Factors moderating the relative effectiveness of varenicline and nicotine replacement therapy in clients using smoking cessation services
Bibliographic record
Abstract
AIMS: To assess how far the greater effectiveness of varenicline over nicotine replacement therapy (NRT) is moderated by characteristics of the smokers or setting in clinical practice. DESIGN: We used observational data from 22 472 treatment episodes between 2013 and 2016 from smoking cessation services in England to assess whether differences between varenicline and NRT were moderated by a set of smoker and setting characteristics: these included level of social deprivation, age, gender, ethnic group, nicotine dependence and treatment context. From the above, 15 640 episodes were analysed in relation to 4-week quit and 14 273 episodes at 12 weeks. All two-way interactions involving pharmacotherapy were fitted in addition to the main effects and a parsimonious model identified using a backwards stepwise selection procedure. SETTING: England PARTICIPANTS: Clients of smoking cessation service (number of individuals in 4-week quit analysis = 15 640). MEASUREMENTS: Four-week carbon monoxide-validated (primary outcome) and 12-week self-reported (secondary outcome) quit success/failure. FINDINGS: At both follow-up points, varenicline was associated with higher success rates overall [P < 0.001 at both 4 and 12 weeks; adjusted odds ratio (OR) varenicline versus NRT = 1.82 (95% confidence interval (CI) = 1.61, 2.06) and 2.58 (95% CI = 2.26, 2.94) at 4 and 12 weeks, respectively]. At 12 weeks, the relative benefits of varenicline were found to be influenced by the setting in which advice was provided [P < 0.001 for interaction pharmacotherapy × setting; adjusted odds ratio for varenicline × pharmacy setting = 0.53 (95% CI = 0.42, 0.69) and for varenicline × general practice (GP) setting = 0.79 (95% CI = 0.64, 0.98) against a baseline of 1 for varenicline × community setting]. The same trends were evident at 4 weeks, but this did not translate to statistical significance. There was inconclusive evidence for moderating effects of other variables. CONCLUSIONS: Varenicline use was associated with higher smoking cessation rates than nicotine replacement therapy in routine clinical practice, irrespective of a wide range of smoker characteristics, but the difference was less in certain intervention settings, most notably pharmacy but also GP practice, compared with community setting.
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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 | 0.009 | 0.051 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".