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

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

2018· article· en· W2911452052 on 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

Bibliographic record

VenueCancer Epidemiology Biomarkers & Prevention · 2018
Typearticle
Languageen
FieldMedicine
TopicCancer Risks and Factors
Canadian institutionsWomen's College Hospital
Fundersnot available
KeywordsBreast cancerMedicineOvarian cancerMenarcheGynecologyDemographyObstetricsEthnic groupCancerInternal medicine

Abstract

fetched live from 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.

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How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.057
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.075
GPT teacher head0.405
Teacher spread0.330 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2018
Admission routes1
Has abstractyes

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