Prevalence of <i><scp>BRCA1</scp></i> and <i><scp>BRCA2</scp></i> mutations in unselected breast cancer patients from Peru
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
The prevalence of BRCA1 and BRCA2 mutations among breast cancer patients in Peru has not yet been explored. We enrolled 266 women with breast cancer from a National cancer hospital in Lima, Peru, unselected for age or family history. DNA was screened with a panel of 114 recurrent Hispanic BRCA mutations (HISPANEL). Among the 266 cases, 13 deleterious mutations were identified (11 in BRCA1 and 2 in BRCA2), representing 5% of the total. The average age of breast cancer in the mutation-positive cases was 44 years. BRCA1 185delAG represented 7 of 11 mutations in BRCA1. Other mutations detected in BRCA1 included: two 2080delA, one 943ins10, and one 3878delTA. The BRCA2 3036del4 mutation was seen in two patients. Given the relatively low cost of the HISPANEL test, one should consider offering this test to all Peruvian women with breast or ovarian cancer.
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 | 0.000 | 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