Breast Cancer Risk in Women from Ghana Carrying Rare Germline Pathogenic Mutations
Bibliographic record
Abstract
BACKGROUND: Risk estimates for women carrying germline mutations in breast cancer susceptibility genes are mainly based on studies of European ancestry women. METHODS: We investigated associations between pathogenic variants (PV) in 34 genes with breast cancer risk in 871 cases [307 estrogen receptor (ER)-positive, 321 ER-negative, and 243 ER-unknown] and 1,563 controls in the Ghana Breast Health Study (GBHS), and estimated lifetime risk for carriers. We compared results with those for European, Asian, and African American ancestry women. RESULTS: The frequency of PV in GBHS for nine breast cancer genes was 8.38% in cases and 1.22% in controls. Relative risk estimates for overall breast cancer were: (OR, 13.70; 95% confidence interval (CI), 4.03-46.51) for BRCA1, (OR, 7.02; 95% CI, 3.17-15.54) for BRCA2, (OR, 17.25; 95% CI, 2.15-138.13) for PALB2, 5 cases and no controls carried TP53 PVs, and 2.10, (0.72-6.14) for moderate-risk genes combined (ATM, BARD1, CHEK2, RAD51C, RAD52D). These estimates were similar to those previously reported in other populations and were modified by ER status. No other genes evaluated had mutations associated at P < 0.05 with overall risk. The estimated lifetime risks for mutation carriers in BRCA1, BRCA2, and PALB2 and moderate-risk genes were 18.4%, 9.8%, 22.4%, and 3.1%, respectively, markedly lower than in Western populations with higher baseline risks. CONCLUSIONS: We confirmed associations between PV and breast cancer risk in Ghanaian women and provide absolute risk estimates that could inform counseling in Ghana and other West African countries. IMPACT: These findings have direct relevance for breast cancer genetic counseling for women in West Africa.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".