Multicomponent Strategy with Decentralized Molecular Testing for Tuberculosis

Cattamanchi, Adithya; Reza, Tania F.; Nalugwa, Talemwa; Adams, Katherine; Nantale, Mariam; Oyuku, Denis; Nabwire, Sarah; Babirye, Diana; Turyahabwe, Stavia; Tucker, Austin; Sohn, Hojoon; Ferguson, Olivia; Thompson, Ryan R.; Shete, Priya B.; Handley, Margaret A.; Ackerman, Sara; Joloba, Moses; Moore, David; Davis, J. Lucian; Dowdy, David W.; Fielding, Katherine; Katamba, Achilles

doi:10.1056/nejmoa2105470

Cited by 16 publications

(16 citation statements)

References 23 publications

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“…Currently, confirmatory tests are primarily done at distant district centralized laboratories using a nucleic acid amplification test (NAAT) like Xpert MTB/RIF Ultra [ 13 ] (Ultra; Cepheid), Truenat MTB (Truenat) [ 14 ], or culture methods like Mycobacteria Growth Indicator Tube 960. In addition to improving decentralization (which has important benefits vs. centralized testing [ 15 ]) and rapidity, a major challenge that needs to be overcome for a confirmatory testing revolution to occur is to show highly accurate non-sputum confirmatory diagnoses are possible in routine primary care settings without specimens needing to leave clinics. One key reason non-sputum testing is itself needed is because people living with HIV (PLHIV) and those not (yet) symptomatic, as well as children and patients with extrapulmonary TB, often cannot produce high-quality sputum.…”

Section: Introductionmentioning

confidence: 99%

Diagnosing Tuberculosis: What Do New Technologies Allow Us to (Not) Do?

Abdulgader¹,

Ojo-Okunola²,

Ndlangalavu³

et al. 2022

Respiration

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New tuberculosis (TB) diagnostics are at a crossroads: their development, evaluation, and implementation is severely damaged by resource diversion due to COVID-19. Yet several technologies, especially those with potential for non-invasive non-sputum-based testing, hold promise for efficiently triaging and rapidly confirming TB near point-of-care. Such tests are, however, progressing through the pipeline slowly and will take years to reach patients and health workers. Compellingly, such tests will create new opportunities for difficult-to-diagnose populations, including primary care attendees (all-comers in high burden settings irrespective of reason for presentation) and community members (with early stage disease or risk factors like HIV), many of whom cannot easily produce sputum. Critically, all upcoming technologies have limitations that implementers and health workers need to be cognizant of to ensure optimal deployment without undermining confidence in a technology that still offers improvements over the status quo. In this state-of-the-art review, we critically appraise such technologies for active pulmonary TB diagnosis. We highlight strengths, limitations, outstanding research questions, and how current and future tests could be used in the presence of these limitations and uncertainties. Among triage tests, CRP (for which commercial near point-of-care devices exist) and computer-aided detection software with digital chest X-ray hold promise, together with late-stage blood-based assays that detect host and/or microbial biomarkers; however, aside from a handful of prototypes, the latter category has a shortage of promising late-stage alternatives. Furthermore, positive results from new triage tests may have utility in people without TB; however, their utility for informing diagnostic pathways for other diseases is under-researched (most sick people tested for TB do not have TB). For confirmatory tests, few true point-of-care options will be available soon; however, combining novel approaches like tongue swabs with established tests like Ultra have short-term promise but first require optimizations to specimen collection and processing procedures. Concerningly, no technologies yet have compelling evidence of meeting the World Health Organization optimal target product profile performance criteria, especially for important operational criteria crucial for field deployment. This is alarming as the target product profile criteria are themselves almost a decade old and require urgent revision, especially to cater for technologies made prominent by the COVID-19 diagnostic response (e.g., at-home testing and connectivity solutions). Throughout the review, we underscore the importance of how target populations and settings affect test performance and how the criteria by which these tests should be judged vary by use case, including in active case finding. Lastly, we advocate for health workers and researchers to themselves be vocal proponents of the uptake of both new tests and those – already available tests that remain suboptimally utilized.

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Section: Introductionmentioning

confidence: 99%

Diagnosing Tuberculosis: What Do New Technologies Allow Us to (Not) Do?

