Polymorphisms in nucleotide excision repair genes and risk of multiple primary melanoma: the Genes Environment and Melanoma Study
Bibliographic record
Abstract
Polymorphisms in six genes involved in nucleotide excision repair of DNA were examined in a large population-based case-control study of melanoma. Genotyping was conducted for 2485 patients with a single primary melanoma (controls) and 1238 patients with second or higher order primary melanomas (cases). Patients were ascertained from nine geographic regions in Australia, Canada, Italy and the United States. Positive associations were observed for XPD 312 Asn/Asn versus Asp/Asp [odds ratio (OR) = 1.5, 95% confidence interval (CI) 1.2-1.9] and XPD 751 Gln/Gln versus Lys/Lys (OR = 1.4, 95% CI 1.1-1.7) genotypes and melanoma. The combined XPD Asn (A) 312 + Gln (C) 751 haplotype was significantly more frequent in cases (32%) compared with controls (29%) (P = 0.003) and risk of melanoma increased significantly with one and two copies of the haplotype (ORs 1.2, 95% CI 1.0-1.4, and 1.6, 95% CI 1.2-2.0, trend P = 0.002). No significant associations were observed for HR23B codon 249, XPG codon 1104, XPC codon 939, XPF codon 415, XPF nt 2063, ERCC6 codon 1213 or ERCC6 codon 1230. ORs for XPD and XPC genotypes were stronger for melanoma diagnosed at an early age, but tests for interaction were not statistically significant. The results provide further evidence for a role of XPD in the etiology of melanoma.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 | 0.001 |
| 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".