Physical activity, mammographic density, and age-related lobular involution among premenopausal and postmenopausal women
Bibliographic record
Abstract
OBJECTIVE: Physical activity may protect against breast cancer by modulating breast tissue composition. We evaluated the association of physical activity with two visual assessments of breast tissue composition-percentage of mammographic density (a radiologic observation) and age-related lobular involution (a histologic assessment). METHODS: Among 164 premenopausal and postmenopausal women with breast cancer, physical activity (household, occupational, and recreational) performed during the year preceding the diagnosis was evaluated using a validated questionnaire. Percentage of mammographic density was assessed in the contralateral breast by a computer-assisted method. Age-related lobular involution was assessed in normal breast tissue on H&E-stained slides. Multivariate generalized linear models were used to assess associations by quartiles of physical activity. RESULTS: Overall, we observed no significant association between total physical activity and percentage of mammographic density or degree of lobular involution. However, occupational physical activity was significantly positively associated with the predominant type I/no type III lobules among premenopausal women (last quartile: prevalence ratio [PR], 5.92; P(trend )= 0.04). Although total physical activity was positively associated with the predominant type I/no type III lobules among premenopausal women (last quartile: PR, 2.61; P(trend) = 0.08), an inverse association was observed among postmenopausal women (last quartile: PR, 0.44; P(trend) = 0.01). Higher levels of household physical activity were significantly associated with higher prevalence of lower mammographic density and complete involution among postmenopausal women (last quartile: PR, 1.21; P(trend) = 0.01). CONCLUSIONS: Physical activity may be associated with less dense and more involuted breasts. Physical activity's effect on mammographic density or age-related lobular involution may mediate, in part, its protective effect against breast cancer.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".