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Enregistrement W2345850213 · doi:10.1158/1940-6215.prev-14-b15

Abstract B15: Second-hand smoke (SHS) and smoking cessation in non-tobacco related cancers

2015· article· en· W2345850213 sur OpenAlexaffabout
Lawson Eng, Xin Qiu, Jie Su, M. Catherine Brown, Margaret Irwin, Dan Pringle, Hiten Naik, Chongya Niu, Mary Mahler, Henrique Hon, Kyoko Tiessen, Rebecca Charow, Henry Thai, Valerie Ho, Vivien Pat, Lindsay Herzog, Anthea Ho, Jennifer M. Jones, Doris Howell, David P. Goldstein, Meredith Giuliani, Wei Xu, Peter Selby, Geoffrey Liu

Notice bibliographique

RevueCancer Prevention Research · 2015
Typearticle
Langueen
DomaineMedicine
ThématiqueCancer Risks and Factors
Établissements canadiensCentre for Addiction and Mental HealthPrincess Margaret Cancer Centre
Organismes subventionnairesnon disponible
Mots-clésMedicineSmoking cessationCancerLogistic regressionLung cancerInternal medicineOdds ratioHazard ratioTobacco smokeEnvironmental healthPathologyConfidence interval

Résumé

récupéré en direct d'OpenAlex

Abstract Introduction: Continued smoking after a diagnosis of cancer has been found to lead to poorer treatment response, reduced survival and quality of life and increased risk of second primary cancers. We have previously demonstrated that SHS (exposure at home, with spouses and peers) is a significant barrier to smoking cessation in tobacco-related (lung and head and neck) cancers with adjust odds ratios of 6-9 (PMID: 24419133, 23765604) for quitting 1 year after diagnosis and quitting at any time after diagnosis; relationships stronger than in non-cancer populations. Here, we examined whether this relationship exists in cancers that are not traditionally associated with smoking. Patients and Methods: Cancer survivors from a single tertiary cancer centre, Princess Margaret Cancer Centre (Toronto, Canada) completed a one-time cross-sectional questionnaire assessing their socio-demographics, functional status, smoking history and SHS exposure. Clinico-pathological variables were obtained through review of patient charts. Multivariate logistic regression and Cox-proportional hazard models evaluated the association of SHS with smoking cessation at 1 year after diagnosis and any time after diagnosis, and time-to-quitting respectively, adjusted for significant co-variates. Results: A total of 1011 non-tobacco related cancer survivors were surveyed between 2012 and 2014: 19% breast, 15% gastrointestinal, 16% genitourinary, 12% gynecological, 23% hematologic, 15% other. Median follow-up time after diagnosis was 26 months. Among the 162 patients currently smoking at diagnosis, 35% quit 1 year after diagnosis and 48% quit at any time after diagnosis. None of the 306 ex-smokers and 543 never smokers (re-)started smoking after diagnosis. Home exposure to SHS was found to be strongly associated with reduced smoking cessation in cancer patients at any time after diagnosis (aOR=4.28, 95% CI (1.56-11.78), P=4.8E-3), while there was a less strong and non-significant trend for home exposure to SHS and reduced smoking cessation at 1 year after diagnosis (aOR=2.56, 95% CI (0.91-7.22), P=0.08)). Time-to-quitting analysis for home exposure to SHS were consistent with these results (aHR=2.76, 95% CI (1.15-6.59), P=0.02)). Unlike lung and head and neck cancer patients, spousal and peer smoking were not found significantly associated with smoking cessation at either time-point (P>0.05). Kaplan-Meier analysis found that 72% of patients who quit, did so within 1 year of their cancer diagnosis. When comparing factors between patients quitting one year after diagnosis versus quitting more than one year after diagnosis, those quitting at one year were more likely older (P<0.05) and have received surgery as part of their cancer care (P=0.06). Conclusions: Home exposure to SHS is a significant barrier to quitting smoking after a diagnosis of cancer in both tobacco-related and non-tobacco related cancers; while spousal and peer smoking were not found significantly associated with smoking cessation in non-tobacco related cancers. Unlike in tobacco-related cancers, home exposure to SHS had a weaker association with quitting at 1 year after diagnosis than quitting at any time after diagnosis; suggesting the effect of the “teachable moment” with SHS and cancer may not be as strong in these cancers. Survivorship programs focusing on secondary prevention and smoking cessation in cancer patients should focus on incorporating SHS exposure. Citation Format: Lawson Eng, Xin Qiu, Jie Su, M Catherine Brown, Margaret Irwin, Dan Pringle, Hiten Naik, Chongya Niu, Mary Mahler, Henrique Hon, Kyoko Tiessen, Rebecca Charow, Henry Thai, Valerie Ho, Vivien Pat, Lindsay Herzog, Anthea Ho, Jennifer M. Jones, Doris Howell, David P. Goldstein, Meredith E. Giuliani, Wei Xu, Peter Selby, Geoffrey Liu. Second-hand smoke (SHS) and smoking cessation in non-tobacco related cancers. [abstract]. In: Proceedings of the Thirteenth Annual AACR International Conference on Frontiers in Cancer Prevention Research; 2014 Sep 27-Oct 1; New Orleans, LA. Philadelphia (PA): AACR; Can Prev Res 2015;8(10 Suppl): Abstract nr B15.

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 distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,002
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesCharge utile insuffisante (le modèle a refusé de juger)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,167
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0020,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,001
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,001
Charge utile insuffisante (le modèle a refusé de juger)0,0010,000

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.

Tête enseignante Opus0,138
Tête enseignante GPT0,447
Écart entre enseignants0,309 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2015
Routes d'admission2
Résumé présentoui

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