Evidence map›Paper›PMID 40492485›Full record

SynthesisThe Cochrane database of systematic reviews2025

Parallel use of low-complexity automated nucleic acid amplification tests and lateral flow urine lipoarabinomannan assays to detect tuberculosis disease in adults and adolescents living with HIV.

Stephanie Bjerrum, Bada Yang, Johanna Åhsberg, Laura Olbrich, Mathias Weis Damkjær, Ruvandhi R Nathavitharana, Tobias Broger, Ioana Diana Olaru, Brittney Sweetser, Hayley Poore and 8 more

Abstract readMeta-AnalysisReview
In one paragraph

Synthesis in The Cochrane database of systematic reviews, 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

18 authors.

Stephanie BjerrumDepartment of Clinical Research, Research Unit of Infectious Diseases, University of Southern Denmark, Odense, Denmark.
Bada YangCochrane Netherlands, Department of Epidemiology and Health Economics, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, Netherlands.
Johanna ÅhsbergDepartment of Clinical Research, Research Unit of Infectious Diseases, University of Southern Denmark, Odense, Denmark.
Laura OlbrichInstitute of Infectious Diseases and Tropical Medicine, LMU University Hospital, LMU Munich, Munich, Germany.
Mathias Weis DamkjærCochrane Denmark & Centre for Evidence-Based Medicine Odense, ​Department of Clinical Research, University of Southern Denmark, Odense, Denmark.
Ruvandhi R NathavitharanaDivision of Infectious Diseases, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, USA.
Tobias BrogerDepartment of Infectious Disease and Tropical Medicine, German Center of Infection Research, partner site, Heidelberg University Hospital, Heidelberg, Germany.
Ioana Diana OlaruDepartment of Infectious Disease and Tropical Medicine, German Center of Infection Research, partner site, Heidelberg University Hospital, Heidelberg, Germany.
Brittney SweetserDivision of Pulmonary Diseases and Critical Care Medicine, University of California, Irvine, USA.
Hayley PooreDivision of Pulmonary Diseases and Critical Care Medicine, University of California, Irvine, USA.
Alia RazidInstitute of Infectious Diseases and Tropical Medicine, LMU University Hospital, LMU Munich, Munich, Germany.
Alexander W KayThe Global Tuberculosis Program, Texas Children's Hospital, Department of Pediatrics, Baylor College of Medicine, Houston, Texas, USA.
Claudia M DenkingerDepartment of Infectious Disease and Tropical Medicine, German Center of Infection Research, partner site, Heidelberg University Hospital, Heidelberg, Germany.
Ian SchillerCentre for Outcomes Research, McGill University Health Centre - Research Institute, Montreal, Canada.
Nandini DendukuriCentre for Outcomes Research, McGill University Health Centre - Research Institute, Montreal, Canada.
Devan JaganathInstitute for Global Health Sciences, Center for Tuberculosis, University of California, San Francisco, San Francisco, USA.
Andreas LundhCochrane Denmark & Centre for Evidence-Based Medicine Odense, ​Department of Clinical Research, University of Southern Denmark, Odense, Denmark.
Maunank ShahDepartment of Medicine, Division of Infectious Diseases, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.

Funding

Developing Clinical Prediction Tools to Define Strategies for Differentiated Service Delivery in Children and Adolescents Living with HIV in sub-Saharan Africa.K01TW011482 · FIC · BAYLOR COLLEGE OF MEDICINE · PI KAY, ALEXANDER WILLIAM · 2020 to 2024
$749k
FIC NIH HHS K01 TW011482
6 · The paper itself

Abstract

backgroundLow-complexity automated nucleic acid amplification tests (LC-aNAATs) are molecular World Health Organization (WHO)-recommended rapid diagnostic tests (also known as mWRDs) widely used to diagnose tuberculosis disease. The lateral flow urine lipoarabinomannan assay (LF-LAM) is recommended by the WHO to assist in diagnosing tuberculosis disease amongst people with HIV. Previous systematic reviews have assessed the diagnostic accuracy of LC-aNAATs and LF-LAM used in isolation for the detection of tuberculosis, but in clinical practice the tests may be used in parallel (i.e. LC-aNAAT in combination with LF-LAM).

