Sex differences in bladder cancer outcomes among smokers with advanced bladder cancer
Notice bibliographique
Résumé
Study Type – Aetiology (individual cohort) Level of Evidence 2b What's known on the subject? and What does the study add? Smoking is well described among the most important risk factors for bladder cancer. It is also known that higher quantity of tobacco exposure is associated with higher bladder cancer risk and that smoking cessation is known to be associated with lower risk of bladder cancer. Furthermore, among patients with non‐muscle invasive bladder cancer, smoking cessation decreases the risk of tumour recurrence. On the other hand, the effect of smoking on tumour stages at presentation and especially on prognosis is not well studied. The current study describes the presentation and outcome of 564 patients (64% smokers, 36% non‐smokers) treated with radical cystectomy. Patients with smoking history have more advanced outcome at the time of radical surgery and significantly worse outcome after surgery when compared to non‐smokers, although the effect of smoking was not significant when survival was studied in multivariable analysis including classic prognostic parameters such as tumour grade, stage and adjuvant chemotherapy. Finally, there was a surprising finding that history of smoking affected outcome among male patients but such effect was not noted among female patients. OBJECTIVE • To study the effect of smoking on bladder cancer presentation and outcome in a large cystectomy population. PATIENTS AND METHODS • A database including 546 patients from the University Health Network (Toronto, Canada) and Turku University Hospital (Turku, Finland) was studied. • In addition to the association of smoking with clinicopathological parameters, the effect of smoking on survival was analyzed. • Categorical data were analyzed by the chi‐squared test and numerical data were analyzed by Student's t ‐test. • The Kaplan–Meier method, log‐rank test and a proportional hazards model were used to estimate the effect of smoking on survival. RESULTS • In total, 352 patients (64%) were smokers and 194 (36%) were non‐smokers. • Smokers had more frequently advanced tumours and nodal metastasis. • The 10‐year disease‐specific survival (DSS) was 52% vs 66% for smokers and non‐smokers, respectively ( P = 0.039). • Smokers also had significantly worse overall survival (10‐year overall survival 37% vs 62%; P = 0.015). • Smoking affected significant DSS among men ( P = 0.012), although no effect was observed among women. • In a univariate model smoking was associated with a hazard ratio (HR) of 1.4 (95% confidence interval, CI, 1.0–1.9) for bladder cancer specific mortality and 1.4 (95% CI, 1.1–1.8) for overall mortality. • In a multivariate model, smoking did not impact on DSS (HR, 1.1; 95% CI, 0.8–1.6; P = 0.41). • In addition to advanced stage and nodal metastasis, female sex was an independent risk factor for DSS (HR, 1.6; 95% CI, 1.1–2.3; P = 0.007). CONCLUSIONS • Smokers appear to have worse outcomes after radical cystectomy for bladder cancer; however, it does not appear to be an independent prognostic factor for survival. • Smoking affected survival only among men. • Women had poorer survival but smoking was not a contributing factor to this.
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 | 0,001 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,002 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 ».