Background Tobacco smoking after cancer diagnosis is associated with impaired survival but large real-world evidence across cancers accounting for treatment intent and key prognostic factors remains scarce. We evaluated associations between smoking and survival in a population-based cohort. Materials and methods We identified all patients who were diagnosed with solid cancers (International Classification of Diseases, 10th Revision codes C00-C43, C45-C68) and treated at two Finnish university hospitals (2009-2019). Smoking status (never, former, and current) was extracted from medical narratives using a validated natural language processing (NLP) pipeline linked to nationwide mortality data. Overall survival (OS) and cancer-specific survival (CSS) were estimated using Kaplan–Meier and multivariable Cox hazard ratios (HRs) adjusted for age, sex, performance status, comorbidity, nodal status, and treatment intent. Results Among 62 893 patients, smoking status was available for 45 395 (72%). Five-year OS was 71% in never, 58% in former, and 49% in current smokers; HR reference, 1.48 [95% confidence interval (CI) 1.43-1.53], and 1.91 (95% CI 1.85-1.97), respectively. Corresponding HRs for CSS were 1.52 (95% CI 1.47-1.59) and 2.09 (95% CI 2.02-2.17). Across most cancer types, 5-year CSS was 4%-19% lower in current versus never smokers. Impaired survival among current smokers (OS: HR 1.15-3.96; CSS: HR 1.12-4.07) and intermediate outcomes in former smokers were observed. Associations persisted after adjustment, including in the curative-intent subgroup ( n = 36 936). Conclusions Current and former smoking are associated with impaired survival across multiple cancers, including after curative-intent treatment. These findings support systematic integration of smoking assessment and cessation into oncology care and demonstrate the utility of NLP for large-scale lifestyle outcome research.
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Heervä et al. (2026) studied this question.
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