Variation in the interaction between familial and reproductive factors on the risk of breast cancer according to age, menopausal status, and degree of familiality
Bibliographic record
Abstract
BACKGROUND: Studies have found that reproductive factors might have a variable effect on the occurrence of breast cancer (BC) according to the existence or not of a family history of BC. The effect of a family history of BC on the risk of BC may also vary according to the age at diagnosis and the degree of kinship. This may confound the relation between familial risk and reproductive factors. A combined analysis was performed to study the interaction between familial risk and reproductive factors according to degree of familiality, age at interview and menopausal status. METHODS: The present analysis included 2948 cases and 4170 controls in seven case-control studies from four countries. The combined relative risks were estimated using a Bayesian random-effects logistic regression model. RESULTS: The main effects of reproductive life factors on the risk of BC are in agreement with previous studies. Two-way interactions between subject's age or menopausal status and a family history of BC were not significant. Although the three-way interaction between age, familial risk and parity was not significant, familial risk seemed to be increased slightly for women with high parity compared with women with low parity in the older age group, and seemed to be slightly decreased for women with high parity compared with women with low parity in younger women. The subject's age also appeared to have an effect on the interaction between familial risk and the age at first childbirth (P = 0.1). CONCLUSIONS: A possible influence of reproductive and menstrual factors on familial risk of BC has been suggested previously and was also evident in the present study. Three-way interactions between age, family history and parity or age at first childbirth might exist and they merit further investigation.
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".