Performance of 8 Smoking Metrics for Modeling Survival in Head and Neck Squamous Cell Carcinoma
Language English Country United States Media print
Document type Journal Article, Multicenter Study
Grant support
001
World Health Organization - International
PubMed
39976935
PubMed Central
PMC11843462
DOI
10.1001/jamaoto.2024.5392
PII: 2830404
Knihovny.cz E-resources
- MeSH
- Squamous Cell Carcinoma of Head and Neck * mortality MeSH
- Cigarette Smoking * adverse effects MeSH
- Smoking * adverse effects MeSH
- Middle Aged MeSH
- Humans MeSH
- Survival Rate MeSH
- Head and Neck Neoplasms * mortality MeSH
- Proportional Hazards Models MeSH
- Retrospective Studies MeSH
- Risk Factors MeSH
- Aged MeSH
- Check Tag
- Middle Aged MeSH
- Humans MeSH
- Male MeSH
- Aged MeSH
- Female MeSH
- Publication type
- Journal Article MeSH
- Multicenter Study MeSH
IMPORTANCE: Cigarette smoking is a strong risk factor for mortality in patients diagnosed with head and neck squamous cell carcinoma (HNSCC). However, little evidence supports which smoking metric best models the association between smoking and survival in HNSCC. OBJECTIVE: To determine which smoking metric best models a linear association between smoking exposure and overall survival (OS) in patients with HNSCC. DESIGN, SETTING, AND PARTICIPANTS: A retrospective multicenter cohort study of 6 clinical epidemiological studies was performed. Five were part of the Human Papillomavirus, Oral and Oropharyngeal Cancer Genomic Research (VOYAGER) consortium. Participants included patients 18 years and older with pathologically confirmed HNSCC. Data were collected from January 2002 to December 2019, and data were analyzed between January 2022 to November 2024. MAIN OUTCOMES AND MEASURES: The primary outcome was OS. The performance of 8 smoking metrics, including pack-years, duration, and log cig-years (calculated as log10[cigarettes smoked per day + 1] × number of years smoked) for modeling OS were compared. Metric performance was measured by the strength of association in Cox proportional hazard models, linearity based on P for linear trend, Akaike information criterion (AIC; lower value indicates better model fit), and visual assessment of spline curves. Secondary outcomes included modeling OS in clinicodemographic subgroups and HNSCC anatomic subsites. Exploratory outcomes included cancer-specific survival and noncancer survival. RESULTS: In total, 8875 patients with HNSCC (2114 [24%] female; median [IQR] age, 61 [54-69] years) were included. Of 8 smoking metrics evaluated, smoking duration (adjusted hazard ratio [aHR], 1.11 [95% CI, 1.03-1.19]) and log cig-years (aHR, 1.11 [95% CI, 1.04-1.18]) had the highest aHRs; both had a statistically significant linear association with OS. Log cig-years had the lowest AIC linear value and the most visually linear spline curve when modeling OS. Duration and log cig-years outperformed pack-years for modeling OS regardless of age, smoking status, and cancer stage. Both performed well in lip and oral cavity, laryngeal (only duration was significant), and human papillomavirus-negative oropharyngeal subsites. In an exploratory analysis, duration had the highest aHR (1.15 [95% CI, 1.02-1.29]), and log cig-years had the lowest AIC linear value when modeling noncancer survival. CONCLUSIONS AND RELEVANCE: In this cohort study, smoking duration and log cig-years best modeled a linear relationship with OS for patients with HNSCC. Both metrics maintained robust performance within specific clinicodemographic subgroups and anatomic subsites. Although most HNSCC survival models control for smoking exposure using smoking status or pack-years, duration and log cig-years may be superior metrics to account for the effects of smoking on survival.
Bristol Dental Hospital and School University of Bristol Bristol United Kingdom
Cancer Epidemiology Unit Department of Medical Sciences University of Turin Turin Italy
Catalan Institute of Oncology Barcelona Spain
Catalan Institute of Oncology Bellvitge Biomedical Research Institute Barcelona Spain
Centro de Investigación Biomédica en Red de Epidemiología y Salud Pública Madrid Spain
Department of Medicine University of Toronto Toronto Ontario Canada
Department of Research Cancer Registry of Norway Norwegian Institute of Public Health Oslo Norway
Division of Infections and Cancer Epidemiology German Cancer Research Center Heidelberg Germany
Division of Medical Oncology Princess Margaret Cancer Centre Toronto Ontario Canada
Epidemiology Dalla Lana School of Public Health Toronto Ontario Canada
Health Sciences North Research Institute Sudbury Ontario Canada
International Agency for Research on Cancer Lyon France
Northern Ontario School of Medicine University Sudbury Ontario Canada
School of Dental Science Trinity College Dublin Dublin Ireland
School of Medicine Dentistry and Nursing University of Glasgow Scotland United Kingdom
School of Medicine National and Kapodistrian University of Athens Athens Greece
School of Public Health University of West Attica Athens Greece
Unit of Cancer Epidemiology Centro di Riferimento Oncologico di Aviano IRCCS Aviano Italy
University Bremen Bremen Germany
University of Padova Padova Italy
University of Tennessee Health Science Center Center for Cancer Research Memphis
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