BRCA1 mutations and prostate cancer in Poland
Why this work is in the frame
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Bibliographic record
Abstract
Evidence to date that BRCA1 mutation carriers are at an increased risk of prostate cancer is mixed - both positive and negative studies have been published. To establish whether or not inherited variation in BRCA1 influences prostate cancer risk we genotyped 1793 men with prostate cancer in Poland and 4570 controls for three founder mutations (C61G, 4153delA and 5382insC). A BRCA1 mutation was present in 0.45% of the cases and 0.48% of the controls (odds ratio=0.9; P=1.0). The odds ratios varied substantially by mutation. The 5382insC mutation is the most common of the three founder mutations. It was detected only in one case (0.06%), whereas it was seen in 0.37% of controls (P=0.06). In contrast, the 4153delA was more common in prostate cancer cases (0.22%) than in controls (0.04%) (odds ratio=5.1; 95% confidence interval: 0.9-27.9; P=0.1). The C61G mutation was also found in excess in cases (0.17%) compared with controls (0.07%) (odds ratio=2.6; 95% confidence interval: 0.5-12.7; P=0.5). Eight men with prostate cancer carried a mutation. Only one of these carried the 5382insC mutation, compared with 17 of 22 individuals with mutations in the control population (P=0.003). These data suggest that the 5382insC mutation is unlikely to be pathogenic for prostate cancer in the Polish population. The presence of one of the other alleles was associated with an increased risk for prostate cancer (odds ratio=3.6; 95% confidence interval: 1.1-11.3; P=0.045); in particular for familial prostate cancer (odds ratio=12; 95% confidence interval: 2.9-51; P=0.0004). We consider that the risk of prostate cancer in BRCA1 carriers varies with the position of the mutation.
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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 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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