Original Contribution Cigarette Smoking, Genetic Variants in Carcinogen-metabolizing Enzymes, and
Bibliographic record
Abstract
The risk of colorectal cancer associated with smoking is unclear and may be influenced by genetic variation in enzymes that metabolize cigarette carcinogens. The authors examined the colorectal cancer risk associated with smoking and 26 variants in carcinogen metabolism genes in 1,174 colorectal cancer cases and 1,293 population-based controls recruited in Canada by the Ontario Familial Colorectal Cancer Registry from 1997 to 2001. Adjusted odds ratios were calculated by multivariable logistic regression. Smoking for>27 years was associated with a statistically significant increased colorectal cancer risk (adjusted odds ratio (AOR) 1.25, 95 % confidence interval (CI): 1.02, 1.53) in all subjects. Colorectal cancer risk associated with smoking was higher in males for smoking status, duration, and intensity. The CYP1A1-3801-CC (AOR 0.47, 95 % CI: 0.23, 0.94) and CYP2C9-430-CT (AOR 0.82, 95 % CI: 0.68, 0.99) genotypes were associated with decreased risk, and the GSTM1-K173N-CG (AOR 1.99, 95 % CI: 1.21, 3.25) genotype was associated with an increased risk of colorectal cancer. Statistical interactions between smoking and genetic variants were assessed by comparing logistic regression models with and without a multiplicative interaction term. Significant interactions were observed between smoking status and SULT1A1-638 (P 0.02), NAT2-857 (P 0.01), and CYP1B1-4390 (P 0.04) variants and between smoking duration and NAT1-1088 (P 0.02), SULT1A1-638 (P 0.04), and NAT1-acetylator (P 0.03) status. These findings support the hypothesis that prolonged cigarette smoking is associated with increased risk of
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.
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 | 0.000 | 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 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".