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Record W2025045247 · doi:10.1097/fpc.0b013e32835f834d

CYP2A6 slow nicotine metabolism is associated with increased quitting by adolescent smokers

2013· article· en· W2025045247 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenuePharmacogenetics and Genomics · 2013
Typearticle
Languageen
FieldMedicine
TopicSmoking Behavior and Cessation
Canadian institutionsUniversity of TorontoCanada Research ChairsUniversity of New BrunswickUniversité de MontréalCentre for Addiction and Mental Health
FundersNational Institute on Drug AbuseCanadian Institutes of Health Research
KeywordsCYP2A6Odds ratioSmoking cessationNicotineConfidence intervalMedicinePharmacogeneticsInternal medicinePhysiologyCohortLogistic regressionAbstinenceEndocrinologyMetabolismGenotypeGeneticsBiologyPsychiatryGeneCytochrome P450Pathology

Abstract

fetched live from OpenAlex

Variation in the CYP2A6 gene, which decreases the rate of nicotine metabolic inactivation, is associated with higher adult smoking cessation rates during clinical trials. We hypothesized that slow metabolism is associated with increased quitting during adolescence. White adolescent smokers (N=308, aged 12-17, 36.3% male) from a cohort study were genotyped for CYP2A6, resulting in 7.8% slow, 14.0% intermediate and 78.2% normal metabolizers. Overall, 144 smokers quit smoking, as indicated by being abstinent for at least 12 months. In logistic regression analyses, the odds ratio for quitting was 2.25 (95% confidence interval 1.05, 4.80; P=0.037) for slow metabolizers relative to normal metabolizers. A linear trend toward increased quitting with decreasing CYP2A6 activity was also observed (odds ratio=1.44, 95% confidence interval 1.02, 2.01; P=0.034). Thus, CYP2A6 slow metabolism is associated with increased adolescent smoking cessation, indicating that even early in the smoking history, genetic variation is influencing smoking cessation.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.090
Threshold uncertainty score0.663

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.017
GPT teacher head0.263
Teacher spread0.246 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it