Risk of Pancreatic Cancer in Breast Cancer Families from the Breast Cancer Family Registry
Bibliographic record
Abstract
BACKGROUND: Increased risk of pancreatic cancer has been reported in breast cancer families carrying BRCA1and BRCA2 mutations; however, pancreatic cancer risk in mutation-negative (BRCAX) families has not been explored to date. The aim of this study was to estimate pancreatic cancer risk in high-risk breast cancer families according to the BRCA mutation status. METHODS: A retrospective cohort analysis was applied to estimate standardized incidence ratios (SIR) for pancreatic cancer. A total of 5,799 families with ≥1 breast cancer case tested for mutations in BRCA1 and/or BRCA2 were eligible. Families were divided into four classes: BRCA1, BRCA2, BRCAX with ≥2 breast cancer diagnosed before age 50 (class 3), and the remaining BRCAX families (class 4). RESULTS: BRCA1 mutation carriers were at increased risk of pancreatic cancer [SIR = 4.11; 95% confidence interval (CI), 2.94-5.76] as were BRCA2 mutation carriers (SIR = 5.79; 95% CI, 4.28-7.84). BRCAX family members were also at increased pancreatic cancer risk, which did not appear to vary by number of members with early-onset breast cancer (SIR = 1.31; 95% CI, 1.06-1.63 for class 3 and SIR = 1.30; 95% CI, 1.13-1.49 for class 4). CONCLUSIONS: Germline mutations in BRCA1 and BRCA2 are associated with an increased risk of pancreatic cancer. Members of BRCAX families are also at increased risk of pancreatic cancer, pointing to the existence of other genetic factors that increase the risk of both pancreatic cancer and breast cancer. IMPACT: This study clarifies the relationship between familial breast cancer and pancreatic cancer. Given its high mortality, pancreatic cancer should be included in risk assessment in familial breast cancer counseling.
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 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 | 0.001 | 0.004 |
| 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".