8292700 Exposure-response relationship for cumulative asbestos exposure and lung cancer: a systematic review and meta-analysis study
Bibliographic record
Abstract
Objective To conduct an updated systematic review and meta-analyses of the exposure-response relationship between cumulative occupational asbestos exposure and the risk of lung cancer. Material and Methods The search strategy was executed on five databases and by review of reference lists. A total of 32 cohort and case-control studies with risk estimates for cumulative, categorical asbestos exposure and lung cancer risk were included. The reported mean or midpoint of each cumulative asbestos exposure category was log-transformed and meta-analyzed using multi-level, random intercept, log-linear regression models. Analyses explored higher risk groups and sources of heterogeneity by exposure and study characteristics, including the quality of the exposure assessment. The investigators reached consensus on interpretation of the findings by emphasizing the consistency of the findings and study informativeness, and placing less emphasis on statistical significance in the meta-analyses of a significant occupational hazard. Results The predicted exposure-response curve, extrapolated from the overall meta-risk estimate (theta (θ)=0.13 (95% CI, 0.10, 0.16)), was nonlinear with a steeper rise in risk at the lower exposure range: the estimated RR was 1.21 (1.17, 1.26) at 5 f-yr/ml; 1.43 (1.33, 1.53) at 25 f-yr/ml; 1.52 (1.40, 1.63) at 50 f-yr/ml; 1.61 (1.47, 1.64) at 100 f-yr/m; and 1.71 (1.54, 1.87) at 200 f-yr/ml. Stronger exposure-response relationships were observed in studies with higher quality exposure assessment (e.g., RR from 1.32 to 2.07 across the same range of exposures), as well as in studies of asbestos production and manufacturing workers, particularly in North America. The results were robust to sensitivity analyses investigating sources of heterogeneity and analytic methods. Conclusion Increasing cumulative asbestos exposure is associated with higher lung cancer risk across the range of cumulative exposure, with a steeper rise in risk at the lower exposure range.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.016 | 0.034 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.031 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".