Association Between Smoking and Survival Benefit of Immunotherapy in Advanced Malignancies
Bibliographic record
Abstract
OBJECTIVES: Smoking is associated with an increased tumor mutational burden. As tumor mutational burden has been shown to correlate with response to immunotherapy (IO), we hypothesized that a history of smoking may be associated with better response to IO. METHODS: We utilized a systematic review with stratified meta-analysis of randomized clinical trials of IO versus standard of care in patients with advanced solid organ malignancies. RESULTS: Among 9 relevant studies, we found no significant difference in the benefit of IO, compared with other systemic therapies, between ever smokers (hazard ratio [HR], 0.77; 95% confidence interval [CI], 0.58-1.04; P=0.09) and never smokers (HR, 0.75; 95% CI, 0.67-0.86; P<0.0001) (test for difference P=0.83). We also observed no significant difference between current (HR, 0.92; 95% CI, 0.63-1.34; P=0.66; I=67%) and never smokers (HR, 0.74; 95% CI, 0.59-0.93; P=0.01; I=46%) (test for difference P=0.35). CONCLUSIONS: Stratified meta-analysis demonstrates that smoking status is not significantly associated with the response to IO in the treatment of advanced solid organ malignancies.
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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 | 0.005 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.013 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| 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".