Effectiveness of Bupropion and Varenicline for Smokers With Baseline Depressive Symptoms
Bibliographic record
Abstract
INTRODUCTION: Smokers with concurrent depression are less likely to achieve abstinence, even with pharmacotherapy. The purpose of this secondary data analysis was to evaluate if the presence of any depressive symptoms at baseline alters the effectiveness of bupropion and varenicline for smoking cessation. AIMS AND METHODS: Eligible participants were enrolled via the internet and randomized 1:1 to receive a 12-week supply of either bupropion (n = 465) or varenicline (n = 499). Depressive symptoms were assessed using the Patient Health Questionnaire (PHQ-2). Follow-up surveys were conducted at weeks 4, 8, 12, 26, and 52 to assess self-reported quit. The primary outcome was 7-day point prevalence abstinence at 12 weeks follow-up (end-of-treatment). RESULTS: Participants who endorsed any depressive symptoms (PHQ-2 > 0; n = 280) were less likely to be quit at end-of-treatment compared to participants who did not endorse any symptoms (PHQ-2 = 0; n = 684) (OR = 0.56, 95% CI: 0.38 to 0.8, p = .003). Within the varenicline group, quit outcomes did not differ between those with and without depressive symptoms (21.3% vs. 26.9%, respectively). Within the bupropion group, however, those with symptoms had a significantly reduced quit rate compared to those without symptoms (7.0% vs. 17.3%, respectively). CONCLUSIONS: The presence of even one symptom of depression at the start of a quit attempt may adversely affect quit outcomes. Patients should be assessed for depressive symptoms when planning to quit smoking as it may inform the approach to treatment. However, future studies are needed to confirm these findings. IMPLICATIONS: Findings from the current study illustrate the importance of evaluating baseline sub-clinical depressive symptoms before a quit attempt using first-line pharmacotherapies. This secondary analysis of a large-scale randomized trial suggests that bupropion may be less effective for those with baseline depressive symptoms while varenicline may be equally effective for those with and without depressive symptoms.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".