Evidence map›Paper›PMID 38051717›Full record

ArticlePLOS global public health2023

Impact of active case-finding for tuberculosis on case-notifications in Blantyre, Malawi: A community-based cluster-randomised trial (SCALE).

Helena R A Feasey, McEwen Khundi, Rebecca Nzawa Soko, Christian Bottomley, Lingstone Chiume, Helen E D Burchett, Marriott Nliwasa, Hussein H Twabi, James A Mpunga, Peter MacPherson and 1 more

Abstract read
In one paragraph

Article in PLOS global public health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
–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

12 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Genomic epidemiology ofMicrobial genomics · 2026
    Article
  5. Observational
  6. Article
  7. Review
  8. Article
  9. Article
  10. Community tuberculosis screening, testing and care, Uganda.Bulletin of the World Health Organization · 2024
    Article
  11. Review
  12. 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

11 authors.

Helena R A FeaseyLondon School of Hygiene and Tropical Medicine, London, United Kingdom.ORCID https://orcid.org/0000-0003-3109-6722
McEwen KhundiAfrican Institute for Development Policy, Lilongwe, Malawi.ORCID https://orcid.org/0000-0003-2718-7576
Rebecca Nzawa SokoMalawi-Liverpool-Wellcome Trust Clinical Research Programme, Blantyre, Malawi.ORCID https://orcid.org/0000-0001-6804-186X
Christian BottomleyLondon School of Hygiene and Tropical Medicine, London, United Kingdom.ORCID https://orcid.org/0000-0002-5241-8412
Lingstone ChiumeMalawi-Liverpool-Wellcome Trust Clinical Research Programme, Blantyre, Malawi.
Helen E D BurchettLondon School of Hygiene and Tropical Medicine, London, United Kingdom.ORCID https://orcid.org/0000-0002-8380-2476
Marriott NliwasaMalawi-Liverpool-Wellcome Trust Clinical Research Programme, Blantyre, Malawi.ORCID https://orcid.org/0000-0002-3100-5512
Hussein H TwabiMalawi-Liverpool-Wellcome Trust Clinical Research Programme, Blantyre, Malawi.ORCID https://orcid.org/0000-0003-4473-296X
James A MpungaNational Tuberculosis Control Programme, Lilongwe, Malawi.
Peter MacPhersonSchool of Health & Wellbeing, University of Glasgow, Glasgow, United Kingdom.ORCID https://orcid.org/0000-0002-0329-9613
Elizabeth L CorbettLondon School of Hygiene and Tropical Medicine, London, United Kingdom.

Funding

Wellcome Trust
6 · The paper itself

Abstract

Active case-finding (ACF) for tuberculosis can help find the "missing millions" with undiagnosed tuberculosis. In a cluster-randomised trial, we investigated impact of ACF on case-notifications in Blantyre, Malawi, where ACF has been intensively implemented following 2014 estimates of ~1,000 per 100,000 adults with undiagnosed TB. Following a pre-intervention prevalence survey (May 2019 to March 2020), constrained randomisation allocated neighbourhoods to either door-to-door ACF (sputum microscopy for reported cough >2 weeks) or standard-of-care (SOC). Implementation was interrupted by COVID-19. Cluster-level bacteriologically-confirmed case-notification rate (CNR) ratio within 91 days of ACF was our redefined primary outcome; comparison between arms used Poisson regression with random effects. Secondary outcomes were 91-day CNR ratios comparing all tuberculosis registrations and all non-ACF registrations. Interrupted time series (ITS) analysis of CNRs in the SOC arm examined prevalence survey impact. (ISRCTN11400592). 72 clusters served by 10 study-supported tuberculosis registration centres were randomised to ACF (261,244 adults, 58,944 person-years follow-up) or SOC (256,713 adults, 52,805 person-years). Of 1,192 ACF participants, 13 (1.09%) were smear-positive. Within 91 days, 113 (42 bacteriologically-confirmed) and 108 (33 bacteriologically-confirmed) tuberculosis patients were identified as ACF or SOC cluster residents, respectively. There was no difference by arm, with adjusted 91-day CNR ratios 1.12 (95% CI: 0.61-2.07) for bacteriologically-confirmed tuberculosis; 0.93 (95% CI: 0.68-1.28) for all tuberculosis registrations; and 0.86 (95%CI: 0.63-1.16) for non-ACF (routinely) diagnosed. Of 7,905 ACF and 7,992 SOC pre-intervention survey participants, 12 (0.15%) and 17 (0.21%), respectively, had culture/Xpert-confirmed tuberculosis. ITS analysis showed no survey impact on SOC CNRs. Despite residual undiagnosed tuberculosis of 150 per 100,000 population, there was no increase in tuberculosis notifications from this previously successful approach targeting symptomatic disease, likely due to previous TB ACF and rapid declines in TB burden. In such settings, future ACF should focus on targeted outreach and demand creation, alongside optimised facility-based screening. Trial Registration: ISRCTN11400592.

Identifiers

PMID38051717
PMCPMC10697577

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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.