Cancer Epidemiol. 2026 Jul 31;104:103166. doi: 10.1016/j.canep.2026.103166. Online ahead of print.
ABSTRACT
BACKGROUND: Alcohol and tobacco are among the leading preventable causes of cancer worldwide and frequently co-occur. While both are well-established independent carcinogens, their combined effects remain insufficiently characterized and inconsistently interpreted across cancer types.
OBJECTIVE: This review synthesizes epidemiological and mechanistic evidence on alcohol-tobacco interaction in carcinogenesis, distinguishing statistical interaction from evidence of biological mechanism.
METHODS: We examined interaction patterns across major cancer sites and assess the extent to which combined effects exceed individual risks. Particular attention is given to methodological approaches used to quantify interaction, including additive and multiplicative models and their implications for causal interpretation.
RESULTS: Current evidence supports a heterogeneous landscape of interaction. Strong and consistent synergistic effects are observed for upper aerodigestive tract cancers, whereas evidence is heterogeneous for hepatocellular carcinoma and context-dependent for breast cancer. By contrast, lung, pancreatic, and early-onset colorectal cancers show predominantly independent effects, with tobacco remaining the principal driver of lung cancer. Mendelian randomization studies support independent causal effects of smoking and, for some cancers, alcohol, but have not assessed their joint interaction.
CONCLUSION: To reconcile these findings, we propose a unified conceptual framework in which alcohol-tobacco interaction is viewed as a continuum ranging from strong biological synergy to functional independence, depending on tissue-specific vulnerability and exposure context. Finally, we identify key gaps in the field, including the need for standardized interaction metrics, prospective cohorts capturing joint exposure trajectories, integrative multi-omics approaches, and combined Mendelian randomization studies. Addressing these challenges will be essential to improve risk stratification and inform both precision oncology strategies and targeted, combined prevention efforts.
PMID:42537280 | DOI:10.1016/j.canep.2026.103166
