Evidence map›Paper›PMID 42125491›Full record

ArticleThe Lancet regional health. Southeast Asia2026

Cost-effectiveness of a mTB-Tobacco intervention for smoking cessation in people with tuberculosis: an economic evaluation of a cluster randomised controlled trial.

Jinshuo Li, Steve Parrott, Maham Zahid, Fahmidur Rahman, Mahmoud Danaee, Shakhawat Hossain Rana, Asiful Chowdhury, Saeed Ansaari, Ai Keow Lim, Melanie Boeckmann and 4 more

Abstract read
In one paragraph

Article in The Lancet regional health. Southeast Asia, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

14 authors.

Jinshuo LiDepartment of Health Sciences, University of York, Heslington, York, YO10 5DD, UK.
Steve ParrottDepartment of Health Sciences, University of York, Heslington, York, YO10 5DD, UK.
Maham ZahidThe Initiative, Orange Grove Farm, Main Korung Road, Banigala, Islamabad, 44000, Pakistan.
Fahmidur RahmanARK Foundation, Suite A-1, C-3 & C-4, House # 06, Road # 109, Gulshan-2, Dhaka, 1212, Bangladesh.
Mahmoud DanaeeDepartment of Social and Preventive Medicine, Faculty of Medicine, University of Malaya, 50603, Kuala Lumpur, Malaysia.
Shakhawat Hossain RanaARK Foundation, Suite A-1, C-3 & C-4, House # 06, Road # 109, Gulshan-2, Dhaka, 1212, Bangladesh.
Asiful ChowdhuryARK Foundation, Suite A-1, C-3 & C-4, House # 06, Road # 109, Gulshan-2, Dhaka, 1212, Bangladesh.
Saeed AnsaariThe Initiative, Orange Grove Farm, Main Korung Road, Banigala, Islamabad, 44000, Pakistan.
Ai Keow LimUsher Institute, Usher Building, University of Edinburgh, 5-7 Little France Road, Edinburgh BioQuarter - Gate 3, Edinburgh, EH16 4UX, UK.
Melanie BoeckmannDepartment of Global Health, Institute of Public Health and Nursing Research IPP, University of Bremen, Universitaetsallee 1B, 28359, Bremen, Germany.
Amina KhanThe Initiative, Orange Grove Farm, Main Korung Road, Banigala, Islamabad, 44000, Pakistan.
Rumana HuqueARK Foundation, Suite A-1, C-3 & C-4, House # 06, Road # 109, Gulshan-2, Dhaka, 1212, Bangladesh.
John NorrieCentre for Public Health, Institute of Clinical Sciences, Royal Victoria Hospital, Queen's University, Belfast, BT12 6BA, UK.
Kamran SiddiqiHull York Medical School, University of York, York, YO31 0TN, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: High prevalence of smoking tobacco among people with tuberculosis (TB) contribute towards poor outcomes in low- and middle-income countries. A mobile phone-based intervention for smoking cessation among this population (mTB-Tobacco) was evaluated for its cost-effectiveness alongside a cluster randomised controlled trial in Pakistan and Bangladesh. Methods: A two-arm superiority cluster randomised controlled trial with 6 months follow up was conducted between September 2023 and January 2025 in Dhaka, Bangladesh and Punjab, Pakistan. The trial compared the mTB-Tobacco intervention with usual care as control. Participants included those older than or equal to 15 years of age, diagnosed with drug-sensitive pulmonary TB in the past 4 weeks, smoked tobacco daily but willing to quit, and had access to mobile phones. Eighteen TB health facilities (cluster) were randomised to mTB-Tobacco group (n = 720 participants) and nine to usual care (n = 360 participants). The primary analysis was an incremental cost-utility analysis from a public/voluntary sector perspective and primary outcome measure was Quality-Adjusted Life Years (QALYs). Total costs included the costs of TB treatment, costs of intervention or control, and costs of doctor visit and hospital stay. Secondary and sensitivity analyses were also conducted. Findings: Total costs were INT$ (international dollars) 36.17 (95% CI 3.65-65.81) higher and QALYs were 0.017 (95% CI 0.003-0.030) higher in mTB-Tobacco group than usual care group. Incremental cost-effectiveness ratio was calculated at INT$2127.64 per QALY gained. Estimates by country suggested mTB-Tobacco being unlikely cost-effective in Bangladesh (ICER = INT$4261.11 per QALY gained) but likely cost-effective in Pakistan (ICER = INT$1024.29 per QALY gained). Interpretation: If decision makers in the public/voluntary sector are willing to pay over INT$2100 for one additional QALY gained, mTB-Tobacco intervention could likely be cost-effective. Funding: The UK NIHR Global Health Research Unit on Respiratory Health (RESPIRE) (NIHR132826).

Indexed as

Cost-effectivenessEconomic evaluationLow- and middle-income countriesMobile healthRandomised controlled trialSmoking cessationTuberculosis

Identifiers

PMID42125491
PMCPMC13158790

What OpenQuestion holds

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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.