Evidence map›Paper›PMID 32064514›Full record

ArticleClinical infectious diseases : an official publication of the Infectious Diseases Society of America2021

Yield, Efficiency, and Costs of Mass Screening Algorithms for Tuberculosis in Brazilian Prisons.

Andrea da Silva Santos, Roberto Dias de Oliveira, Everton Ferreira Lemos, Fabiano Lima, Ted Cohen, Olivia Cords, Leonardo Martinez, Crhistinne Gonçalves, Albert Ko, Jason R Andrews and 1 more

Open access · greenAbstract read
In one paragraph

Article in Clinical infectious diseases : an official publication of the Infectious Diseases Society of America, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
36citing papers in PubMed, 4 pooled it
0.7field-weighted citation impact, top 17% 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

36 citing papers in PubMed, 4 syntheses or guidelines pooled it, 53 citations in OpenAlex.

  1. Pooled it
  2. Number needed to screen for TB in clinical, structural or occupational risk groups.The international journal of tuberculosis and lung disease : the official journal of the International Union against Tuberculosis and Lung Disease · 2022
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  9. Lancet regional health. Americas · 2025
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

11 authors at 4 institutions in 2 countries.

Andrea da Silva SantosFaculty of Health Sciences, Federal University of Grande Dourados, Dourados, Brazil.
Roberto Dias de OliveiraSchool of Medicine, Federal University of Mato Grosso do Sul, Campo Grande, Brazil.
Everton Ferreira LemosSchool of Medicine, Federal University of Mato Grosso do Sul, Campo Grande, Brazil.
Fabiano LimaSchool of Medicine, Federal University of Mato Grosso do Sul, Campo Grande, Brazil.
Ted CohenDepartment of Epidemiology of Microbial Diseases, Yale University School of Public Health, New Haven, Connecticut, USA.
Olivia CordsDivision of Infectious Diseases and Geographic Medicine, Stanford University School of Medicine, Stanford, California, USA.
Leonardo MartinezDivision of Infectious Diseases and Geographic Medicine, Stanford University School of Medicine, Stanford, California, USA.
Crhistinne GonçalvesSchool of Medicine, Federal University of Mato Grosso do Sul, Campo Grande, Brazil.
Albert KoDepartment of Epidemiology of Microbial Diseases, Yale University School of Public Health, New Haven, Connecticut, USA.
Jason R AndrewsDivision of Infectious Diseases and Geographic Medicine, Stanford University School of Medicine, Stanford, California, USA.
Julio CrodaSchool of Medicine, Federal University of Mato Grosso do Sul, Campo Grande, Brazil.
Universidade Federal de Mato Grosso do Sul · BRStanford University · USYale University · USUniversidade Federal da Grande Dourados · BR

Funding

Yale Clinical and Translational Science Award (U Component)UL1TR001863 · NCATS · YALE UNIVERSITY · PI John H. Krystal, LUCILA OHNO-MACHADO · 2016 to 2026
$102.9M
Strategies for tuberculosis control in prisonsR01AI130058 · NIAID · STANFORD UNIVERSITY · PI Jason Randolph Andrews, Julio Henrique Rosa Croda · 2017 to 2026
$5.8M
Global Epidemiology of Infectious DiseasesT32AI052073 · NIAID · STANFORD UNIVERSITY · PI Angelle Desiree LaBeaud, Stephen Patrick Luby · 2003 to 2026
$4.2M
UC Davis DVM/PhD Medical Scientist Training ProgramT32GM136559 · NIGMS · UNIVERSITY OF CALIFORNIA AT DAVIS · PI Xinbin Chen, Bethany Paige Cummings · 2020 to 2026
$2.2M
NCATS NIH HHS UL1 TR001863NIAID NIH HHS R01 AI130058NIAID NIH HHS T32 AI052073NIGMS NIH HHS T32 GM136559
6 · The paper itself

Abstract

backgroundTuberculosis (TB) is a major cause of morbidity and mortality among incarcerated populations globally. We performed mass TB screening in 3 prisons and assessed yield, efficiency, and costs associated with various screening algorithms.

methodsBetween 2017 and 2018, inmates from 3 prisons in Brazil were screened for TB by symptom assessment, chest radiography, sputum testing by Xpert MTB/RIF fourth-generation assay, and culture. Chest radiographs were scored by an automated interpretation algorithm (Computer-Aided Detection for Tuberculosis [CAD4TB]) that was locally calibrated to establish a positivity threshold. Four diagnostic algorithms were evaluated. We assessed the yield (percentage of total cases found) and efficiency (prevalence among those screened) for each algorithm. We performed unit costing to estimate the costs of each screening or diagnostic test and calculated the cost per case detected for each algorithm.

resultsWe screened 5387 prisoners, of whom 214 (3.9%) were diagnosed with TB. Compared to other screening strategies initiated with chest radiography or symptoms, the trial of all participants with a single Xpert MTB/RIF sputum test detected 74% of all TB cases at a cost of US$249 per case diagnosed. Performing Xpert MTB/RIF screening tests only on those with symptoms had a similar cost per case diagnosed (US$255) but missed 35% more cases (73 vs 54) as screening all inmates.

conclusionsIn this prospective study in 3 prisons in a high TB burden country, we found that testing all inmates with sputum Xpert MTB/RIF was a sensitive approach, while remaining cost-efficient. These results support use of Xpert MTB/RIF for mass screening in TB-endemic prisons.

Indexed as

HIV InfectionsMycobacterium tuberculosisTuberculosisAlgorithmsBrazilHumansMass ScreeningPrisonsProspective StudiesSensitivity and SpecificitySputumalgorithmscost-effectivenessmass screeningprisonstuberculosis

Identifiers

PMID32064514
PMCPMC7935388
OpenAlexW3008647472

What OpenQuestion holds

Textmetadata
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.