Evidence map›Paper›PMID 34805431›Full record

ArticleOpen forum infectious diseases2021

Prediction Tool to Identify Children at Highest Risk of Tuberculosis Disease Progression Among Those Exposed at Home.

Meredith B Brooks, Leonid Lecca, Carmen Contreras, Roger Calderon, Rosa Yataco, Jerome Galea, Chuan-Chin Huang, Megan B Murray, Mercedes C Becerra

Open access · goldAbstract read
In one paragraph

Article in Open forum infectious diseases, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
0.3field-weighted citation impact, top 38% 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

6 citing papers in PubMed, 8 citations in OpenAlex.

  1. Risk of Tuberculosis Infection in Young Children Exposed to Multidrug-resistant Tuberculosis in the TB-CHAMP Multi-site Randomized Controlled Trial.Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2025
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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 3 institutions in 3 countries.

Meredith B BrooksDepartment of Global Health and Social Medicine, Harvard Medical School, Boston, Massachusetts, USA.ORCID https://orcid.org/0000-0003-1022-2515
Leonid LeccaDepartment of Global Health and Social Medicine, Harvard Medical School, Boston, Massachusetts, USA.
Carmen ContrerasPartners In Health/Socios En Salud, Lima, Peru.
Roger CalderonPartners In Health/Socios En Salud, Lima, Peru.
Rosa YatacoPartners In Health/Socios En Salud, Lima, Peru.
Jerome GaleaDepartment of Global Health and Social Medicine, Harvard Medical School, Boston, Massachusetts, USA.
Chuan-Chin HuangDepartment of Global Health and Social Medicine, Harvard Medical School, Boston, Massachusetts, USA.
Megan B MurrayDepartment of Global Health and Social Medicine, Harvard Medical School, Boston, Massachusetts, USA.
Mercedes C BecerraDepartment of Global Health and Social Medicine, Harvard Medical School, Boston, Massachusetts, USA.
Harvard University · USEsSALUD · PEUniversidade Federal do Rio de Janeiro · BR

Funding

Real-time surveillance to support dynamic and predictive models of MDR/XDR TBU19AI076217 · NIAID · BRIGHAM AND WOMEN'S HOSPITAL · PI FARMER, PAUL EDWARD · 2007 to 2011
$13.5M
Epidemiology of multidrug-resistant tuberculosis in PeruU01AI057786 · NIAID · HARVARD MEDICAL SCHOOL · PI BECERRA, MERCEDES C · 2009 to 2010
$1.2M
Tuberculosis in teens: a geospatial approach to predict community transmissionK01AI151083 · NIAID · HARVARD MEDICAL SCHOOL · PI Meredith Blair Brooks · 2021 to 2026
$698k
NIAID NIH HHS K01 AI151083NIAID NIH HHS U01 AI057786NIAID NIH HHS U19 AI076217
6 · The paper itself

Abstract

backgroundThere is a dearth of research to understand which children, among those who are exposed at home to tuberculosis (TB), are at the highest risk of TB disease, to tailor care. We sought to identify predictors of TB progression in children.

methodsWe conducted a prospective cohort study of children living with adults with pulmonary TB in Lima, Peru (2009-2012). We applied classification and regression tree analysis to examine potential predictors of incident TB disease during 12 months in 3 age groups (0-4, 5-9, and 10-14 years). We calculated the relative risk (RR) for top predictors in each age group.

resultsAmong 4545 children 0-14 years old, 156 (3.4%) were diagnosed with TB within 1 year of household exposure to TB (3.4%, 2.3%, and 4.7% in children 0-4, 5-9, and 10-14 years old, respectively). The most important predictor of TB was having a positive tuberculin skin test (TST) result, with RRs of 6.6 (95% CI, 4.0-10.7), 6.6 (95% CI, 3.2-13.6), and 5.2 (95% CI, 3.0-9.0) in the age groups 0-4, 5-9, and 10-14 years, respectively. In young children with a positive TST, not using isoniazid preventive treatment further increased risk of disease (RR, 12.2 [95% CI, 3.8-39.2]).

conclusionsWe present a tool that identifies child household contacts at high risk of TB disease progression based on data collected during contact tracing. In addition to the use of TB preventive therapy for all children exposed at home to TB, those children at highest risk of progressing to TB disease may benefit from more frequent follow-up.

Indexed as

CART analysisdecision treespediatricstuberculosis

Identifiers

PMID34805431
PMCPMC8599776
OpenAlexW3216752663

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.