Performance of 8 Smoking Metrics for Modeling Survival in Head and Neck Squamous Cell Carcinoma
Notice bibliographique
Résumé
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.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,011 | 0,021 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,002 |
| Bibliométrie | 0,002 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».