Polymorphisms in <i>XPC</i> and <i>ERCC2</i> genes, smoking and breast cancer risk
Bibliographic record
Abstract
To evaluate the associations of breast cancer risk with polymorphisms in the XPC and XPD/ERCC2 DNA nucleotide excision repair genes, a case-control study nested within a prospective cohort of 14,274 women was conducted. Genotypes were characterized for 612 incident, invasive breast cancer cases and their 1:1 matched controls. The homozygous variant of a poly(AT) insertion/deletion polymorphism in intron 9 of the XPC gene (XPC-PAT+/+), was associated with breast cancer risk [odds ratio (OR) = 1.45, 95% confidence interval: 1.07-1.97], after adjustment for other breast cancer risk factors. The breast cancer risk associated with XPC-PAT+/+ did not differ by age at diagnosis. There was an indication of an interaction (p = 0.08) between the XPC-PAT+/+ genotype and cigarette smoking. Ever smokers with the XPC-PAT+/+ genotype were at elevated risk of breast cancer (OR = 1.56, CI: 0.95-2.58), but no differences were observed among never smokers. Analyses of the ERCC2 Lys751Gln polymorphism did not show an association with breast cancer risk, either overall or at younger ages. The results suggest that breast cancer risk is related to the XPC haplotype tagged by the XPC-PAT+/+ insertion-deletion polymorphism in intron 9. Further study of the XPC haplotypes and their interactions with smoking in relation to breast cancer risk is needed.
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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 | 0.002 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".