O-22 Cancer surveillance among plastics and rubber manufacturing workers in Ontario, Canada
Bibliographic record
Abstract
Objective Occupational exposure to agents used in plastics and rubber manufacturing have been associated with elevated risk of certain cancers. We sought to estimate cancer risk among workers with a history of employment in plastics and rubber manufacturing as part of an ongoing surveillance program in Ontario, Canada. Methods The Occupational Disease Surveillance System (ODSS) cohort was established using workers’ compensation claims data and includes 2.18 million workers employed between 1983–2014. Workers were followed for site-specific cancer diagnoses in the Ontario Cancer Registry through 2016. Cox-proportional hazard models were used to estimate adjusted hazard ratios (HR) and 95% confidence intervals (CI). Results We identified 81,127 workers (69% male) ever-employed in plastics and rubber manufacturing industries or materials processing and product fabricating occupations. Compared to all other workers in the ODSS, workers in materials processing occupations had an elevated rate of lung cancer (HR 1.11, 95% CI: 1.02–1.20), which occurred almost exclusively among females (HR 1.38, 95% CI 1.20–1.58) in sex-stratified analyses. An elevated rate of breast cancer was observed among female labourers (HR 1.36, 95% CI: 1.01–1.82) and moulders (HR 1.47, 95% CI: 0.91–2.37) in plastics and rubber product fabricating occupations. Rates were elevated for esophageal, liver, stomach, prostate, and kidney cancer in job-specific subgroups including mixing and blending, bonding and cementing, and labouring. Workers in the plastics product fabricating industry had modestly elevated rates of pancreatic and brain and nervous system cancer. Conclusions Elevated rates of lung and breast cancer among females are consistent with other studies of women in plastics and rubber manufacturing and warrant further attention in Ontario. Results for digestive and other cancers are broadly consistent with exposure to known or suspected carcinogens in these industries and suggest new sites of potential concern.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".