Neither NRT aided gradual cessation nor abrupt cessationis superior in producing long-term abstinence: Reconcilingconflicting results from two recent meta-analyses
Bibliographic record
Abstract
Dear Editor, Reduction in tobacco smoking before attempting to quit is common (i.e.gradual cessation) 1 , but guidelines for health professionals recommend abrupt smoking cessation 2,3 .We recently completed a Cochrane systematic review and metaanalysis including 22 trials (9219 participants) of gradual versus abrupt smoking cessation and found neither approach produced superior long-term cessation outcomes (RR=1.01;95% CI: 0.87-1.17;I 2 =29%).We found similar results when restricting the analysis to 9 trials of gradual cessation versus abrupt cessation aided by nicotine replacement therapy (NRT) (RR=0.91;95% CI: 0.72-1.16;I 2 =26%; 4359 participants) 4 .However, Tan et al. 5 recently published a metaanalysis that concluded abrupt cessation was superior to gradual cessation with the aid of NRT, which contradicts our findings 4 .Tan et al. 5 report that they restricted their meta-analysis to 3 trials where abstinence was biochemically verified and 'both groups used an equal amount of NRT before and after quitting'.However, two of their three included trials provided NRT to participants before quitting in the gradual but not in the abrupt cessation condition 6,7 , and the third provided more NRT to the gradual than to the abrupt condition in the period before the quit day 8 .Our meta-analysis of NRT-aided studies included the three trials in the Tan et al. 5 meta-analysis, plus an additional six trials comparing gradual versus abrupt smoking cessation 4 .Due to the design of the existing trials testing this comparison, neither meta-analysis provided a test of gradual versus abrupt cessation with equivalent pre-and post-quit NRT across conditions.There are a number of methodological limitations to the Tan et al. 5 review, two of which were likely to have led to the limited number of studies found eligible for inclusion.First, they only included studies that used biochemically verified abstinence.Although, this is a gold standard for measuring smoking abstinence in trials 9 , and its absence may inflate absolute abstinence rates, there is no apparent reason to assume that the likelihood of misreporting abstinence would differ between the gradual and abrupt conditions.Thus, the use of selfreported abstinence in some trials is unlikely to have affected relative abstinence rates (e.g.risk ratios) and should be included in meta-analyses to maximize the use of existing research.Second, they reported the use of very limited search terms (['smoking cessation'] AND ['abrupt' OR 'gradual']), which appear to have missed much of the relevant literature.Many relevant trials do not use the terms 'gradual' or 'abrupt' to describe their methodology.This is supported by the fact that their searches resulted in 134 records for screening 5 , as opposed to the 1944 records screened by Lindson et al. 8 .Thus, we conclude that due to methodological limitations, the Tan et al. 5 findings do not fully represent existing research.When all trials of NRT-aided gradual versus abrupt 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 | 0.035 | 0.058 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.024 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.004 |
| 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".