Evidence map›Paper›PMID 41734924›Full record

ArticleBMJ open2026

Markov-model cost-effectiveness evaluation of a cessation programme when tobacco policies are comprehensive.

Irene Mussio, Patricia Triunfo, Mariana Gerstenblüth

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Article in BMJ open, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Irene MussioDepartment of Economics, Leeds University Business School, Leeds, UK i.mussio@leeds.ac.uk.ORCID http://orcid.org/0000-0003-3724-9865
Patricia TriunfoDepartamento de Economía, Universidad de la Republica Uruguay, Montevideo, Uruguay.
Mariana GerstenblüthDepartamento de Economía, Universidad de la Republica Uruguay, Montevideo, Uruguay.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesThis study conducts a cost-effectiveness analysis of the Tobacco Treatment Programme (TTP) of Uruguay's National Resource Fund (NRF), within the context of the country's advanced implementation of tobacco control policies.

designWe run a 10 000 Markov model simulation with three states (people who smoke, people who have quit smoking and death) to simulate the trajectories of a cohort. The model has been widely used in previous studies evaluating smoking cessation interventions.

participantsFor the simulations, we use information from the 2016 to 2017 NRF TTP cohort. Nearly half of the participants lived in the capital, one-fifth had tertiary education, and about one-third had public health coverage. Participants began smoking at an average age of 16 years and smoked about 20 cigarettes per day when entering the TTP.

interventionsThe process of tobacco cessation is simulated under different alternatives: no intervention, the current TTP (bupropion, nicotine gum and counselling), an expanded TTP that incorporates nicotine patches as a replacement therapy, and a potential future programme with cytisine and counselling (with and without mortality adjustments).

settingWe focus on Uruguay, which has been recognised as a global leader in tobacco control, including 100% smoke-free environments, a full advertising ban, plain packaging and steady tax increases. MEASUREMENTS: We compare cost-effectiveness of policy alternatives using years of life lost (YLL) and incremental cost-effectiveness ratios, comparing policy alternatives with no intervention and the current tobacco cessation programme in the country. The analysis considers the direct costs of treatments for smoking-related diseases (healthcare perspective) as well as social costs resulting from loss of productivity (societal perspective).

resultsThe results indicate that all policy interventions lead to a reduction in the YLL compared with no intervention. Among these options, the inclusion of cytisine emerges as the most cost-effective choice. In a scenario including the transition probabilities from the TTP cohort, this alternative would result in a 10.9% reduction in YLL, with a particularly positive impact among women (-16.5% vs -4.0% in men). In terms of cost-effectiveness, the costs per YLL averted would be on average US$3991 per YLL from a healthcare perspective, and US$3773 per YLL from a societal perspective.

conclusionsTobacco cessation programmes in Uruguay are highly cost-effective, and our results justify their expansion and optimisation. The incorporation of cytisine into the TTP and a focus on groups with more severe tobacco consumption are recommended.

Indexed as

Health PolicySmoking CessationAdolescentAlkaloidsAzocinesCost-Benefit AnalysisCost-Effectiveness AnalysisCounselingFemaleHumansMaleMarkov ChainsNicotine Replacement TherapyQuinolizidine AlkaloidsQuinolizinesTobacco ControlAlkaloidsAzocinescytisineQuinolizidine AlkaloidsQuinolizinesHealth Care CostsHEALTH ECONOMICSHealth policyTobacco Use

Identifiers

PMID41734924
PMCPMC12933769

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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.