A Randomized Controlled Trial Evaluating the Efficacy of E-Cigarette Use for Smoking Cessation in the General Population: E3 Trial Design
Bibliographic record
Abstract
BACKGROUND: Smoking cessation improves morbidity and mortality among smokers who achieve long-term abstinence. Many smokers are using electronic cigarettes (e-cigarettes) to attempt to quit, despite a lack of data concerning their efficacy and safety for smoking cessation. METHODS: The Evaluating the Efficacy of E-Cigarette use for Smoking Cessation (E3) trial is a multicentre randomized controlled trial (NCT02417467) with a treatment period of 12 weeks and follow-up of 52 weeks. A total of 376 participants motivated to quit smoking were enrolled at 17 Canadian centres (November 2016 to September 2019). Participants were randomized (1:1:1) to 1 of 3 treatment arms: nicotine e-cigarettes, non-nicotine e-cigarettes, or no e-cigarettes. All groups received individual counselling. Treatment allocation was double-blind for the e-cigarette groups. The trial includes follow-ups by telephone at weeks 1, 2, 8, and 18, and clinic visits at weeks 4, 12, 24, and 52. The primary endpoint is to compare nicotine e-cigarettes to counselling alone in terms of biochemically validated point-prevalence smoking abstinence at 12 weeks; the primary endpoint was changed from 52 weeks after early termination (77% of targeted enrollment) due to a prolonged delay in e-cigarette manufacturing. The secondary objectives are to examine the efficacy of nicotine and non-nicotine e-cigarettes in terms of point-prevalence and continuous smoking abstinence, and reduction in daily cigarette consumption at all follow-ups through week 52, and to describe the occurrence of adverse events. CONCLUSION: The E3 trial will provide regulators, health care professionals, and smokers with important information about the efficacy and safety of e-cigarettes for smoking cessation.
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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 | 0.016 | 0.018 |
| Meta-epidemiology (narrow) | 0.004 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.004 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.006 | 0.004 |
| Insufficient payload (model declined to judge) | 0.020 | 0.002 |
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".