O-063 ENDOCRINE DISRUPTING CHEMICALS AND COLORECTAL CANCER – AN ANALYSIS OF FOUR PARTICIPATING COHORTS OF THE CANADIAN PARTNERSHIP FOR TOMORROW’S HEALTH STUDY
Bibliographic record
Abstract
Abstract Introduction Endocrine disrupting chemicals (EDCs) may influence cancer risk by interfering with sex hormone signaling but their role in colorectal cancer (CRC) etiology is under-explored. EDCs are ubiquitous in the general environment, but exposure levels are much higher in some workplaces. Methods Occupational EDC exposure in relation to CRC was examined in the Canadian Partnership for Tomorrow’s Health, a collaboration of six Canadian regional cohorts, including 330,000 participants aged 30-74 at baseline. Among four regional cohorts with enough cases for inclusion, a case-cohort approach was used, which included 1,087 cases that were diagnosed during follow-up (2009-2020) and a representative sub-cohort of 4,895 participants. Based on participants’ reported longest-held job, exposure to EDCs of estrogenic (arsenic, BPA, cadmium, copper, PCBs), anti-estrogenic (arsenic, lead, PCBs) and anti-androgenic (arsenic, BPA, lead, phthalates, toluene) mode of action was estimated using the Canadian Job Exposure Matrix. Odds ratios and 95% confidence intervals were estimated separately for the four regional cohorts and then pooled using a random-effects model. Results Compared to those never exposed, participants exposed to BPA (OR=1.70, 95%CI: 1.20-2.41) or 2+ anti-estrogenic EDCs (OR2 EDCs=1.48, 95%CI: 1.09-2.01; OR3 EDCs= OR=17.23, 95%CI: 0.79-375.52) had elevated odds for CRC while an inverse association was observed for cadmium. Substantial heterogeneity was observed across provincial regions. Discussion and conclusion Among EDCs considered, exposure to BPA and multiple anti-estrogenic EDCs in the workplace were associated with elevated risk for CRC. However, conclusions should be tempered given the heterogeneity between the four regional cohorts, low study power for some of the analyses and multiple comparisons.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".