Maternal Supplementation with Folic Acid and Other Vitamins and Risk of Leukemia in Offspring
Bibliographic record
Abstract
BACKGROUND: Maternal prenatal supplementation with folic acid and other vitamins has been inconsistently associated with a reduced risk of childhood acute lymphoblastic leukemia (ALL). Little is known regarding the association with acute myeloid leukemia (AML), a rarer subtype. METHODS: We obtained original data on prenatal use of folic acid and vitamins from 12 case-control studies participating in the Childhood Leukemia International Consortium (enrollment period: 1980-2012), including 6,963 cases of ALL, 585 cases of AML, and 11,635 controls. Logistic regression was used to estimate pooled odds ratios (ORs) and 95% confidence intervals (CIs), adjusted for child's age, sex, ethnicity, parental education, and study center. RESULTS: Maternal supplements taken any time before conception or during pregnancy were associated with a reduced risk of childhood ALL; odds ratios were 0.85 (95% CI = 0.78-0.92) for vitamin use and 0.80 (0.71-0.89) for folic acid use. The reduced risk was more pronounced in children whose parents' education was below the highest category. The analyses for AML led to somewhat unstable estimates; ORs were 0.92 (0.75-1.14) and 0.68 (0.48-0.96) for prenatal vitamins and folic acid, respectively. There was no strong evidence that risks of either types of leukemia varied by period of supplementation (preconception, pregnancy, or trimester). CONCLUSIONS: Our results, based on the largest number of childhood leukemia cases to date, suggest that maternal prenatal use of vitamins and folic acid reduces the risk of both ALL and AML and that the observed association with ALL varied by parental education, a surrogate for lifestyle and sociodemographic characteristics.
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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 | 0.004 |
| 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 | 0.001 | 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".