Risk factors for breast cancer in postmenopausal Caucasian and Chinese women.
Notice bibliographique
Résumé
B177 Background. Striking differences exist between countries in the incidence of breast cancer. The causes of these differences are unknown, but because incidence rates change in migrants, they are thought to be due to environmental rather than genetic differences. The goal of this research is to identify factors responsible for international differences in breast cancer risk. Methods . We have recruited Caucasian women, Chinese migrants to Canada who had lived in the West for less than 10 years, and women of Chinese ancestry who were born in the West, or who migrated to the West before age 21. All subjects were postmenopausal and aged 50 years or more. We obtained information on epidemiological risk factors by interview, and measured anthropometric characteristics. Results. Average length of residence in the West was 61 years for Caucasians (N=413), 62 years for women of Chinese ancestry born in the West (N=63), 40 years for Chinese who migrated early in life (N=153), and 7 years for recent Chinese migrants (N=421). Compared to Caucasians, recent Chinese migrants, weighed on average 14 kg less, and were 6 cms shorter. Recent migrants had menarche 1 year later than Caucasians, had menopause 0.6 year earlier, and were more often parous. Use of hormone replacement therapy was reported by 28% of recent Chinese migrants and 49% of Caucasians. 8% of recent migrants had at least one first degree relative with breast cancer, compared to 17% of Caucasians. 3% of recent migrants and 63% of Caucasians reported to have alcohol consumption at least once per week for 6 months or longer. 2% of recent migrants had smoked at least 1 cigarette per day for 3 months or longer, compared to 48% of Caucasians. Women of Chinese ancestry born in the West and early Chinese migrants had values for most of these variables that were intermediate between those of Caucasians and recent Chinese migrants. Conclusions. The differences observed between the 4 groups in this study strongly suggest that differences in risk of breast cancer between them are, at least in part, the result of differences in exposure to several known risk factors for breast cancer, and that levels of these risk factors are influenced by environmental factors.
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) | 0,001 | 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 ».