Toward Personalized Therapy for Smoking Cessation: A Randomized Placebo-controlled Trial of Bupropion
Bibliographic record
Abstract
We examined whether a pretreatment phenotypic marker of nicotine metabolism rate (NMR) predicts successful smoking cessation with bupropion. Smokers (N = 414) were tested for pretreatment NMR, based on the ratio of 3′-hydroxycotinine/cotinine derived during smoking, before entering a placebo-controlled randomized trial of bupropion plus counseling. At the end of the 10-week treatment phase, slow metabolizers (1st NMR quartile) had equivalent quit rates with placebo or bupropion (32%). Fast metabolizers (4th NMR quartile) had low quit rates with placebo (10%), and these were enhanced significantly by bupropion (34%). Smokers in the 2nd quartile (placebo: 25%, bupropion: 30%) and the 3rd quartile (placebo: 20%, bupropion: 30%) did not benefit significantly from bupropion. At the 6-month follow-up, the relationship between the NMR and quitting remained similar, but was no longer statistically significant. A pretreatment assessment of NMR may identify smokers who are most and least likely to benefit from treatment with bupropion for smoking cessation. Clinical Pharmacology & Therapeutics (2008); 84, 3, 320–325 doi:10.1038/clpt.2008.57
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".