Evidence map›Paper›PMID 40385422›Full record

ArticlemedRxiv : the preprint server for health sciences2025

Importance of confirmatory test characteristics in optimizing community-based screening for tuberculosis: An epidemiological modeling analysis.

Lukas E Brümmer, Theresa S Ryckman, Sourya Shrestha, Florian M Marx, William Worodria, Devasahayam J Christopher, Grant Theron, Adithya Cattamanchi, Claudia M Denkinger, David W Dowdy and 1 more

Abstract readPreprint
In one paragraph

Article in medRxiv : the preprint server for health sciences, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

11 authors.

Lukas E BrümmerDivision of Infectious Disease and Tropical Medicine, Center for Infectious Diseases, Heidelberg University Hospital, Heidelberg, Germany.ORCID 0000-0002-8812-7975
Theresa S RyckmanCenter for Tuberculosis Research, Division of Infectious Diseases, Johns Hopkins University School of Medicine, Baltimore, MD, USA.ORCID 0000-0003-3214-3228
Sourya ShresthaDepartment of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.ORCID 0000-0002-6106-6834
Florian M MarxDivision of Infectious Disease and Tropical Medicine, Center for Infectious Diseases, Heidelberg University Hospital, Heidelberg, Germany.ORCID 0000-0003-4630-4598
William WorodriaDepartment of Medicine, Mulago National Referral Hospital, Kampala, Uganda.
Devasahayam J ChristopherDepartment of Pulmonary Medicine, Christian Medical College, Vellore, India.ORCID 0000-0002-9405-8494
Grant TheronDSI-NRF Centre of Excellence for Biomedical Tuberculosis Research, Division of Molecular Biology and Human Genetics, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa.ORCID 0000-0002-9216-2415
Adithya CattamanchiCenter for Tuberculosis, Division of Pulmonary and Critical Care Medicine, University of California San Francisco, San Francisco, CA, USA.ORCID 0000-0002-6553-2601
Claudia M DenkingerDivision of Infectious Disease and Tropical Medicine, Center for Infectious Diseases, Heidelberg University Hospital, Heidelberg, Germany.ORCID 0000-0002-7216-7067
David W DowdyDepartment of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.ORCID 0000-0003-0481-7475
Emily A KendallDepartment of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.ORCID 0000-0002-0083-422X

Funding

The Center for Innovation in Point-of-Care Technologies for HIV/AIDS atNorthwestern University (C-THAN) Supplemental RequestU54EB027049 · NIBIB · NORTHWESTERN UNIVERSITY · PI Chad J Achenbach · 2018 to 2026
$24.0M
Rapid Research for Diagnostics Development in TB Network (R2D2 TB Network)U01AI152087 · NIAID · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI CATTAMANCHI, ADITHYA, DENKINGER, CLAUDIA MARIA · 2020 to 2024
$19.3M
Hotspot versus clinic-based active case finding for TB in Uganda: A pragmatic randomized trialR01HL138728 · NHLBI · JOHNS HOPKINS UNIVERSITY · PI David Wesley Dowdy, Emily A Kendall · 2017 to 2026
$5.4M
Who are the Ultra-positive, culture-negative? Understanding the trajectories of individuals in Uganda with trace M. tuberculosis nucleic acid in sputumR01HL153611 · NHLBI · JOHNS HOPKINS UNIVERSITY · PI KENDALL, EMILY A · 2020 to 2024
$3.2M
HIV and Mycobacterial Disease in MaliD43TW010350 · FIC · UNIV OF SCIENCES, TECH & TECH OF BAMAKO · PI MAIGA, ALMOUSTAPHA ISSIAKA, MURPHY, ROBERT LEO · 2016 to 2025
$3.0M
Pre- and post-treatment lung microbiota, metabolome and immune signatures at the site of disease in patients with active pulmonary tuberculosisR01AI136894 · NIAID · STELLENBOSCH UNIVERSITY · PI THERON, GRANT DE VOS · 2019 to 2023
$678k
FIC NIH HHS D43 TW010350NHLBI NIH HHS R01 HL138728NHLBI NIH HHS R01 HL153611NIAID NIH HHS R01 AI136894NIAID NIH HHS U01 AI152087NIBIB NIH HHS U54 EB027049
6 · The paper itself

Abstract

Background: Current active case-finding (ACF) efforts for tuberculosis (TB) are limited by the costs, operational barriers, and sensitivity of available tools to confirm a TB diagnosis. However, it is not well understood which of these limitations has the greatest epidemiological relevance and might therefore warrant prioritization in test development. Methods: We developed a state-transition model of a one-time, community-based ACF intervention, with a fixed budget of one million United States dollars for screening and confirmatory testing. Assuming an adult population with four time the national prevalence of Uganda, we compared the impact of this intervention on TB diagnoses, mortality, and transmission when using a currently available confirmatory test (mirroring sputum-based Xpert Ultra) versus an improved confirmatory test. We considered the following test improvements: (1) increased sensitivity (from 69% to 80%), (2) non-sputum specimen type (increasing specimen availability from 93% to 100%), (3) immediate turn-around of test results (increasing delivery of positive results from 91% to 100%), (4) reduced costs (from $20 to $9 per confirmatory test). For those individuals not included in ACF efforts, TB outcomes under routine care were informed by recent natural history models. Results: In a simulated target population of 400,000 adults, 6,421 (1.6%; 95% uncertainty range [UR] 5,316-7,531) had TB disease, and 873 (612-1,182) were projected to die of TB in the absence of ACF. Assuming current tests, ACF efforts could reach 83,808 (59,388-118,601; 21% of the target population) people under the allotted budget, connecting 651 (429-983) individuals with TB to treatment and averting 76 (39-132) deaths. Of all hypothetical confirmatory test improvements modeled, higher diagnostic sensitivity most increased the number of people with TB who received treatment as a result of ACF (by 14% [4-26%]). However, considering mortality or transmission as a metric, the largest reductions resulted from tests that provided immediate turn-around of results (by 11% [5-18%]). Conclusion: Making confirmatory tests for community-based TB screening more accessible and rapid may lead to greater population health benefits than further increasing sensitivity. Nonetheless, achieving large (>20%) increases in the health impact of ACF will require improvements to components of ACF other than the confirmatory diagnostic test.

Indexed as

active case-findingconfirmatory testingepidemiological modelingtuberculosis

Identifiers

PMID40385422
PMCPMC12083569

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LicenceCC BY-NC-ND
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.