Prenatal exposure to medication and risk of childhood cancer – a systematic review and meta-analysis
Bibliographic record
Abstract
BACKGROUND: The use of medication during pregnancy carries a potential health risk, including childhood cancer, for the unborn child. However, most drugs examined in previous observational studies have shown inconsistent results with the risk of childhood cancer, and these findings have not been consolidated in drug-specific meta-analyses. METHODS: We conducted a systematic search in the databases PubMed and Web of Science for studies on medication use during pregnancy and childhood cancer risk. Studies with exposure to diethylstilbestrol as a known teratogen were excluded. Meta-analyses were conducted if ≥ 3 studies on the same research question were available to calculate pooled estimates for random effects models with 95% confidence intervals (CI). The I2 statistic was calculated to quantify between-study heterogeneity. Statistical significance of I2 was analyzed using Q statistic (P value for heterogeneity (P)). Study quality was assessed with a scoring tool adapted from the Newcastle–Ottawa Scale and ROBINS-E/I. RESULTS: Of 2,366 identified studies, 80 were included in the systematic review. Of these, 68 studies with a total of 14,396,922 participants were included in meta-analyses, covering 13 medication types and 11 childhood cancer sites across 70 analyses. From 54 site-specific analyses, we observed four risk reductions and eleven increases in risk. We found an increased risk for prenatal exposure to any kind of antibiotics and acute lymphoblastic leukemia (ALL; estimate (ES) = 1.14 (95%CI 1.03; 1.25), I2 = 19.1%, P = 0.26). For specific antibiotics, nitrosatable antibiotics were associated with an increased risk of childhood cancer overall (ES = 1.32 (1.13; 1.55), I2 = 0.0%, P = 0.98). Maternal intake of vitamin and mineral supplements was associated with a reduced risk of acute leukemia (AL) (ES = 0.72 (0.54; 0.96), I2=46.3%, P = 0.16), ALL (ES = 0.81 (0.67; 0.99), I2 = 66.6%, P = 0.001) and tumors of the central nervous system (CNS; ES = 0.77 (0.62; 0.96), I2 = 67.2%, P = 0.002). DISCUSSION: Our results suggest that the use of antibiotics during pregnancy was associated with an increased childhood cancer risk, although this association is likely influenced by the underlying maternal infections that required treatment. This highlights the importance of considering maternal health factors when interpreting medication–related associations. Supplementation of vitamins and minerals during pregnancy might decrease the risk of AL, ALL and CNS tumors in children.
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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 | 0.012 | 0.030 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.018 | 0.045 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".