Evidence map›Paper›PMID 36650014›Full record

SynthesisBMJ global health2023

Prevalence and predictive factors of tuberculosis treatment interruption in the Asia region: a systematic review and meta-analysis.

Ai Ling Oh, Mohd Makmor-Bakry, Farida Islahudin, Ian Ck Wong

Open access · goldAbstract readMeta-AnalysisSystematic Review
In one paragraph

Synthesis in BMJ global health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed, 2 pooled it
6.2field-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

18 citing papers in PubMed, 2 syntheses or guidelines pooled it, 32 citations in OpenAlex.

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  14. Occurrence of multidrug-resistantVeterinary world · 2024
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  17. Clinical standards for the management of adverse effects during treatment for TB.The international journal of tuberculosis and lung disease : the official journal of the International Union against Tuberculosis and Lung Disease · 2023
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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

4 authors at 1 institution in 3 countries.

Ai Ling OhFaculty of Pharmacy, Universiti Kebangsaan Malaysia, Kuala Lumpur, Malaysia.
Mohd Makmor-BakryFaculty of Pharmacy, Universiti Kebangsaan Malaysia, Kuala Lumpur, Malaysia mohdclinpharm@ukm.edu.my.
Farida IslahudinFaculty of Pharmacy, Universiti Kebangsaan Malaysia, Kuala Lumpur, Malaysia.
Ian Ck WongFaculty of Pharmacy, Universiti Kebangsaan Malaysia, Kuala Lumpur, Malaysia.
National University of Malaysia · MY

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionTuberculosis (TB) treatment interruption remains a critical challenge leading to poor treatment outcomes. Two-thirds of global new TB cases are mostly contributed by Asian countries, prompting systematic analysis of predictors for treatment interruption due to the variable findings.

methodsArticles published from 2012 to 2021 were searched through seven databases. Studies that established the relationship for risk factors of TB treatment interruption among adult Asian were included. Relevant articles were screened, extracted and appraised using Joanna Briggs Institute's checklists for cohort, case-control and cross-sectional study designs by three reviewers. Meta-analysis was performed using the random effect model in Review Manager software. The pooled prevalence and predictors of treatment interruption were expressed in ORs with 95% CIs; heterogeneity was assessed using the I

resultsFifty eligible studies (658 304 participants) from 17 Asian countries were included. The overall pooled prevalence of treatment interruption was 17% (95% CI 16% to 18%), the highest in Southern Asia (22% (95% CI 16% to 29%)), followed by Eastern Asia (18% (95% CI 16% to 20%)) and South East Asia (16% (95% CI 4% to 28%)). Seven predictors were identified to increase the risk of treatment interruption, namely, male gender (OR 1.38 (95% CI 1.26 to 1.51)), employment (OR 1.43 (95% CI 1.11 to 1.84)), alcohol intake (OR 2.24 (95% CI 1.58 to 3.18)), smoking (OR 2.74 (95% CI 1.98 to 3.78)), HIV-positive (OR 1.50 (95% CI 1.15 to 1.96)), adverse drug reactions (OR 2.01 (95% CI 1.20 to 3.34)) and previously treated cases (OR 1.77 (95% CI 1.39 to 2.26)). All predictors demonstrated substantial heterogeneity except employment and HIV status with no publication bias.

conclusionThe identification of predictors for TB treatment interruption enables strategised planning and collective intervention to be targeted at the high-risk groups to strengthen TB care and control in the Asia region.

Indexed as

TuberculosisAdultAsiaCross-Sectional StudiesHumansMalePrevalenceRisk FactorsTuberculosis

Identifiers

PMID36650014
PMCPMC9853156
OpenAlexW4317207445

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.