Abdulgader¹,

Ojo-Okunola²,

Ndlangalavu³

et al. 2022

Respiration

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“…XPEL-TB assessed whether providing decentralised point-of-care molecular testing using the GeneXpert Edge platform, in conjunction with streamlined clinical workflows and performance feedback via monthly report cards, would increase the number of people diagnosed with tuberculosis and reduce pre-treatment loss to follow-up, compared with routine care. 13 , 14 Ten health centres were randomised to receive this package, and had GeneXpert Edge systems installed onsite. The remaining ten centres were randomised to routine care, with SSM performed onsite and molecular Xpert testing performed at an off-site facility in accordance with national guidelines.…”

Section: Methodsmentioning

confidence: 99%

“…The primary trial was performed under a waiver of informed consent for extraction of participant data. 13 , 14 …”

Section: Methodsmentioning

confidence: 99%

“…The Xpert Performance Evaluation for Linkage to Tuberculosis Care (XPEL-TB) trial in Uganda 13 showed that, relative to centralised testing, the XPEL-TB strategy—a multicomponent strategy focused around decentralised molecular testing—improved case detection and treatment initiation. 14 As part of the XPEL-TB study, we collected empirical economic data in the context of the trial to evaluate the cost and cost-effectiveness of the XPEL-TB strategy versus routine tuberculosis testing (onsite SSM plus centralised Xpert testing using a hub-and-spoke model).…”

Section: Introductionmentioning

confidence: 99%

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Multicomponent strategy with decentralised molecular testing for tuberculosis in Uganda: a cost and cost-effectiveness analysis

Thompson¹,

Nalugwa²,

Oyuku³

et al. 2023

The Lancet Global Health

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“…The XPEL-TB Study was a cluster-randomized trial examining the effect of a multicomponent diagnostic strategy on the number of TB patients initiating treatment within 14 days of diagnosis. The intervention included on-site GeneXpert testing for TB and monthly feedback of quality metrics to staff [24][25][26].…”

Section: Study Design and Rationalementioning

confidence: 99%

Is aggregated surveillance data a reliable method for constructing tuberculosis care cascades? A secondary data analysis from Uganda

White

Hernández-Ramírez²,

Majwala³

et al. 2022

PLOS Glob Public Health

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To accelerate tuberculosis (TB) control and elimination, reliable data is needed to improve the quality of TB care. We assessed agreement between a surveillance dataset routinely collected for Uganda’s national TB program and a high-fidelity dataset collected from the same source documents for a research study from 32 health facilities in 2017 and 2019 for six measurements: 1) Smear-positive and 2) GeneXpert-positive diagnoses, 3) bacteriologically confirmed and 4) clinically diagnosed treatment initiations, and the number of people initiating TB treatment who were also 5) living with HIV or 6) taking antiretroviral therapy. We measured agreement as the average difference between the two methods, expressed as the average ratio of the surveillance counts to the research data counts, its 95% limits of agreement (LOA), and the concordance correlation coefficient. We used linear mixed models to investigate whether agreement changed over time or was associated with facility characteristics. We found good overall agreement with some variation in the expected facility-level agreement for the number of smear positive diagnoses (average ratio [95% LOA]: 1.04 [0.38–2.82]; CCC: 0.78), bacteriologically confirmed treatment initiations (1.07 [0.67–1.70]; 0.82), and people living with HIV (1.11 [0.51–2.41]; 0.82). Agreement was poor for Xpert positives, with surveillance data undercounting relative to research data (0.45 [0.099–2.07]; 0.36). Although surveillance data overcounted relative to research data for clinically diagnosed treatment initiations (1.52 [0.71–3.26]) and number of people taking antiretroviral therapy (1.71 [0.71–4.12]), their agreement as assessed by CCC was not poor (0.82 and 0.62, respectively). Average agreement was similar across study years for all six measurements, but facility-level agreement varied from year to year and was not explained by facility characteristics. In conclusion, the agreement of TB surveillance data with high-fidelity research data was highly variable across measurements and facilities. To advance the use of routine TB data as a quality improvement tool, future research should elucidate and address reasons for variability in its quality.

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Multicomponent Strategy with Decentralized Molecular Testing for Tuberculosis

Cited by 16 publications

References 23 publications

Diagnosing Tuberculosis: What Do New Technologies Allow Us to (Not) Do?

Diagnosing Tuberculosis: What Do New Technologies Allow Us to (Not) Do?

Multicomponent strategy with decentralised molecular testing for tuberculosis in Uganda: a cost and cost-effectiveness analysis

Is aggregated surveillance data a reliable method for constructing tuberculosis care cascades? A secondary data analysis from Uganda

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