O-066 OCCUPATIONAL EXPOSURE TO NICKEL OR HEXAVALENT CHROMIUM AND THE RISK OF LUNG CANCER (SYNERGY)
Bibliographic record
Abstract
Abstract Background Limited evidence exists on the exposure-response relationship of hexavalent chromium (Cr(VI)) or nickel with lung-cancer risk. We estimated lung-cancer risks based on quantitative indices of occupational exposure to each metal, and their interaction with smoking habits. Methods Fourteen case-control studies from Europe and Canada (16,901 cases, 20,965 controls) were pooled. A measurement-based job-exposure matrix was used to estimate year- and region-specific exposure levels for Cr(VI) and nickel, which were linked to the study subjects’ occupational histories. Odds ratios (OR) and 95% confidence intervals (CI) were calculated, adjusting for study, age group, smoking, and exposure to other occupational lung carcinogens. Results The OR for the highest quartile (>99.5 μg/m3-years) of cumulative exposure to Cr(VI) in men was 1.32 (95% CI 1.19-1.47) and for nickel (highest quartile >78.1 μg/m3-years) OR=1.29 (95% CI 1.15-1.45). Corresponding results in women were: 1.04 (95% CI 0.48-2.24) and 1.29 (95% CI 0.60-2.86). In men, increased lung-cancer risks from occupational Cr(VI) and nickel exposure were also observed in each stratum of never, former, and current smokers. The joint effects of Cr(VI) and nickel with smoking were generally greater than additives. Discussion Strengths of our analysis include a large study population, detailed individual information on smoking habits, and exposure assessment by a comprehensive, measurement-based job-exposure matrix. However, we cannot rule out a combined classical measurement and Berkson error structure that may have caused bias in our risk estimates. Conclusion In conclusion, relatively low cumulative levels of occupational exposure to Cr(VI) and nickel were associated with increased ORs for lung cancer, particularly in men.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.004 | 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".