Association of Nicotine Metabolite Ratio and CYP2A6 Genotype With Smoking Cessation Treatment in African-American Light Smokers
Bibliographic record
Abstract
Cytochrome P450 2A6 (CYP2A6) is the main nicotine (NIC)-metabolizing enzyme in humans. We investigated the relationships between CYP2A6 genotype, baseline plasma trans- 3'-hydroxycotinine/cotinine (3HC/COT) (a phenotypic marker of CYP2A6 activity), and smoking behavior in African-American light smokers. Cigarette consumption, age of initiation, and dependence scores did not differ among 3HC/COT quartiles or CYP2A6 genotype groups. Slow metabolizers (SMs; both genetic and phenotypic) had significantly higher plasma NIC levels, suggesting that cigarette consumption was not reduced to adjust for slower rates of NIC metabolism. Individuals in the slowest 3HC/COT quartile had higher quitting rates with both placebo and NIC gum treatments (odds ratio 1.85, 95% confidence interval (CI) 1.08-3.16, P = 0.03). Similarly, the slowest CYP2A6 genotype group had higher quitting rates, although this trend did not reach significance (odds ratio 1.61, 95% CI 0.95-2.72, P = 0.08). The determination of the 3HC/COT ratio, and possibly CYP2A6 genotype, may be useful in the future for personalizing the choice of smoking cessation treatment in African-American light smokers.
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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 | 0.003 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".