The Nicotine Metabolite Ratio is Associated With Early Smoking Abstinence Even After Controlling for Factors That Influence the Nicotine Metabolite Ratio
Bibliographic record
Abstract
INTRODUCTION: The decrease in smoking rates in North America has plateaued, underscoring the need for new approaches to treat nicotine dependence. Inter-individual differences in smoking behavior result, in part, from variation in the rate of CYP2A6-mediated nicotine metabolism. A phenotypic measure of CYP2A6 activity is the nicotine metabolite ratio (NMR), the ratio of 3'hydroxycotinine/cotinine. The NMR is associated with smoking cessation. However, the NMR is also associated with genetic (eg, CYP2A6 genotype) and other (eg, sex and ethnicity) factors. Here we aimed to determine if previously identified non-CYP2A6 sources of variation in the NMR mitigated the association between the NMR and short-term abstinence. METHODS: The NMR was determined from blood samples collected at intake from daily smokers aged 18-65. Biochemically-verified point prevalence abstinence (exhaled carbon monoxide level ≤ 8 ppm) was measured at 1 week following the target quit date in participants from a smoking cessation clinical trial (NCT01314001). Analyses were restricted to N = 462 blacks and N = 693 whites in the intent-to-treat sample. RESULTS: Lower NMR (<0.31) was associated with a higher likelihood of 1-week abstinence (OR = 1.43; 95% CI = 1.12, 1.84). NMR was associated with abstinence even after controlling for treatment arm (nicotine patch or varenicline) and factors previously associated with NMR variation including sex, ethnicity, estrogen-containing hormonal therapy, body mass index, alcohol, and cigarette consumption. CONCLUSIONS: NMR was associated with 1-week smoking abstinence; NMR may be a useful addition to medication screening approaches evaluating treatments for nicotine dependence.
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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 | 0.007 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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".