Cigarette Smoking and Risk of Lung Metastasis from Esophageal Cancer
Bibliographic record
Abstract
BACKGROUND: Whereas extensive research has explored the effect of environmental factors on the etiology of specific cancers, the influence of exposures such as smoking on risk of site-specific metastasis is unknown. We investigated the association of cigarette smoking with lung metastasis in esophageal cancer. METHODS: We conducted a case-control study of esophageal cancer patients from two centers, comparing cases with lung metastases to controls without lung metastases. Information was gathered from medical records on smoking history, imaging results, site(s) of metastasis, and other patient and tumor characteristics. We used logistic regression to assess association. RESULTS: We identified 354 esophageal cancer cases; smoking status was known in 289 (82%). Among patients with lung metastases, 73.6% (39 of 53) were ever smokers, versus 47.8% (144 of 301) of patients without lung metastases [P=0.001; summary odds ratio (OR), 2.52; 95% confidence interval (95% CI), 1.17-5.45; stratified by histology]. Smoking was associated with a nonsignificant increased adjusted odds of lung metastasis (OR, 1.89; 95% CI, 0.80-4.46). Upper esophageal subsite (OR, 4.71; 95% CI, 1.20-18.5), but not histology (squamous OR 0.65,95% CI 0.27-1.60), was associated with lung metastasis. Compared with the combined never/unknown smoking status group, smoking was associated with a significantly increased odds of lung metastasis (OR, 2.35; 95% CI, 1.11-4.97). There was no association between liver metastasis and smoking (OR, 0.88; 95% CI, 0.42-1.83). CONCLUSIONS: Smoking is associated with increased odds of lung metastasis from esophageal cancer, and this relationship seems to be site specific. Future studies are needed to determine whether smoking affects the tumor cell or the site of metastasis, and whether this changes the survival outcome.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| 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) | 0.001 | 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, unvalidatedLabeled directly by 2 models reading the full record.
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".