Infant feeding practices and childhood acute leukemia: Findings from the Childhood Cancer & Leukemia International Consortium
Bibliographic record
Abstract
Increasing evidence suggests that breastfeeding may protect from childhood acute lymphoblastic leukemia (ALL) and acute myeloid leukemia (AML). However, most studies have limited their analyses to any breastfeeding, and only a few data have examined exclusive breastfeeding, or other exposures such as formula milk. We performed pooled analyses and individual participant data metaanalyses of data from 16 studies (N = 17 189 controls; N = 10 782 ALL and N = 1690 AML cases) from the Childhood Leukemia International Consortium (CLIC) to characterize the associations of breastfeeding duration with ALL and AML, as well as exclusive breastfeeding duration and age at introduction to formula with ALL. In unconditional multivariable logistic regression analyses of pooled data, we observed decreased odds of ALL among children breastfed 4 to 6 months (0.88, 95% CI 0.81-0.96) or 7 to 12 months (OR 0.85, 0.79-0.92). We observed a similar inverse association between breastfeeding ≥4 months and AML (0.82, 95% CI 0.71-0.95). Odds of ALL were reduced among children exclusively breastfed 4 to 6 months (OR 0.73, 95% CI 0.63-0.85) or 7 to 12 months (OR 0.70, 95% CI 0.53-0.92). Random effects metaanalyses produced similar estimates, and findings were unchanged in sensitivity analyses adjusted for race/ethnicity or mode of delivery, restricted to children diagnosed ≥1 year of age or diagnosed with B-ALL. Our pooled analyses indicate that longer breastfeeding is associated with decreased odds of ALL and AML. Few risk factors for ALL and AML have been described, therefore our findings highlight the need to promote breastfeeding for leukemia prevention.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.019 | 0.039 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.012 |
| Bibliometrics | 0.005 | 0.008 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 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".