Smoking May Reduce the Effectiveness of Anti-TNF Therapies to Induce Clinical Response and Remission in Crohn’s Disease: A Systematic Review and Meta-analysis
Bibliographic record
Abstract
BACKGROUND AND AIMS: Cigarette smoking worsens prognosis of Crohn's disease [CD]. We conducted a systematic review and meta-analysis to examine the association between smoking and induction of clinical response or remission with anti-tumour necrosis factor [TNF] therapy. METHODS: MEDLINE, EMBASE, PubMed, and Cochrane CENTRAL [June 2019] were searched for studies reporting the effect of smoking on short-term clinical response and remission to anti-TNF therapy [≤16 weeks following the first treatment] in patients with CD. Risk ratios [RR] with 95% confidence intervals [CI] were calculated using random-effects models. RESULTS: Eighteen observational studies and three randomised controlled trials [RCT] were included. Current smokers and non-smokers [never or former] had similar rates of clinical response [observational studies RR: 0.96; 95% CI: 0.88, 1.05; RCTs RR: 1.09; 95% CI: 0.84, 1.41]. When restricted to studies clearly defining the smoking exposure, smokers treated with anti-TNF were less likely to achieve clinical response than non-smokers [smokers defined as having ≥5 cigarettes/day for ≥6 months RR: 0.63; 95% CI: 0.48, 0.83; lifetime never smokers vs ever smokers excluding former smokers RR: 0.81; 95% CI: 0.71, 0.93]. Current smokers were also less likely to achieve clinical remission in observational studies [RR: 0.75; 95% CI: 0.57, 0.98], though this association was not seen in RCTs [RR: 1.04; 95% CI: 0.89, 1.21]. CONCLUSIONS: Smoking is significantly associated with a reduction in the ability of infliximab or adalimumab to induce short-term clinical response and remission when pooling studies where smoking status was clearly defined. When patients with CD are treated with highly effective therapy, including anti-TNF agents, concurrent smoking cessation may improve clinical outcomes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 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) | 0.000 | 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 teacher head, 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".