Childhood Acute Lymphoblastic Leukemia Associated with Parental Alcohol Consumption and Polymorphisms of Carcinogen-Metabolizing Genes
Bibliographic record
Abstract
BACKGROUND: Limited information is available on the association of parental consumption of alcohol prior to and during pregnancy with the risk of childhood leukemia, as well as for the potentially modifying role of genetic polymorphisms. METHODS: We conducted a population-based, case-control study of 491 incident cases of acute lymphoblastic leukemia age 0-9 years and matched on age and sex to 491 healthy controls. Cases were identified at tertiary care centers in the Province of Québec between 1980 and 1993. Each parent was interviewed separately about alcohol consumption habits. We also used a case-only design with 186 cases to estimate interaction odds ratios between prenatal exposure and child DNA variants in the GSTM1 and CYP2E1 genes. RESULTS: The adjusted odds ratio for any maternal consumption during pregnancy was 0.7 (95% confidence interval = 0.5-0.9). The interaction odds ratios for the GSTM1 null genotype during third pregnancy trimester was 2.4 (95% confidence interval = 1.1-5.4); the interaction odds ratio for CYP2E1 variant G-1295C (or allele *5) during the nursing period was 4.9 (95% confidence interval = 1.5-16.7). CONCLUSIONS: The observed association with maternal alcohol consumption during pregnancy could be due to the potential chemopreventive effects of flavonoids found in wine and beer. These possible effects of alcohol may be at least partially genetically determined, although data are preliminary.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".