objectivesTo compare the diagnostic accuracy of the parallel use of LC-aNAAT on respiratory samples and LF-LAM on urine versus LC-aNAATs on respiratory samples alone for detection of tuberculosis disease in adults and adolescents with HIV who present with presumptive tuberculosis. SEARCH

methodsWe searched Cochrane CENTRAL, MEDLINE, Embase, Science Citation Index-Expanded, Biosis Previews, Conference Proceedings Citation Index - Science, Scopus, WHO Global Index Medicus, ProQuest Dissertations & Theses, ClinicalTrial.gov, and the WHO International Clinical Trials Registry up to 3 November 2023. SELECTION CRITERIA: We included studies that allowed assessment of the diagnostic accuracy of parallel testing and LC-aNAAT on respiratory samples in the same study group. Participants were adults and adolescents (defined as 10 years of age and older) with HIV who presented with presumptive tuberculosis. The reference standards we used for the detection of tuberculosis disease were microbiological or composite. As well as published studies, we included unpublished data if the data provided by study authors on request were the final data and could be used to compare diagnostic accuracy of parallel testing to one of the component tests. DATA COLLECTION AND ANALYSIS: Two review authors independently extracted data using a standardised form and assessed methodological quality using QUADAS-2 and QUADAS-C tools. We performed bivariate random-effects meta-analysis using a Bayesian approach to estimate sensitivity, specificity, and absolute differences between index tests. We performed subgroup analyses based on the presence of signs and symptoms, CD4 cell count, and clinical setting, as well as separate analyses for those with a positive screen for tuberculosis, advanced HIV, or serious illness. MAIN

resultsIn 27 studies involving 12,651 participants, of whom 2368 (19%) had tuberculosis based on a microbiological reference standard, the parallel use of respiratory LC-aNAAT and urine LF-LAM had a pooled sensitivity of 77.5% (95% credible interval (CrI) 73.4 to 81.3) and specificity of 89.4% (95% CrI 85.8 to 92.3). Compared to respiratory LC-aNAAT alone, parallel testing had 6.7 (95% CrI 3.8 to 10.7) percentage points higher sensitivity (low certainty) and -6.8 (95% CrI -9.5 to -4.7) percentage points difference in specificity (low-certainty evidence), using a microbiological reference standard. In 23 studies, 11,109 participants, of whom 3723 (34%) had tuberculosis based on a composite reference standard, parallel testing had a pooled sensitivity of 67.6% (95% CrI 59.9 to 74.6) and a pooled specificity of 96.2% (95% CrI 92.8 to 98.1). Compared to respiratory LC-aNAAT alone, parallel testing had 16.0 (10.7 to 22.9) percentage points higher sensitivity (low-certainty evidence) and -3.5 (95% CrI -6.6 to -1.7) percentage points difference in specificity (very low certainty evidence), using a composite reference standard. AUTHORS'

conclusionsIn the diagnosis of tuberculosis disease in people with HIV who present with presumptive tuberculosis, parallel testing (LC-aNAAT on respiratory samples and LF-LAM on urine) improves sensitivity at the cost of reduced specificity compared to LC-aNAAT on respiratory samples alone. The gain in sensitivity should be weighed against the loss of specificity, taking into consideration the varying tuberculosis prevalence in different settings. For low-prevalence settings, using the tests in parallel may lead to a large increase in false-positive results. In settings with high tuberculosis prevalence, the benefit of identifying additional patients with tuberculosis at the point-of-care likely outweighs the relatively lower risk of overtreatment of those without tuberculosis.

fundingInternal sources: Liverpool School of Tropical Medicine, UK External sources: Foreign, Commonwealth and Development Office (FCDO), UK. Project number 300342-104; WHO, TB Prevention, Diagnosis, Treatment, Care & Innovation (PCI), Global TB Programme REGISTRATION: Protocol available via https://doi.org/10.1002/14651858.CD016070, version published 13 May 2024.

Indexed as

HIV InfectionsLipopolysaccharidesNucleic Acid Amplification TechniquesTuberculosisTuberculosis, PulmonaryAdolescentAdultHumansRandomized Controlled Trials as TopicSensitivity and SpecificitylipoarabinomannanLipopolysaccharides

Identifiers

PMID40492485
PMCPMC12150366

What OpenQuestion holds

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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.