Evidence map›Paper›PMID 42904091›Full record

ArticleESMO real world data and digital oncology2026

Smoking status and survival by cancer type and treatment intent in a population-based cohort with adjustment for major prognostic factors.

E Heervä, A Ellonen, S Kukkurainen, T Mikkola, K Savolainen, T Laitinen, K Mattila, H Blomster, H Minn, H Irjala and 3 more

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Article in ESMO real world data and digital oncology, 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

What it found

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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

13 authors.

E HeerväDepartment of Oncology, Turku University Hospital and University of Turku, Turku, Finland.
A EllonenDepartment of Oncology, Turku University Hospital and University of Turku, Turku, Finland.
S KukkurainenResearch Services, Tampere University Hospital, Tampere, Finland.
T MikkolaResearch Services, Tampere University Hospital, Tampere, Finland.
K SavolainenDepartment of Obstetrics and Gynaecology, Tampere University Hospital and FICAN Mid Cancer Centre, Tampere, Finland.
T LaitinenInstitute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland.
K MattilaDepartment of Oncology, Helsinki University Hospital and University of Helsinki, FICAN South Cancer Center, Helsinki, Finland.
H BlomsterDepartment of Otorhinolaryngology-Head and Neck Surgery, Tampere University Hospital, Tampere, Finland.
H MinnDepartment of Oncology, Turku University Hospital and University of Turku, Turku, Finland.
H IrjalaDepartment of Otorhinolaryngology-Head and Neck Surgery, University of Turku and Turku University Hospital, Turku, Finland.
A KarlssonDepartment of Medicine, University of Turku, Turku, Finland.
M BärlundDepartment of Oncology, Tampere University Hospital and University of Tampere, Wellbeing Services County of Pirkanmaa, Tampere, Finland.
P ÖsterlundDepartment of Oncology, Tampere University Hospital and University of Tampere, Wellbeing Services County of Pirkanmaa, Tampere, Finland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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 ( 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.

Indexed as

artificial intelligencebig datacancerpopulation-basedprognosissmoking

Identifiers

PMID42904091
PMCPMC13682021

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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.