Inflammatory Cytokines and Lung Cancer Risk in 3 Prospective Studies
Bibliographic record
Abstract
To further investigate the role of inflammation in lung carcinogenesis, we evaluated associations between proinflammatory cytokines and lung cancer risk. We conducted a case-control study nested within 3 prospective cohort studies-the Melbourne Collaborative Cohort Study (1990-1994), the Malmö Diet and Cancer Study (1991-1996), and the Northern Sweden Health and Disease Study (initiated in 1985)-involving 807 incident lung cancer cases and 807 smoking-matched controls. Conditional logistic regression models adjusting for serum cotinine concentrations were used to estimate odds ratios for lung cancer risk associated with concentrations of interleukin (IL)-1β, IL-2, IL-6, IL-8, IL-10, IL-12, interferon γ, tumor necrosis factor α, and granulocyte-macrophage colony-stimulating factor. We observed a higher lung cancer risk for participants with elevated concentrations of IL-6 and IL-8. These associations seemed to be stronger among former smokers (for fourth quartile vs. first quartile, odds ratio (OR) = 2.70, 95% confidence interval (CI): 1.55, 4.70) and current smokers (OR = 1.99, 95% CI: 1.15, 3.44) for IL-6 and among former smokers (OR = 2.83, 95% CI: 1.18, 6.75) and current smokers (OR = 1.30, 95% CI: 0.69, 2.44) for IL-8. No notable associations were observed among never smokers. Risk associations with IL-6 and IL-8 were observed for blood samples taken close to diagnosis (<5 years) as well as more than 15 years postdiagnosis.
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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 | 0.002 | 0.009 |
| 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 | 0.001 |
| 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".