Abstract B25: Mammographic density and risk of breast cancer by body weight: A combined analysis of four case-control studies
Notice bibliographique
Résumé
Abstract Background. Breast density assessed from mammography is a strong predictor of breast cancer risk, but the strength of the association may vary with adiposity. To examine effect modification by adiposity, we combined data from four case-control studies on breast density that represented an ethnically diverse population with a wide variation in level of adiposity as measured by body mass index (BMI, kg/m2). Methods. We combined data from four case-control studies representing different locations: California, Hawaii and Minnesota in the United States, and Gifu in Japan. All studies included incident breast cancer cases diagnosed between 1994 and 2002 and matched controls representing the underlying case population. One mammographic image per subject was selected, specifically the mammogram at diagnosis for the studies from California, Minnesota, and Japan and the closest prediagnostic mammogram for Hawaii. Percent density was measured by one reader, who was blinded to case status, using a computer-assisted method. Self-reported anthropometric measures were used to classify women as normal, overweight, and obese according to ethnic-specific BMI cut points (<23, 23-27.4, and ≥27.5 for Asian women and <25, 25-29.9, and ≥30 for other ethnic groups). Logistic regression was used to estimate odds ratios (OR) and 95% confidence intervals (95% CI) and to evaluate interactions using the likelihood ratio while adjusting for potential confounders, including age and ethnicity. Heterogeneity across studies was marginally significant as assessed by examining density-by-study interaction (P = 0.09) and, therefore, we also adjusted for study-site. Results. The study included 1,699 cases and 2,422 controls of diverse ethnicity: 45% Caucasian, 40% Asian, 9% African-American, and 7% Other. Of these women, we classified 34% as overweight and19% as obese. Age-adjusted mean percent density was significantly greater for cases than for controls: 31.7% versus 28.9%, respectively (P < 0.001). BMI was inversely associated with breast density; the estimated age-adjusted mean percent density was 36.5%, 26.8%, and 19.3% for normal, overweight, and obese, respectively (Ptrend < 0.001). The overall OR for a 10% higher percent density was 1.15 (95% CI: 1.05, 1.18) with higher estimates in overweight (OR: 1.19, 95% CI: 1.09, 1.29) and obese (OR: 1.25, 95% CI: 1.11, 1.41) than normal BMI (OR: 1.11, 95% CI: 1.05, 1.18). The effect modification by BMI was statistically significant (Pinteraction = 0.01). Conclusions. Our findings confirm that the elevated risk of breast cancer associated with breast density differs by level of adiposity, with a higher risk for overweight and obese than normal BMI. Further research is needed to understand the underlying biological reasons for these noted differences in association by adiposity. Citation Information: Cancer Prev Res 2010;3(12 Suppl):B25.
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 | 0,026 | 0,044 |
| Méta-épidémiologie (sens strict) | 0,003 | 0,002 |
| Méta-épidémiologie (sens large) | 0,005 | 0,015 |
| Bibliométrie | 0,012 | 0,010 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,004 | 0,001 |
| Science ouverte | 0,002 | 0,002 |
| Intégrité de la recherche | 0,002 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 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 ».