Pesticide use, immunologic conditions, and risk of non‐Hodgkin lymphoma in Canadian men in six provinces
Bibliographic record
Abstract
Pesticide exposures and immune suppression have been independently associated with the risk of non-Hodgkin lymphoma (NHL), but their joint effect has not been well explored. Data from a case-control study of men from six Canadian provinces were used to evaluate the potential effect modification of asthma, allergies, or asthma and allergies and hay fever combined on NHL risk from use of: (i) any pesticide; (ii) any organochlorine insecticide; (iii) any organophosphate insecticide; (iv) any phenoxy herbicide; (v) selected individual pesticides [1,1'-(2,2,2-trichloroethylidene)bis[4-chlorobenzene]; 1,1,1-trichloro-2,2-bis(4-chlorophenyl) ethane (DDT), malathion, (4-chloro-2-methylphenoxy)acetic acid (MCPA), mecoprop, and (2,4-dichlorophenoxy)acetic acid (2,4-D); and (vi) from the number of potentially carcinogenic pesticides. Incident NHL cases (n = 513) diagnosed between 1991 and 1994 were recruited from provincial cancer registries and hospitalization records and compared to 1,506 controls. A stratified analysis was conducted to calculate odds ratios (ORs) adjusted for age, province, proxy respondent, and diesel oil exposure. Subjects with asthma, allergies, or hay fever had non-significantly elevated risks of NHL associated with use of MCPA (OR = 2.67, 95% confidence interval [CI]: 0.90-7.93) compared to subjects without any of these conditions (OR = 0.81, 95% CI: 0.39-1.70). Conversely, those with asthma, allergies, or hay fever who reported use of malathion had lower risks of NHL (OR = 1.25, 95% CI: 0.69-2.26) versus subjects with none of these conditions (OR = 2.44, 95% CI: 1.65-3.61). Similar effects were observed for asthma and allergies evaluated individually. Although there were some leads regarding effect modification by these immunologic conditions on the association between pesticide use and NHL, small numbers, measurement error and possible recall bias limit interpretation of these results.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".