Parental alcohol consumption and risk of leukemia in the offspring: a systematic review and meta-analysis
Bibliographic record
Abstract
Parental alcohol consumption before and during pregnancy has been linked to adverse outcomes in the offspring including leukemogenesis. We, therefore, aimed to systematically assess and quantitatively synthesize published data on the association of paternal consumption during preconception and maternal consumption during pregnancy with leukemia risk in childhood (0-14 years). Following Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, we searched PubMed (until February 2016) and the reference lists of the relevant studies. Observational studies examining the association between parental alcohol consumption and childhood leukemia were considered eligible. Data extracted from 39 case-control studies (over 16 000 leukemia cases and 30 000 controls) were pooled and summary-effect estimates were calculated. Subgroup analyses were carried out by main acute leukemia type [lymphoblastic or myeloid), cytogenetics/genetic polymorphisms, and specific alcohol beverages. We found a statistically significant dose-response association of any level of maternal alcohol consumption compared with nondrinking during pregnancy exclusively with acute myeloid leukemia (AML) [odds ratio (OR)moderate consumption: 1.64, 95% confidence intervals (CIs): 1.23-2.17 and ORhigh consumption: 2.36, 95% CI: 1.60-3.49]. In contrast, no association of paternal preconception consumption with any leukemia type was noted. In beverage-specific analyses, only a positive association of maternal wine drinking with childhood AML was found, which was more pronounced in analyses including only studies on infant leukemia (ORwine: 2.12, 95% CI: 1.16-3.90). The largest ever meta-analysis shows a sizeable, statistically significant dose-response association of maternal alcohol consumption during index pregnancy with AML risk. Future research exploring the role of genetic polymorphisms is anticipated to shed light on the underlying pathophysiology.
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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 | 0.008 | 0.023 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.014 | 0.030 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| 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".