Maternal Vitamin Use and Reduced Risk of Neuroblastoma
Bibliographic record
Abstract
BACKGROUND: Previous studies have suggested that maternal vitamin use during pregnancy may reduce the incidence of childhood brain tumors. Using data from a large North American study, we conducted an analysis to investigate maternal vitamin use and neuroblastoma in offspring. METHODS: Cases were children diagnosed with neuroblastoma over the period 1 May 1992 to 30 April 1994 at Children's Cancer Group and Pediatric Oncology Group institutions throughout the United States and Canada. One matched control was selected for each case using random-digit dialing. We obtained vitamin use information during specific periods before and during pregnancy from 538 case and 504 control mothers through telephone interviews. RESULTS: Daily vitamin and mineral use in the month before pregnancy and in each trimester was associated with a 30-40% reduction in risk of neuroblastoma. For example, daily use in the second trimester had an odds ratio of 0.6 (95% confidence interval = 0.4-0.9). We were unable to isolate the effects of specific vitamins or minerals. Neither age at diagnosis nor oncogene amplification status materially altered the results. CONCLUSIONS: The results of this study suggest that vitamin use during pregnancy might reduce incidence of neuroblastoma, consistent with findings for other childhood cancers.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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) | 0.001 | 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".