Birth Weight as a Risk Factor for Childhood Leukemia: A Meta-Analysis of 18 Epidemiologic Studies
Bibliographic record
Abstract
Evidence has emerged that childhood leukemia is initiated in utero. High birth weight is one of the few birth-related factors that has been associated with childhood leukemia, albeit not consistently. The authors conducted a meta-analysis of studies of the association between birth weight and childhood leukemia risk. Study-specific odds ratios for leukemia were calculated, using a cutoff at 4,000 g of birth weight. The authors also evaluated whether the association between birth weight and leukemia followed a log-linear dose-response-like pattern. They calculated summary estimates using weighted averages of study-specific odds ratios from dichotomous and trend analyses. Eighteen studies (published between 1962 and 2002) were included, encompassing 10,282 children with leukemia. Children weighing 4,000 g or more at birth were at higher risk of acute lymphoblastic leukemia than children weighing less (odds ratio (OR) = 1.26, 95% confidence interval (CI): 1.17, 1.37). Furthermore, data were consistent with a dose-response-like effect (OR = 1.14/1,000-g birth weight increase, 95% CI: 1.08, 1.20). Studies of acute myeloid leukemia indicated a similar increase in risk for children weighing 4,000 g or more at birth (OR = 1.27, 95% CI: 0.73, 2.20) and a dose-response-like effect (OR = 1.29/1,000 g, 95% CI: 0.80, 2.06), but results varied across studies. Our findings support a relation between birth weight and childhood acute lymphoblastic leukemia risk and emphasize the need for additional studies of the biologic mechanisms underlying this association.
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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 | 0.014 | 0.029 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.011 | 0.048 |
| Bibliometrics | 0.005 | 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 | 0.003 |
| 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".