Occupational asbestos exposure and gastrointestinal cancers: systematic review and meta-analyses
Bibliographic record
Abstract
OBJECTIVE: To conduct meta-analyses of occupational asbestos exposure and oesophageal, stomach and colorectal cancer risk, including a critical exposure assessment approach. METHODS: The search strategy was executed on MEDLINE, Embase, CINAHL, Scopus and Web of Science databases (March 2022, March 2024). Effect estimates (ORs, HRs, standardised incidence ratio and standardised mortality ratio) from eligible cohort and case-control studies were combined in random effects models. Meta-relative risks (mRRs) were calculated by cancer site and exposure characteristics. Investigators with occupational epidemiology and hygiene expertise came to a consensus on the estimates where there was confidence in significant asbestos exposure. RESULTS: A total of 82 (oesophageal), 153 (stomach) and 144 (colorectal) papers met the inclusion criteria. Elevated mRRs were observed for any occupational asbestos exposure for oesophageal (1.17 (95% CI 1.07 to 1.29)), stomach (1.14 (95% CI 1.05 to 1.23)) and colorectal cancer (1.16 (95% CI 1.08 to 1.24)). There was consistency of mRR estimates and higher mRRs in meta-analyses where there was increased confidence in the categorisation of highly exposed workers, including among the highest exposed workers in exposure-response studies (oesophageal: 1.63 (95% CI 1.29 to 2.06); stomach: 1.28 (95% CI 1.09 to 1.52); colorectal: 1.29 (95% CI 1.09 to 1.53)), among asbestos insulation workers (oesophageal: 1.68 (95% 1.19 to 2.36); stomach: 1.53 (95% 0.93 to 2.51); colorectal: 1.59 (95% 1.14 to 2.23)) and among workers in cohorts with a twofold or greater risk of asbestos-related lung cancer (oesophageal: 1.40 (95% CI 1.14 to 1.71); stomach: 1.33 (95% CI 1.14 to 1.56); colorectal: 1.47 (95% CI 1.34 to 1.61)). CONCLUSION: The meta-analyses support a causal link between occupational asbestos exposure and the risk of oesophageal, stomach and colorectal cancer.
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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 | 0.021 | 0.045 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.021 | 0.048 |
| Bibliometrics | 0.011 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| 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 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".