Insufficient Milk Supply and Breast Cancer Risk: A Systematic Review
Bibliographic record
Abstract
BACKGROUND: An association between insufficient milk supply, the inability of a mother's breast milk to provide sufficiently for her infant, and breast cancer has been suggested by observations in animal models. To determine if an association has been reported in epidemiological studies of human breast cancer, a systematic review of the literature has been conducted. We also sought to identify the methodological limitations of existing studies to guide the design of any future prospective studies in this field. METHODOLOGY/PRINCIPAL FINDINGS: PubMed, EMBASE, Web of Science, BIOSIS, and CAB abstracts were searched. We selected any study that (1) assessed breast cancer in association with breastfeeding history and (2) examined the relationship between insufficient milk supply with breast cancer. Seven relevant studies were identified that met both criteria. There was statistically significant heterogeneity among the results which likely reflects clinically significant differences in definitions of insufficient milk supply and reference groups that were used. Among premenopausal women who had experienced insufficient milk supply, odds ratios (ORs) for breast cancer risk ranged from 0.9 to 16.3. Among postmenopausal women, ORs ranged from 0.6 to 6.7. Based on the range of odds ratios obtained in the studies reported in this review, it remains unclear if there is a true association between insufficient milk supply and breast cancer. CONCLUSIONS/SIGNIFICANCE: Although some studies have shown a strong positive association, there is no consistent evidence for an effect of insufficient milk supply on breast cancer risk. Exposure definitions are in need of improvement in order to focus on primary insufficient milk supply. Reference groups consisting of women who have successfully breastfed may also introduce positive bias (inflation of the odds ratio) into study results because of the protective effect of prolonged breastfeeding in the control group.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".