Number concentrations of ultrafine particles and the incidence of postmenopausal breast cancer
Bibliographic record
Abstract
Background: There have been a number of reports regarding possible associations between the incidence of female breast cancer and ambient air pollution. Only one study has been published about possible association with ultrafine particles (UFPs; <0.1 μm). Methods: We conducted a case–control study of incident postmenopausal breast cancer in Montreal, Canada. Cases were identified between 1996 and 1997 from all hospitals that treated breast cancer. Controls were women diagnosed with other sites of cancer and frequency-matched to cases by hospital and 5-year age groups. Concentrations of UFPs were estimated using a land-use regression model developed in 2011–2012 and assigned to women’s residential addresses at time of diagnosis. Odds ratios (OR) and 95% confidence intervals (95% CI) were estimated using logistic regression models adjusting for individual-level and ecological covariates. Results: We found that the response functions between UFPs and incident, postmenopausal breast cancer were consistent with linearity. Adjusted ORs of 1.08 (95% CI = 0.96, 1.21) were found for an increase in UFPs equal to the interquartile range (IQR). We found higher ORs among cases with positive estrogen (ER+) and negative progesterone receptor (PR−) (OR = 1.23; 95% CI = 1.04–1.45) and for women with ER−/PR− status (OR = 1.23; 95% CI = 0.99–1.54). We also found stronger associations when analyses were restricted to those women who had not lived at their current address for 10 years or more (OR = 1.27; 95% CI = 0.94–1.71). Conclusions: Our findings suggest that exposure to ambient UFPs may increase the risk of incident postmenopausal breast cancer, especially among cases with ER+/PR− and ER−/PR− receptor status.
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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 | 0.005 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".