Association of Reduced Nicotine Content Cigarettes With Smoking Behaviors and Biomarkers of Exposure Among Slow and Fast Nicotine Metabolizers
Bibliographic record
Abstract
Importance The US Food and Drug Administration (FDA) has announced its intention to reduce the nicotine content in combustible cigarettes but must base regulation on public health benefits. Fast nicotine metabolizers may be at risk for increased smoking following a national nicotine reduction policy. We hypothesized that using reduced nicotine content (RNC) cigarettes would be associated with increases in smoking behaviors and exposure among smokers with a fast—but not slow—nicotine-metabolite ratio (NMR). Objectives To examine the association of RNC cigarettes with smoking behaviors and biomarkers of exposure and to compare these associations in fast and slow metabolizers of nicotine based on the NMR. Design, Setting, and Participants A 35-day, 3-period, within-participant nonrandomized clinical trial was conducted at an academic medical center in Philadelphia, Pennsylvania. A 5-day baseline period using the smokers’ preferred brand of cigarettes was followed by 2 consecutive 15-day periods using free investigational RNC cigarettes. A total of 100 daily, non–treatment-seeking, nonmenthol cigarette smokers (59 fast, 41 slow metabolizers) were recruited from December 24, 2013, to December 2, 2015. Data analysis was performed from December 12, 2016, to January 3, 2018. Interventions Two 15-day periods using cigarettes containing 5.2 mg (RNC1) and 1.3 mg (RNC2) of nicotine per gram of tobacco. Main Outcomes and Measures Smoking behaviors (number of cigarettes per day [CPD], total puff volume) and biomarkers of exposure (carbon monoxide [CO], urine total nicotine equivalents [TNE], and 4-[methylnitrosamino]-1-[3-pyridyl]-1-butanol [NNAL]). Results Smokers (73 [73.0%] men; 74 [74.0%] white; mean [SD] age, 43.02 [12.13] years; mean [SD] CPD, 17.31 [5.72]) consumed 2.62 (95% CI, 1.54-3.70) more CPD during the RNC1 period vs their preferred brand during baseline (P < .001) and approximated baseline CPD during the RNC2 period (mean difference, 0.96 [95% CI, −0.36 to 2.28];P = .24). Additional outcome measures were lower during both RNC periods vs baseline (total puff volume, mean [95% CI]: RNC1, 537 mL [95% CI, 479-595 mL]; RNC2, 598 mL [95% CI, 547-649 mL] vs baseline, 744 mL [95% CI, 681-806 mL]; TNE, mean [95% CI]: RNC1, 30.9 nmoL/mg creatinine [95% CI, 26.0-36.6 nmoL/mg]; RNC2, 22.8 nmoL/mg creatinine [95% CI, 17.8-29.0 nmoL/mg] vs baseline, 54.6 nmoL/mg creatinine [95% CI, 48.1-62.1 nmoL/mg]; and NNAL, mean [95% CI]: RNC1, 229 pg/mg creatinine [95% CI, 189-277 pg/mg]; RNC2, 190 pg/mg creatinine [95% CI, 157-231 pg/mg] vs baseline, 280 pg/mg creatinine [95% CI, 231-339 pg/mg]; allP < .001). Carbon monoxide measures were similar across study periods (CO boost [SD], RNC1, 4.6 ppm [4.1-5.1 ppm]; RNC2, 4.2 ppm [3.7-4.6 ppm]; and baseline, 4.4 ppm [3.8-4.9 ppm]). The RNC cigarette associations did not differ by NMR. Conclusions and Relevance Both RNC cigarettes were associated with decreased puffing and urinary biomarker exposure but not with decreased daily cigarette consumption or CO levels. The NMR did not moderate associations at the nicotine levels tested, suggesting that fast metabolizers may not be at greater risk of increasing use or exposure from these products should the FDA mandate an RNC standard for cigarettes. Trial Registration ClinicalTrials.gov identifier:NCT01898507
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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) | 0.002 | 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".