The Prevalence of BRCA2 Mutations in Familial Pancreatic Cancer
Bibliographic record
Abstract
Mutations in the BRCA2 gene have been implicated in pancreatic cancer susceptibility through studies of high-risk breast and ovarian cancer families. To determine the contribution of mutations in BRCA2 to familial pancreatic cancer, we screened affected probands from 151 high-risk families identified through pancreatic cancer clinics for germ-line BRCA2 mutations. Of these families, 118 had two or more first- and second-degree relatives with pancreatic cancer, and an additional 33 had two or more affected second-degree relatives. The average age of onset for pancreatic cancer was 62.8 years. Five BRCA2 truncating mutations were identified, three in families with two or more first- and second-degree relatives with pancreatic cancer. Three of the families with mutations had a history of breast cancer but not ovarian cancer. Four of five families with mutations were identified through probands with early-onset (<55 years) pancreatic cancer. The results of this study were combined with those from a BRCA2 mutation study of 29 other families from the same Johns Hopkins University National Familial Pancreatic Tumor Registry to estimate the frequency of BRCA2 mutations. A total of 10 carriers from 180 families were identified, suggesting that BRCA2 mutations account for 6% of moderate and high-risk pancreatic cancer families.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".