Pediatric Germ Cell Tumors and Maternal Vitamin Supplementation: a Children's Oncology Group Study
Bibliographic record
Abstract
Maternal vitamin supplementation has been linked to a reduced risk of several pediatric malignancies. We examined this relationship in a study of childhood germ cell tumors (GCT). Subjects included 278 GCT cases diagnosed <15 years during 1993 to 2001 at a United States or Canadian Children's Oncology Group Institution and 423 controls that were ascertained through random digit dialing matched to cases on sex, and age within 1 year. Unconditional logistic regression was used to estimate odds ratios (OR) and 95% confidence intervals (CI) for the association between GCTs and maternal vitamin use at several time points during and around pregnancy. In models controlling for the child's age, sex, household income, and maternal education, any maternal vitamin use during the 6 months before conception through nursing was associated with a nonsignificant reduced risk of GCTs (OR, 0.7; 95% CI, 0.4-1.2). Inverse associations were observed for both extragonadal (OR, 0.8; 95% CI, 0.4-1.6) and gonadal (OR, 0.6; 95% CI, 0.3-1.1) tumors, and for dysgerminoma/seminoma (OR, 0.6; 95% CI, 0.2-1.3) and teratoma (OR, 0.5; 95% CI, 0.2-0.9) but not yolk sac tumors (OR, 1.1; 95% CI, 0.5-2.3). No consistent patterns were found with respect to vitamin use during the periconceptional period (6 months before pregnancy and first trimester) or first trimester specifically. In conclusion, although our study suggests that maternal vitamin supplementation may reduce the risk or pediatric GCTs in the offspring, the small study size and limitations inherent to observational studies must be considered when interpreting 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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".