Utility and Relationships of Biomarkers of Smoking in African-American Light Smokers
Bibliographic record
Abstract
Although expired carbon monoxide (CO) and plasma cotinine (COT) have been validated as biomarkers of self-reported cigarettes per day (CPD) in heavy smoking Caucasians, their utility in light smokers is unknown. Further, variability in CYP2A6, the enzyme that mediates formation of COT from nicotine and its metabolism to trans-3'-hydroxycotinine (3HC), may limit the usefulness of COT. We assessed whether CO and COT are correlated with CPD in African-American light smokers (< or =10 CPD, n = 700), a population with known reduced CYP2A6 activity and slow COT metabolism. We also examined whether gender, age, body mass index, smoking mentholated cigarettes, or rate of CYP2A6 activity, by genotype and phenotype measures (3HC/COT), influence these relationships. At baseline, many participants (42%) exhaled CO of < or =10 ppm, the traditional cutoff for smoking, whereas few (3.1%) had COT below the cutoff of < or =14 ng/mL; thus, COT seems to be a better biomarker of smoking status in this population. CPD was weakly correlated with CO and COT (r = 0.32-0.39, P < 0.001), and those reporting fewer CPD had higher CO/cigarette and COT/cigarette, although the correlations coefficients between these variables were also weak (r = -0.33 and -0.08, P < 0.05). The correlation between CPD and CO was not greatly increased when analyzed by CYP2A6 activity, smoking mentholated cigarettes, or age, although it appeared stronger in females (r = 0.38 versus 0.21, P < 0.05) and obese individuals (r = 0.38 versus 0.24, P < 0.05). Together, these results suggest that CO and COT are weakly associated with self-reported cigarette consumption in African-American light smokers, and that these relationships are not substantially improved when variables previously reported to influence these biomarkers are considered.
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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 | 0.007 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".