Maternal Supplement, Micronutrient, and Cured Meat Intake during Pregnancy and Risk of Medulloblastoma during Childhood: A Children's Oncology Group Study
Bibliographic record
Abstract
We conducted a case-control study of medulloblastoma/primitive neuroectodermal tumors of brain (PNET) to pursue findings related to vitamin and mineral supplements, micronutrients, and cured meat consumption during gestation. Mothers of 315 cases ages <6 years at diagnosis in 1991 to 1997 identified from the United States and Canada through the Children's Oncology Group and mothers of 315 controls selected by random-digit dialing were interviewed. In the periconception period of the index pregnancy, case mothers were less likely than control mothers to report use of multivitamins [adjusted odds ratio (OR), 0.7; 95% confidence interval (95% CI), 0.4-1.0; P = 0.08] and to be in the highest quartile of iron and folate intake from food and supplements combined (adjusted OR for iron, 0.5; 95% CI, 0.3-0.9; P(trend) = 0.008; adjusted OR for folate, 0.5; 95% CI, 0.3-0.9; P(trend) = 0.007). Case and control mothers had similar intakes of cured meats, although case mothers were more likely to have the combination of high cured meat and low vitamin C intake (OR, 1.5; 95% CI, 1.0-2.3; P = 0.08). The results of the study add to the evidence of a protective role for multivitamins, suggest a possible role for micronutrients early in pregnancy, and generally do not support an association between cured meats and medulloblastoma/PNET.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".