Parental Exposure to Polycyclic Aromatic Hydrocarbons and the Risk of Childhood Brain Tumors: The SEARCH International Childhood Brain Tumor Study
Bibliographic record
Abstract
Experimental evidence suggests that parental exposure to polycyclic aromatic hydrocarbons (PAH), which occurs primarily through tobacco smoke, occupational exposure, and air pollution, could increase the risk of cancer during childhood. Population-based case-control studies carried out in seven countries as part of the SEARCH Program compared data for 1,218 cases of childhood brain tumors and 2,223 controls (1976-1994). Parental occupational exposure to PAH during the 5-year period before birth was estimated with a job exposure matrix. Risk estimates were adjusted for child's age, sex, and study center. Paternal preconceptional occupational exposure to PAH was associated with increased risks of all childhood brain tumors (odds ratio (OR) = 1.3, 95% confidence interval: 1.1, 1.6) and astroglial tumors (OR = 1.4, 95% confidence interval: 1.1, 1.7). However, there was no trend of increasing risk with predicted level of exposure. Paternal smoking alone (OR = 1.4) was also associated with the risk of astroglial tumors in comparison with nonsmoking, non-occupationally-exposed fathers. Risks for paternal occupational exposure were higher, with (OR = 1.6) or without (OR = 1.7) smoking. Maternal occupational exposure to PAH before conception or during pregnancy was rare, and this exposure was not associated with any type of childhood brain tumor. This large study supports the hypothesis that paternal preconceptional exposure to PAH increases the risk of brain tumors in humans.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".