Abstract A126: Characteristics of menstruation and pregnancy and the risk of lung cancer in women
Notice bibliographique
Résumé
Abstract A126 Differences between men and women in the descriptive epidemiology of lung cancer suggest that hormonal factors may influence lung carcinogenesis in women. Few epidemiological studies have been conducted on hormone-related variables and lung cancer risk and the findings have not been consistent. We investigated the association between characteristics of menstruation and pregnancy in relation to lung cancer risk in a population-based case-control study carried out in Montreal, Canada. Between January 1996 and December 1997, newly diagnosed lung cancer cases were identified and recruited from 18 Montreal-area hospitals that together diagnose 98% of cases that occur among Montreal residents. Population controls from Montreal were identified from the provincial electoral lists and were randomly selected, stratified to the expected age and sex distribution of cases. The participation rate was 81.7% among cases and 69.4% among controls. Among cases, interviews were conducted an average of 12.1 months after diagnosis. For each variable, odds ratios (OR) and 95% confidence intervals (CI) were estimated using unconditional logistic regression modeling. Each hormone-related variable was modeled separately. Associations were also examined according to age at diagnosis and level of smoking and by lung cancer histology. All statistical tests were two-sided. Among 422 women with lung cancer and 577 controls, we observed that most characteristics of menstruation and pregnancy were not associated with the risk of lung cancer. However, an increased lung cancer risk was observed for women who had had surgical menopause with bilateral oophorectomy compared to women who had had a natural menopause (OR=1.95, 95% CI: 1.29-3.17). These results did not vary by age at diagnosis or level of smoking, and they were similar for different histological types. Our results suggest that hormonal factors, related to surgical menopause and/or ovary removal, may play a role in the risk of lung cancer. Further studies are needed to confirm these findings, and to assess the possible contribution of hormone replacement therapy. Citation Information: Cancer Prev Res 2008;1(7 Suppl):A126.
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 enseignantsNi 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.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 tête enseignante, 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 ».