Folic acid food fortification is associated with a decline in neuroblastoma
Bibliographic record
Abstract
BACKGROUND: Neuroblastoma, an embryonic tumor, is the second most common pediatric tumor and is the most prevalent extracranial solid tumor in children. Results of previous studies have suggested that maternal vitamin intake may decrease the risk of several childhood cancers. In January 1997, Canada began fortifying flour with folic acid for the prevention of neural tube defects. The effect of folic acid fortification on the rate of neuroblastoma in offspring is not known. METHODS: We investigated the rates of neuroblastoma (<1 year), acute lymphoblastic leukemia, and hepatoblastoma registered by the Pediatric Oncology Group of Ontario, which captures 95% of all pediatric cancers in Ontario, before and after the introduction of folate fortification. RESULTS: An interventional time series analysis showed that the incidence of neuroblastoma declined from 1.57 cases per 10,000 births before to 0.62 case per 10,000 births after folic acid fortification (P <.0001). The crude incidence rate ratio (0.40; 95% confidence interval, 0.25-0.64) remained significant after adjustment for both age and disease stage at diagnosis (adjusted incidence rate ratio, 0.38; 95% confidence interval, 0.23-0.62). In contrast, there was no significant change in the rate of infant acute lymphoblastic leukemia (incidence rate ratio, 0.97; 95% confidence interval, 0.41-2.27) or hepatoblastoma (incidence rate ratio, 0.81; 95% confidence interval, 0.35-1.89). CONCLUSIONS: Folic acid fortification was associated with a 60% reduction in neuroblastoma but was not associated with any change in the rate of infant acute lymphoblastic leukemia or hepatoblastoma. Further investigation is needed into the role of metabolism in the formation and prevention of neuroblastoma and other embryonically determined 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 | 0.004 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".