The Prevalence of BRCA2 Mutations in Familial Pancreatic Cancer
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it