Evidence map›Paper›PMID 34180536›Full record

SynthesisThe Cochrane database of systematic reviews2021

Screening tests for active pulmonary tuberculosis in children.

Bryan Vonasek, Tara Ness, Yemisi Takwoingi, Alexander W Kay, Susanna S van Wyk, Lara Ouellette, Ben J Marais, Karen R Steingart, Anna M Mandalakas

Open access · bronzeAbstract readMeta-AnalysisSystematic Review
In one paragraph

Synthesis in The Cochrane database of systematic reviews, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 49 papers, 7 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
49citing papers in PubMed, 7 pooled it
3.8field-weighted citation impact, top 5% of its field
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

49 citing papers in PubMed, 7 syntheses or guidelines pooled it, 69 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Pooled it
  5. Screening tests for active pulmonary tuberculosis in children.The Cochrane database of systematic reviews · 2021
    Pooled it
  6. Pooled it
  7. Pooled it
  8. Review
  9. HIV-Tuberculosis Co-Infection Among Immigrants and Refugees in the United States: An Integrative Review.International journal of environmental research and public health · 2026
    Review
  10. Article
  11. High prevalence of TB in children less than 5 years old hospitalised with severe acute malnutrition.The international journal of tuberculosis and lung disease : the official journal of the International Union against Tuberculosis and Lung Disease · 2026
    Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Review
  17. Article
  18. Article
  19. Article
  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors at 7 institutions in 4 countries.

Bryan VonasekThe Global Tuberculosis Program, Texas Children's Hospital, Section of Global and Immigrant Health, Department of Pediatrics, Baylor College of Medicine, Houston, Texas, USA.
Tara NessThe Global Tuberculosis Program, Texas Children's Hospital, Section of Global and Immigrant Health, Department of Pediatrics, Baylor College of Medicine, Houston, Texas, USA.
Yemisi TakwoingiTest Evaluation Research Group, Institute of Applied Health Research, University of Birmingham, Birmingham, UK.
Alexander W KayThe Global Tuberculosis Program, Texas Children's Hospital, Section of Global and Immigrant Health, Department of Pediatrics, Baylor College of Medicine , Houston, Texas, USA.
Susanna S van WykCentre for Evidence-based Health Care, Epidemiology and Biostatistics, Department of Global Health, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa.
Lara OuelletteTexas Medical Center Library, Houston, Texas, USA.
Ben J MaraisMarie Bashir Institute for Infectious Diseases and Biosecurity, University of Sydney, Sydney, Australia.
Karen R SteingartHonorary Research Fellow, Department of Clinical Sciences, Liverpool School of Tropical Medicine, Liverpool, UK.
Anna M MandalakasThe Global Tuberculosis Program, Texas Children's Hospital, Section of Global and Immigrant Health, Department of Pediatrics, Baylor College of Medicine , Houston, Texas, USA.
Baylor College of Medicine · USTexas Children's Hospital · USCochrane · GBTexas Medical Center · USUniversity of Birmingham · GBUniversity of Sydney · AUWestern Cape Department of Health · ZA

Funding

Microbial Pathogenesis &Host Responses Training ProgramT32AI055397 · NIAID · UNIVERSITY OF WISCONSIN-MADISON · PI KLEIN, BRUCE STEVEN · 2003 to 2024
$5.5M
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 TW011482NIAID NIH HHS T32 AI055397
6 · The paper itself

Abstract

backgroundGlobally, children under 15 years represent approximately 12% of new tuberculosis cases, but 16% of the estimated 1.4 million deaths. This higher share of mortality highlights the urgent need to develop strategies to improve case detection in this age group and identify children without tuberculosis disease who should be considered for tuberculosis preventive treatment. One such strategy is systematic screening for tuberculosis in high-risk groups.

objectivesTo estimate the sensitivity and specificity of the presence of one or more tuberculosis symptoms, or symptom combinations; chest radiography (CXR); Xpert MTB/RIF; Xpert Ultra; and combinations of these as screening tests for detecting active pulmonary childhood tuberculosis in the following groups. - Tuberculosis contacts, including household contacts, school contacts, and other close contacts of a person with infectious tuberculosis. - Children living with HIV. - Children with pneumonia. - Other risk groups (e.g. children with a history of previous tuberculosis, malnourished children). - Children in the general population in high tuberculosis burden settings. SEARCH

methodsWe searched six databases, including the Cochrane Central Register of Controlled Trials, MEDLINE, and Embase, on 14 February 2020 without language restrictions and contacted researchers in the field. SELECTION CRITERIA: Cross-sectional and cohort studies where at least 75% of children were aged under 15 years. Studies were eligible if conducted for screening rather than diagnosing tuberculosis. Reference standards were microbiological (MRS) and composite reference standard (CRS), which may incorporate symptoms and CXR. DATA COLLECTION AND ANALYSIS: Two review authors independently extracted data and assessed study quality using QUADAS-2. We consolidated symptom screens across included studies into groups that used similar combinations of symptoms as follows: one or more of cough, fever, or poor weight gain and one or more of cough, fever, or decreased playfulness. For combination of symptoms, a positive screen was the presence of one or more than one symptom. We used a bivariate model to estimate pooled sensitivity and specificity with 95% confidence intervals (CIs) and performed analyses separately by reference standard. We assessed certainty of evidence using GRADE. MAIN

