Abstract P3-08-06: Demographics of breast cancer in a cohort of Afro-Caribbean women
Bibliographic record
Abstract
Abstract Objectives: In Latin America and the Caribbean, non – communicable chronic diseases are now the leading cause of premature mortality. The incidence of cancer has increased in the region as a result of population aging and growth but also as more people adopt lifestyle choices like smoking, physical inactivity, and ‘‘westernized’’ diets. In women, fertility factors such as decreased parity, earlier onset of menses and later age at time of first pregnancy are known epidemiologically to increase incidence of hereditary and sporadic breast cancer. Recently there has also been a strong link to a genetic etiology of the breast and ovarian cancer in the Bahamas (27% in unselected breast cancer cases). A study was designed to address the prevalence and spectrum of BRCA1 and BRCA2 mutations in the Afro-Caribbean population. Methods: Demographic and clinical pathologic data was collected from 347 women of Afro-Caribbean decent. The cohort included women with breast cancer from the following countries: the Cayman Islands, Jamaica, Barbados, Dominica, Trinidad and Haiti. Summary statistics and t-tests and ANOVA were used to analyze population characteristics. A Bahamian mutation panel was created and detailed analyses of samples are ongoing. Results: The mean age of onset in the cohort is 48.1 yrs with a mean BMI of 27.7. 70% of breast cancer cases ER+ (n=241 informative cases) and in Jamaica 27% (n=105) of breast cancer cases were Her2+. 67.8% cases were diagnosed at stages II/III (n=90). TAH-BSO delayed invasive breast cancer from 48 to 53 years, p=0.005. Parity was a statistically significant factor (p<0.0001), which delayed age of onset by 8 yrs. Additionally, pregnancy alone delayed age of onset (p<0.005) also by 8 yrs in our cohort (n=379). Only three women out of 347 were found to have a mutation. Summary demographics of Caribbean women with breast cancerCountryNo. of ParticipantsMean age at diagnosis (yrs)ER+Her2+BRCA1/2 +BMICayman Islands6651.429/443/431/2730.3Barbados8946.652/739/734/8727.5Dominica6052.29/132/70/4628.7Jamaica13748.669/10528/105128.7Trinidad and Tobago645.54/61/51/527.4Haiti3448.5NANANA24.9 Reproductive Characteristics of Caribbean women with breast cancerNMean Agep-valueTAH-BSOPerformed71530.005Not Performed30448ParityNulliparous6042⟨ 0.0001Multiparous31950PregnancyNone4843⟨ 0.0001More than 133150 Conclusions: This population-based study provides an insight into pattern of risk factors – both genetic and environmental of breast cancer incidence and subtype across the Caribbean. In conclusion 1) genetic causes of breast cancer appear rare outside of the Bahamas, 2) fertility factors appear important in the development of breast cancer, 3) TAH-BSO is common as both a form of contraception and because of the high incidence of fibroids in the Caribbean and it may be protective, 4) BMI may impact on breast cancer development and 5) screening mammography is rare and the vast majority of mammography performed is diagnostic in nature. Citation Format: Sophia HL George, Talia Donenberg, Mohammed Akbari, Cheryl Alexis, Gillian Wharfe, Sook Yin, Hedda Dyer, Theodore Turnquest, Vincent DeGennaro, Steven Narod, Judith Hurley. Demographics of breast cancer in a cohort of Afro-Caribbean women [abstract]. In: Proceedings of the Thirty-Seventh Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2014 Dec 9-13; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2015;75(9 Suppl):Abstract nr P3-08-06.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".