Prenatal Multivitamin Supplementation and Rates of Pediatric Cancers: A Meta-Analysis
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Prenatal supplementation of folic acid has been shown to decrease the risk of several congenital malformations. Several studies have recently suggested a potential protective effect of folic acid on certain pediatric cancers. The protective role of prenatal multivitamins has not been elucidated. We conducted a systematic review and meta-analysis to assess the potential protective effect of prenatal multivitamins on several pediatric cancers. Medline, PubMed, EMBASE, Toxline, Healthstar, and Cochrane databases were searched for studies published in all languages from 1960 to July 2005 on multivitamin supplementation and pediatric cancers. References from all articles collected were reviewed for additional articles. Two blinded independent reviewers assessed the articles for inclusion and exclusion. Rates of cancers in women supplemented with multivitamins were compared with unsupplemented women using a random effects model. Sixty-one articles were identified in the initial search, of which, seven articles met the inclusion criteria. There was an apparent protective effect for leukemia (odds ratio (OR)=0.61, 95% confidence interval (CI)=0.50-0.74), pediatric brain tumors (OR=0.73, 95% CI=0.60-0.88) and neuroblastoma (OR=0.53, 95% CI=0.42-0.68). In conclusion, maternal ingestion of prenatal multivitamins is associated with a decreased risk for pediatric brain tumors, neuroblastoma, and leukemia. Presently, it is not known which constituent(s) among the multivitamins confer this protective effect.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| 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 | 0.001 | 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 it