resultsNineteen studies assessed the following screens: one symptom (15 studies, 10,097 participants); combinations of symptoms (12 studies, 29,889 participants); CXR (10 studies, 7146 participants); and Xpert MTB/RIF (2 studies, 787 participants). Several studies assessed more than one screening test. No studies assessed Xpert Ultra. For 16 studies (84%), risk of bias for the reference standard domain was unclear owing to concern about incorporation bias. Across other quality domains, risk of bias was generally low. Symptom screen (verified by CRS) One or more of cough, fever, or poor weight gain in tuberculosis contacts (4 studies, tuberculosis prevalence 2% to 13%): pooled sensitivity was 89% (95% CI 52% to 98%; 113 participants; low-certainty evidence) and pooled specificity was 69% (95% CI 51% to 83%; 2582 participants; low-certainty evidence). Of 1000 children where 50 have pulmonary tuberculosis, 339 would be screen-positive, of whom 294 (87%) would not have pulmonary tuberculosis (false positives); 661 would be screen-negative, of whom five (1%) would have pulmonary tuberculosis (false negatives). One or more of cough, fever, or decreased playfulness in children aged under five years, inpatient or outpatient (3 studies, tuberculosis prevalence 3% to 13%): sensitivity ranged from 64% to 76% (106 participants; moderate-certainty evidence) and specificity from 37% to 77% (2339 participants; low-certainty evidence). Of 1000 children where 50 have pulmonary tuberculosis, 251 to 636 would be screen-positive, of whom 219 to 598 (87% to 94%) would not have pulmonary tuberculosis; 364 to 749 would be screen-negative, of whom 12 to 18 (2% to 3%) would have pulmonary tuberculosis. One or more of cough, fever, poor weight gain, or tuberculosis close contact (World Health Organization four-symptom screen) in children living with HIV, outpatient (2 studies, tuberculosis prevalence 3% and 8%): pooled sensitivity was 61% (95% CI 58% to 64%; 1219 screens; moderate-certainty evidence) and pooled specificity was 94% (95% CI 86% to 98%; 201,916 screens; low-certainty evidence). Of 1000 symptom screens where 50 of the screens are on children with pulmonary tuberculosis, 88 would be screen-positive, of which 57 (65%) would be on children who do not have pulmonary tuberculosis; 912 would be screen-negative, of which 19 (2%) would be on children who have pulmonary tuberculosis. CXR (verified by CRS) CXR with any abnormality in tuberculosis contacts (8 studies, tuberculosis prevalence 2% to 25%): pooled sensitivity was 87% (95% CI 75% to 93%; 232 participants; low-certainty evidence) and pooled specificity was 99% (95% CI 68% to 100%; 3281 participants; low-certainty evidence). Of 1000 children, where 50 have pulmonary tuberculosis, 63 would be screen-positive, of whom 19 (30%) would not have pulmonary tuberculosis; 937 would be screen-negative, of whom 6 (1%) would have pulmonary tuberculosis. Xpert MTB/RIF (verified by MRS) Xpert MTB/RIF, inpatient or outpatient (2 studies, tuberculosis prevalence 1% and 4%): sensitivity was 43% and 100% (16 participants; very low-certainty evidence) and specificity was 99% and 100% (771 participants; moderate-certainty evidence). Of 1000 children, where 50 have pulmonary tuberculosis, 31 to 69 would be Xpert MTB/RIF-positive, of whom 9 to 19 (28% to 29%) would not have pulmonary tuberculosis; 969 to 931 would be Xpert MTB/RIF-negative, of whom 0 to 28 (0% to 3%) would have tuberculosis. Studies often assessed more symptoms than those included in the index test and symptom definitions varied. These differences complicated data aggregation and may have influenced accuracy estimates. Both symptoms and CXR formed part of the CRS (incorporation bias), which may have led to overestimation of sensitivity and specificity. AUTHORS'

conclusionsWe found that in children who are tuberculosis contacts or living with HIV, screening tests using symptoms or CXR may be useful, but our review is limited by design issues with the index test and incorporation bias in the reference standard. For Xpert MTB/RIF, we found insufficient evidence regarding screening accuracy. Prospective evaluations of screening tests for tuberculosis in children will help clarify their use. In the meantime, screening strategies need to be pragmatic to address the persistent gaps in prevention and case detection that exist in resource-limited settings.

Indexed as

Contact TracingAdolescentBiasChildChild BehaviorChild, PreschoolCohort StudiesConfidence IntervalsCoughCross-Sectional StudiesFalse Negative ReactionsFalse Positive ReactionsFeverHIV InfectionsHumansMass Screening

Identifiers

PMID34180536
PMCPMC8237391
OpenAlexW3045976532

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

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.