Evidence map›Paper›PMID 31678031›Full record

ArticleThe Lancet. Infectious diseases2020

A household-level score to predict the risk of tuberculosis among contacts of patients with tuberculosis: a derivation and external validation prospective cohort study.

Matthew J Saunders, Tom Wingfield, Sumona Datta, Rosario Montoya, Eric Ramos, Matthew R Baldwin, Marco A Tovar, Benjamin E W Evans, Robert H Gilman, Carlton A Evans

Open access · hybridAbstract readValidation Study
In one paragraph

Article in The Lancet. Infectious diseases, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
34citing papers in PubMed, 3 pooled it
5.9field-weighted citation impact, top 3% 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

34 citing papers in PubMed, 3 syntheses or guidelines pooled it, 63 citations in OpenAlex.

  1. Pooled it
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  4. Key risk factors for pulmonary vs. extrapulmonary tuberculosis: a comparative study in Southwest Ethiopia.Journal of clinical tuberculosis and other mycobacterial diseases · 2026
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  12. Effects of the COVID-19 Pandemic on Patients with Tuberculosis.Journal of clinical practice and research · 2024
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

10 authors at 5 institutions in 4 countries.

Matthew J SaundersDepartment of Infectious Diseases, Imperial College London, London, UK; Innovation For Health And Development, Laboratory of Research and Development, Universidad Peruana Cayetano Heredia, Lima, Peru; Innovación Por la Salud Y Desarrollo, Asociación Benéfica PRISMA, Lima, Peru. Electronic address: matthew.saunders@ifhad.org.
Tom WingfieldInnovation For Health And Development, Laboratory of Research and Development, Universidad Peruana Cayetano Heredia, Lima, Peru; Innovación Por la Salud Y Desarrollo, Asociación Benéfica PRISMA, Lima, Peru; Department of Clinical Infection, Microbiology and Immunology, Institute of Infection and Global Health, University of Liverpool, UK; LIV-TB Collaboration and Department of Clinical Science, Liverpool School of Tropical Medicine, Liverpool, UK; Social Medicine, Infectious Diseases and Migration Group, Department of Public Health Sciences, Karolinska Institute, Stockholm, Sweden.
Sumona DattaDepartment of Infectious Diseases, Imperial College London, London, UK; Innovation For Health And Development, Laboratory of Research and Development, Universidad Peruana Cayetano Heredia, Lima, Peru; Innovación Por la Salud Y Desarrollo, Asociación Benéfica PRISMA, Lima, Peru.
Rosario MontoyaInnovation For Health And Development, Laboratory of Research and Development, Universidad Peruana Cayetano Heredia, Lima, Peru; Innovación Por la Salud Y Desarrollo, Asociación Benéfica PRISMA, Lima, Peru.
Eric RamosInnovation For Health And Development, Laboratory of Research and Development, Universidad Peruana Cayetano Heredia, Lima, Peru; Innovación Por la Salud Y Desarrollo, Asociación Benéfica PRISMA, Lima, Peru.
Matthew R BaldwinInnovation For Health And Development, Laboratory of Research and Development, Universidad Peruana Cayetano Heredia, Lima, Peru; Innovación Por la Salud Y Desarrollo, Asociación Benéfica PRISMA, Lima, Peru; College of Physicians and Surgeons, Columbia University, New York, NY, USA.
Marco A TovarInnovation For Health And Development, Laboratory of Research and Development, Universidad Peruana Cayetano Heredia, Lima, Peru; Innovación Por la Salud Y Desarrollo, Asociación Benéfica PRISMA, Lima, Peru.
Benjamin E W EvansInnovation For Health And Development, Laboratory of Research and Development, Universidad Peruana Cayetano Heredia, Lima, Peru.
Robert H GilmanJohns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
Carlton A EvansDepartment of Infectious Diseases, Imperial College London, London, UK; Innovation For Health And Development, Laboratory of Research and Development, Universidad Peruana Cayetano Heredia, Lima, Peru; Innovación Por la Salud Y Desarrollo, Asociación Benéfica PRISMA, Lima, Peru.
Prisma · PEUniversidad Peruana Cayetano Heredia · PEImperial College London · GBJohns Hopkins University · USKarolinska Institutet · SE

Funding

Medical Research Council MR/K007467/1Wellcome TrustWellcome Trust 057434/Z/99/ZWellcome Trust 070005/Z/02/ZWellcome Trust 078340/Z/05/ZWellcome Trust 105788/Z/14/ZWellcome Trust 201251/Z/16/Z
6 · The paper itself

Abstract

backgroundThe epidemiological impact and cost-effectiveness of social protection and biomedical interventions for tuberculosis-affected households might be improved by risk stratification. We therefore derived and externally validated a household-level risk score to predict tuberculosis among contacts of patients with tuberculosis.

methodsIn this prospective cohort study, we recruited tuberculosis-affected households from 15 desert shanty towns in Ventanilla and 17 urban communities in Callao, Lima, Peru. Tuberculosis-affected households included index patients with a new diagnosis of tuberculosis and their contacts who reported being in the same house as the index patient for more than 6 h per week in the 2 weeks preceding index patient diagnosis. Tuberculosis-affected households were not included if the index patient had no eligible contacts or lived alone. We followed contacts until 2018 and defined household tuberculosis, the primary outcome, as any contact having any form of tuberculosis within 3 years. We used logistic regression to identify characteristics of index patients, contacts, and households that were predictive of household tuberculosis, and used these to derive and externally validate a household-level score.

findingsBetween Dec 12, 2007, and Dec 31, 2015, 16 505 contacts from 3 301 households in Ventanilla were included in a derivation cohort. During the 3-year follow-up, tuberculosis occurred in contacts of index patients in 430 (13%, 95% CI 12-14) households. Index patient predictors were pulmonary tuberculosis and sputum smear grade, age, and the maximum number of hours any contact had spent with the index patient while they had any cough. Household predictors were drug use, schooling of the female head of a household, and lower food spending. Contact predictors were if any of the contacts were children, number of lower-weight (body-mass index [BMI] <20·0 kg/m

interpretationThis externally validated score will enable comprehensive biosocial, household-level interventions to be targeted to tuberculosis-affected households that are most likely to benefit.

fundingWellcome Trust, Medical Research Council, Department of Health and Social Care, Department for International Development, Joint Global Health Trials consortium, Bill & Melinda Gates Foundation, Innovation for Health and Development.

Indexed as

Family CharacteristicsSurveys and QuestionnairesAdolescentAdultChildChild, PreschoolContact TracingCoughFemaleHumansIllicit DrugsInfantInfant, NewbornMaleMiddle AgedPeruIllicit Drugs

Identifiers

PMID31678031
PMCPMC6928575
OpenAlexW2982301714

What OpenQuestion holds

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LicenceCC BY
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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.