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Record W2321635862 · doi:10.1158/1055-9965.disp-11-a71

Abstract A71: BRCA mutations and surgical decision making in a sample of young black women with invasive breast cancer

2011· article· en· W2321635862 on OpenAlexaff
Patrice Fleming, Susan T. Vadaparampil, Devon Bonner, Álvaro N.A. Monteiro, Lisa Kessler, Robert E. Royer, Steven A. Narod, Tuya Pal

Bibliographic record

VenueCancer Epidemiology Biomarkers & Prevention · 2011
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBRCA gene mutations in cancer
Canadian institutionsWomen's College Hospital
Fundersnot available
KeywordsMedicineBreast cancerBRCA mutationGenetic testingMastectomyFamily historyCancerGenetic counselingGynecologyCohortReferralOncologyObstetricsInternal medicineFamily medicineGenetics

Abstract

fetched live from OpenAlex

Abstract Background: On average, Black women develop breast cancer ten years earlier than White women and are more likely to die from the disease. Early onset breast cancer is a hallmark feature of the BRCA1 and BRCA2 (BRCA) gene mutations and may contribute to a portion of breast cancers in Black women. Widespread availability of genetic testing for hereditary breast cancer has resulted in an increasing number of women considering their BRCA test results prior to surgical treatment decisions for their breast cancer surgery (e.g., consideration of a risk-reducing bilateral mastectomy, contralateral prophylactic mastectomy). However, little is known about use of BRCA testing prior to definitive surgery specifically among Black women. The purpose of this abstract is to describe baseline utilization of BRCA testing in Black breast cancer patients prior to surgery and to document the prevalence of BRCA mutations in a cohort of Black women with early onset breast cancer. Methods: Black women diagnosed with invasive breast cancer ≤ age 50 between the years of 2005 and 2006 were recruited through the Florida Cancer Registry utilizing state-mandated recruitment methods. Participants completed genetic counseling and a comprehensive risk factor questionnaire including 7 items specific to referral and uptake of genetics clinical services. Biological specimens (either blood or saliva) were collected, and BRCA testing was performed. Results: Of the 209 eligible cases, 48 women consented to study participation. Of the 46 women with usable biological specimens: the average age of diagnosis was 42.8 ±6.14 and 50% (n=23) reported a positive family history of breast cancer (i.e., ≥ 1 first and/or second-degree relative with breast cancer). A previous BRCA test was reported by 30.4% (n=14) of those completing the study with only 2 participants (4.3%) receiving a genetic test result prior to making a breast surgery decision. Seven women (15.2 %) chose a bilateral mastectomy, 4 of which were risk reducing. No association was observed between family history and the type of breast surgery elected. Mutations in the BRCA genes were identified in three participants (including 1 in BRCA1 and 2 in BRCA2). In 16 additional participants, there were a total of 28 variants of uncertain significance (VUS) identified. Conclusions: Our results suggest that few Black women utilized genetic test results and/or family history to make surgical decisions for their breast cancer treatment despite data documenting similar BRCA prevalence rates in Black women with early onset breast cancers as those previously reported in White women. These findings highlight an important health disparity in access to and utilization of genetics services among Black women with breast cancer. Citation Information: Cancer Epidemiol Biomarkers Prev 2011;20(10 Suppl):A71.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.017
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.037
GPT teacher head0.339
Teacher spread0.302 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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".

Quick stats

Citations0
Published2011
Admission routes1
Has abstractyes

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