Evidence map›Paper›PMID 36966785›Full record

ArticleThe Lancet. Global health2023

Quantifying progression and regression across the spectrum of pulmonary tuberculosis: a data synthesis study.

Alexandra S Richards, Bianca Sossen, Jon C Emery, Katherine C Horton, Torben Heinsohn, Beatrice Frascella, Federica Balzarini, Aurea Oradini-Alacreu, Brit Häcker, Anna Odone and 6 more

Abstract read
In one paragraph

Article in The Lancet. Global health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 51 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
51citing papers in PubMed, 1 pooled it
–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

51 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Subclinical tuberculosis: a meta-analysis of prevalence and scoping review of definitions, prevalence and clinical characteristics.European respiratory review : an official journal of the European Respiratory Society · 2024
    Pooled it
  2. Article
  3. Article
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  5. A model for the epidemiological impact of tuberculosis policy options.Bulletin of the World Health Organization · 2026
    Article
  6. Cost-effectiveness of community tuberculosis screening in South Africa.American journal of respiratory and critical care medicine · 2026
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

16 authors.

Alexandra S RichardsTB Modelling Group, TB Centre, London School of Hygiene & Tropical Medicine, London, UK; Infectious Disease Epidemiology Department, London School of Hygiene & Tropical Medicine, London, UK. Electronic address: alexandra.richards@lshtm.ac.uk.
Bianca SossenDepartment of Medicine, Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa.
Jon C EmeryTB Modelling Group, TB Centre, London School of Hygiene & Tropical Medicine, London, UK; Infectious Disease Epidemiology Department, London School of Hygiene & Tropical Medicine, London, UK.
Katherine C HortonTB Modelling Group, TB Centre, London School of Hygiene & Tropical Medicine, London, UK; Infectious Disease Epidemiology Department, London School of Hygiene & Tropical Medicine, London, UK.
Torben HeinsohnInstitute for Global Health, University College London, London, UK; Helmholtz Centre for Infection Research, Braunschweig, Germany; German Centre for Infection Research, Braunschweig, Germany.
Beatrice FrascellaSchool of Public Health, Vita-Salute San Raffaele University, Milan, Italy.
Federica BalzariniSchool of Public Health, Vita-Salute San Raffaele University, Milan, Italy; Local Health Authority of Bergamo, Bergamo, Italy.
Aurea Oradini-AlacreuSchool of Public Health, Vita-Salute San Raffaele University, Milan, Italy.
Brit HäckerDepartment of Public Health, Experimental and Forensic Medicine, University of Pavia, Pavia, Italy.
Anna OdoneGerman Central Committee Against Tuberculosis, Berlin, Germany.
Nicky McCreeshTB Modelling Group, TB Centre, London School of Hygiene & Tropical Medicine, London, UK; Infectious Disease Epidemiology Department, London School of Hygiene & Tropical Medicine, London, UK.
Alison D GrantTB Centre, London School of Hygiene & Tropical Medicine, London, UK; Africa Health Research Institute, School of Laboratory Medicine and Medical Sciences, College of Health Sciences, University of KwaZulu-Natal, Durban, South Africa; School of Public Health, University of the Witwatersrand, Johannesburg, South Africa.
Katharina KranzerClinical Research Department, Faculty of Infectious and Tropical Diseases, London School of Hygiene & Tropical Medicine, London, UK; Biomedical Research and Training Institute, Harare, Zimbabwe; Division of Infectious Diseases and Tropical Medicine, University Hospital, Ludwig Maximilian University of Munich, Munich, Germany.
Frank CobelensDepartment of Global Health and Amsterdam Institute for Global Health and Development, Amsterdam University Medical Centers, Amsterdam, Netherlands.
Hanif EsmailWellcome Centre for Infectious Diseases Research in Africa, Institute of Infectious Diseases and Molecular Medicine, University of Cape Town, Cape Town, South Africa; Institute for Global Health, University College London, London, UK; MRC Clinical Trials Unit, University College London, London, UK.
Rein M G J HoubenTB Modelling Group, TB Centre, London School of Hygiene & Tropical Medicine, London, UK; Infectious Disease Epidemiology Department, London School of Hygiene & Tropical Medicine, London, UK.

Funding

Medical Research Council MR/V00476X/1Wellcome TrustWellcome Trust 218261/Z/19/Z
6 · The paper itself

Abstract

backgroundPrevalence surveys show a substantial burden of subclinical (asymptomatic but infectious) tuberculosis, from which individuals can progress, regress, or even persist in a chronic disease state. We aimed to quantify these pathways across the spectrum of tuberculosis disease.

methodsWe created a deterministic framework of untreated tuberculosis disease with progression and regression between three states of pulmonary tuberculosis disease: minimal (non-infectious), subclinical (asymptomatic but infectious), and clinical (symptomatic and infectious). We obtained data from a previous systematic review of prospective and retrospective studies that followed and recorded the disease state of individuals with tuberculosis in a cohort without treatment. These data were considered in a Bayesian framework, enabling quantitative estimation of tuberculosis disease pathways with rates of transition between states and 95% uncertainty intervals (UIs).

findingsWe included 22 studies with data from 5942 individuals in our analysis. Our model showed that after 5 years, 40% (95% UI 31·3-48·0) of individuals with prevalent subclinical disease at baseline recover and 18% (13·3-24·0) die from tuberculosis, with 14% (9·9-19·2) still having infectious disease, and the remainder with minimal disease at risk of re-progression. Over 5 years, 50% (40·0-59·1) of individuals with subclinical disease at baseline never develop symptoms. For those with clinical disease at baseline, 46% (38·3-52·2) die and 20% (15·2-25·8) recover from tuberculosis, with the remainder being in or transitioning between the three disease states after 5 years. We estimated the 10-year mortality of people with untreated prevalent infectious tuberculosis to be 37% (30·5-45·4).

interpretationFor people with subclinical tuberculosis, classic clinical disease is neither an inevitable nor an irreversible outcome. As such, reliance on symptom-based screening means a large proportion of people with infectious disease might never be detected.

fundingTB Modelling and Analysis Consortium and European Research Council.

Indexed as

Communicable DiseasesTuberculosisTuberculosis, PulmonaryBayes TheoremHumansRetrospective Studies

Identifiers

PMID36966785
PMCPMC10126316

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.