Effects of varenicline and bupropion on laboratory smoking outcomes: Meta‐analysis of randomized, placebo‐controlled human laboratory studies
Bibliographic record
Abstract
Human laboratory studies are widely used to evaluate behavioural mechanisms of pharmacotherapy effects. Results from human laboratory studies examining smoking cessation pharmacotherapies have not been examined in aggregate. The current meta-analysis aimed to synthesize data from randomized, placebo-controlled human laboratory studies on the effects of non-nicotine pharmacotherapies on outcomes relevant for smoking cessation. Literature searches identified 15 human laboratory studies of varenicline (n = 697) and 9 studies of bupropion (n = 313) with sufficient data for inclusion. Studies involved acute or subacute pharmacotherapy treatment with administration durations ranging from a single dose to 8 weeks. Primary outcomes examined were craving, withdrawal and behavioural indices of smoking. Varenicline significantly reduced craving (Hedge's g = -0.36[-0.54,-0.17], p < 0.001), withdrawal (g = -0.25[-0.41,-0.09], p = 0.003) and behavioural indices of smoking (g = -0.36[-0.63,-0.08], p = 0.01) relative to placebo. In contrast, results were inconclusive regarding bupropion's effects on craving (g = -0.13[-0.32,0.05], p = 0.15), withdrawal (g = -0.15[-0.44,0.14], p = 0.31) and behavioural indices of smoking (g = -0.05[-0.35,0.24], p = 0.73) relative to placebo. Findings provide meta-analytic support that short-term varenicline treatment decreases craving, withdrawal symptoms and smoking behaviour under controlled laboratory conditions. However, findings also suggest the ability of human laboratory paradigms to detect pharmacotherapy effects may differ by treatment type. Pharmacotherapy discovery and evaluation efforts utilizing human laboratory methods should aim to align study designs and laboratory procedures with presumed therapeutic mechanisms when possible.
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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 | 0.029 | 0.055 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.019 | 0.045 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".