeta, Graeme Meintjes, Morten Ruhwald, Rosanna W Peeling, Nitika Pant Pai, Nira R Pollock, Madhukar Pai, Adithya Cattamanchi, David W Dowdy, Puneet Dewan, Claudia M Denkinger
• E-Jahr: 2024
• Jahr: July 2024
• Umfang: 8 S.
• Illustrationen: Illustrationen
• Fussnoten: Online verfügbar 12 June 2024, Version des Artikels 12 June 2024 ; Gesehen am 27.01.2025
• Titel Quelle: Enthalten in: The lancet. Global health
• Ort Quelle: Oxford : Elsevier, 2013
• Jahr Quelle: 2024
• Band/Heft Quelle: 12(2024), 7, Seite e1184-e1191
• ISSN Quelle: 2214-109X
• DOI: doi:10.1016/S2214-109X(24)00148-7
• Datenträger: Online-Ressource
• Sprache: eng
• K10plus-PPN: 1915639956

Abstract

Better access to tuberculosis testing is a key priority for fighting tuberculosis, the leading cause of infectious disease deaths in people. Despite the roll-out of molecular WHO-recommended rapid diagnostics to replace sputum smear microscopy over the past decade, a large diagnostic gap remains. Of the estimated 10·6 million people who developed tuberculosis globally in 2022, more than 3·1 million were not diagnosed. An exclusive focus on improving tuberculosis test accuracy alone will not be sufficient to close the diagnostic gap for tuberculosis. Diagnostic yield, which we define as the proportion of people in whom a diagnostic test identifies tuberculosis among all people we attempt to test for tuberculosis, is an important metric not adequately explored. Diagnostic yield is particularly relevant for subpopulations unable to produce sputum such as young children, people living with HIV, and people with subclinical tuberculosis. As more accessible non-sputum specimens (eg, urine, oral swabs, saliva, capillary blood, and breath) are being explored for point-of-care tuberculosis testing, the concept of yield will be of growing importance. Using the example of urine lipoarabinomannan testing, we illustrate how even tests with limited sensitivity can diagnose more people with tuberculosis if they enable increased diagnostic yield. Using tongue swab-based molecular tuberculosis testing as another example, we provide definitions and guidance for the design and conduct of pragmatic studies that assess diagnostic yield. Lastly, we show how diagnostic yield and other important test characteristics, such as cost and implementation feasibility, are essential for increased effective population coverage, which is required for optimal clinical care and transmission impact. We are calling for diagnostic yield to be incorporated into tuberculosis test evaluation processes, including the WHO Grading of Recommendations, Assessment, Development, and Evaluations process, providing a crucial real-life implementation metric that complements traditional accuracy measures.