Female Reproductive Factors, Gene Polymorphisms in the Estrogen Metabolism Pathway, and Risk of Lung Cancer in Chinese Women
Bibliographic record
Abstract
The authors examined relations between reproductive factors and 5 estrogen pathway gene polymorphisms (CYP17 rs743572, CYP19A1 rs10046, ERβ rs1256049, ERβ rs4986938, and COMT rs4680) among 702 Singapore Chinese female lung cancer cases and 1,578 hospital controls, of whom 433 cases (61.7%) and 1,375 controls (87.1%) were never smokers. Parity (per child, odds ratio (OR) = 0.92, 95% confidence interval (CI): 0.87, 0.97) and menstrual cycle length (for ≥30 days vs. <30 days, OR = 0.50, 95% CI: 0.32, 0.80) were inversely associated with lung cancer in never smokers, while age at first birth (for ages 21-25, 26-30, and ≥31 years vs. ≤20 years, ORs were 1.54, 2.17, and 1.30, respectively), age at menopause (for ages 49-51 and ≥52 years vs. ≤48 years, ORs were 1.37 and 1.59; P(trend) = 0.003), and reproductive period (for 31-33, 34-36, 37-39, and ≥40 years vs. ≤30 years, ORs were 1.06, 1.25, 1.45, and 1.47; P(trend) = 0.026) were positively associated. Among smokers, parity was inversely associated with lung cancer, but there was no association with other reproductive factors. The COMT rs4680 A allele was positively associated with lung cancer in never smokers (for G/A or A/A vs. G/G, OR = 1.46, 95% CI: 1.12, 1.90) but not in ever smokers. No associations were seen with other polymorphisms. These results support a risk-enhancing role of estrogens in lung carcinogenesis among never smokers.
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How this classification was reachedexpand
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".