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Enregistrement W2911452052 · doi:10.1158/1538-7755.disp17-b81

Abstract B81: Changing fertility factors affecting breast cancer in the Bahamas

2018· article· en· W2911452052 sur OpenAlexaff
Sophia George, Ana Sandoval Leon, Talia Donenberg, Raleigh Bulter, Darron Halliday, DuVaughn Curling, Theodore Turnquest, John Lunn, Mohammad R. Akbari, Steven A. Narod, Judith Hurley

Notice bibliographique

RevueCancer Epidemiology Biomarkers & Prevention · 2018
Typearticle
Langueen
DomaineMedicine
ThématiqueCancer Risks and Factors
Établissements canadiensWomen's College Hospital
Organismes subventionnairesnon disponible
Mots-clésBreast cancerMedicineOvarian cancerMenarcheGynecologyDemographyObstetricsEthnic groupCancerInternal medicine

Résumé

récupéré en direct d'OpenAlex

Abstract Introduction: There are many factors that affect breast and ovarian cancer incidence. Genetics, obesity, parity, age at menarche, age at first pregnancy, and family size are all determinants of breast and ovarian cancer risk and factors that differ between well-resourced countries and low- and middle-income countries (LMIC). These factors can be subject to rapid change. In addition, there are risks that are associated with the development of breast and ovarian cancer that are associated with race and ethnic group that are less well understood. The Caribbean is home to more than 20 million women, the majority of whom are of African ancestry. The demographics of the Caribbean basin in terms of finance, diet, and exposures are rapidly changing and these factors will, no doubt, be reflected in the rates of breast and ovarian cancer diagnosis. In this article, we propose to examine the changing factors that affect the development of breast and ovarian cancer in women with breast and ovarian cancer of Afro-Caribbean origin. Methods: This prospective study was approved by the University of Miami IRB and the Ministry of Health in the Bahamas. We recruited breast and ovarian cancer patients from public and private clinics in the Bahamas between September 2008 and January 2010. Women were eligible if they had been diagnosed with breast or ovarian cancer, and if at least one parent was born in the Bahamas. Data were analyzed from 250 women from 229 families. The cohort was divided into four groups depending on the year that they were born: <1950, 1950-1959, 1960-1969, or >1970. Data analysis was conducted using the c2 test or ANOVA with adjustment for clustered data. Results: Data analysis was conducted on the 250 patients, and the groups were broken down as follows: fifty-six patients were born before 1950, ninety-one were born between 1950-1959, seventy-one between 1960-1969, and thirty-two in or after 1970. The mean age of diagnosis of their first cancer decreased from 57 years (born before 1950) to 31 years (born in or after 1970, p<0.0001). Patients born before 1950 had more siblings (p=0.045), more pregnancies (p<0.0001), and more children (p<0.0001). They had their menarche at an older age (13.8 years vs to 12.7 years, p=0.028) and their first pregnancy at a younger age (21.6 years vs 24.8 years, p=0.021) when compared to the patients born in or after 1970. There was no difference in their body mass index or family history of breast and ovarian cancer. 3.6% of the women were diagnosed with ovarian cancer. At the time of enrollment to study, 21% of the cohort had a TAH-BSO. 59.4% of women born in the 1950s underwent a TAH-BSO. Multivariate analysis of women diagnosed with breast or ovarian cancer, born in the 1960s or 1970s, had a significant odds ratio of having a BRCA mutation, OR 2.88 (1.26, 6.57), p=0.012 and OR 4.06 (1.62, 10.36), p=0.003, respectively. Conclusions: The Bahamas has undergone a rapid change from a developing country fertility pattern in the 1950s and by 1970 to a developed country's fertility pattern, in one generation. These changes influence breast and ovarian cancer risk and are associated with younger age of onset of breast cancer. We documented that 2.8% of Bahamian women without breast or ovarian cancer who had a family history of breast cancer had a deleterious mutation in BRCA 1 or 2. 40% of the 1,857 unaffected women who were offered genetic testing had a family history; thus, the prevalence of these mutations in the population is approximately 1% overall. However, the incidence of ovarian cancer is low. The unintended consequence of TAH-BSO for birth control and menorrhagia is a decrease in expected rates of both breast cancer and ovarian cancer. Citation Format: Sophia HL George, Ana Sandoval Leon, Talia Donenberg, Raleigh Bulter, Darron Halliday, DuVaughn Curling, Theodore Turnquest, John Lunn, Mohammad R. Akbari, Steven Narod, Judith Hurley. Changing fertility factors affecting breast cancer in the Bahamas [abstract]. In: Proceedings of the Tenth AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2017 Sep 25-28; Atlanta, GA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2018;27(7 Suppl):Abstract nr B81.

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)0,003
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 enseignants0,057
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0030,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0000,001
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
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 Opus0,075
Tête enseignante GPT0,405
Écart entre enseignants0,330 · 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
Publié2018
Routes d'admission1
Résumé présentoui

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