ArticlePLoS medicine2026
Tobacco control policies on cancer prevention in the Eastern Mediterranean Region, 2025-2050: A modeling study.
Article in PLoS medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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.
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.
Who cites it
1 citing paper in PubMed.
- Projected preventable cancers through full implementation of tobacco control policies in East and South-East Asian countries, 2025-2050: a modeling study.The Lancet regional health. Western Pacific · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundDespite the implementation of control policies, smoking prevalence remains high in Eastern Mediterranean Region (EMR), and the impact of tobacco control efforts on cancer prevention is unclear. We assessed the potential impact of key policy interventions on tobacco-related cancer incidence in EMR countries from 2025 to 2050. METHODS AND
findingsWe conducted a modeling study using a country-level historical data to project tobacco smoking prevalence in EMR countries under four scenarios: (i) full implementation of the MPOWER (Monitor, Protection, Offer, Warn, Enforce, and Raise) policy package, (ii) a 10-unit increase in the cigarette affordability index (Higher values of the affordability index indicate that cigarettes are less affordable) (iii) maximized literacy rates (100% adult literacy), and (iv) combined implementation of all three policies. For each scenario, we estimated the Population Attributable Fraction (PAF) of tobacco smoking for 13 cancer types causally linked to tobacco use. The number of preventable cancer cases was calculated using the difference in PAFs between the current and alternative scenarios, referred to as the Potential Impact Fraction (PIF). An estimated 14.3 million tobacco-related cancer cases will occur in the EMR between 2025 and 2050, with over 3 million attributable to current smoking prevalence (PAF = 21.3%; [95% CI: 18.4, 24.6]). Combined implementation of all assessed policies could prevent 442,292 cases (95% CI: 226,987, 660,045) (3.1% of all projected cases; [95% CI: 1.6, 4.6]). The greatest impact was observed in low HDI (Human Development Index) countries, where up to 291,425 (95% CI: 198,186, 388,546) cases could be averted. Maximizing literacy showed the highest preventive potential in low (n = 224,463; [95% CI: 149,521, 307,386]) and medium HDI (n = 84,569; [95% CI: [2,801, 177,317]) countries, while full implementation of MPOWER had the greatest effect in high HDI countries (n = 11,890; [95% CI: 8,397, 15,378]). As our main limitation, we assumed a causal relationship between previously implemented policies and concurrent changes, while other potential causes of these changes have not been considered in the current study.
conclusionStrengthening tobacco control policies particularly improving literacy in low HDI countries may potentially contribute to reductions in future cancer burden in EMR.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.