Mammographic densities and the prevalence and incidence of histological types of benign breast disease
Why this work is in the frame
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Bibliographic record
Abstract
There is now a large amount of evidence indicating that women with extensive areas of mammographic densities are 4-6 times more likely to develop breast cancer than those with little or no density in the mammogram. We have examined one potential biological explanation for this association by estimating the incidence of various histological types of benign breast disease in relation to mammographic density. We studied the large cohort of women taking part in the National Breast Screening Study (NBSS), a randomized trial of screening with mammography. Mammograms from subjects with biopsies (n = 423) and from a comparison group of subjects randomly selected from the NBSS (n = 465) were included. Histological slides from biopsied subjects (n = 353) were classified independently by the pathologists of the NBSS and by a review pathologist (H.M.J.). Mammographic density in more than 75% of the breast area was associated with an increased risk of incidence of hyperplasia without atypia, and of atypical hyperplasia and/or carcinoma in situ. The classifications of the review pathologist showed that, compared to women with no density, the relative risk of incident lesions for women with density in more than 75% of breast was 13.85 (95% CI 2.65-72.49) for hyperplasia, and 9.23 (95% CI 1.66-51.48) for atypical hyperplasia and/or carcinoma in situ. These findings suggest that the association between extensive mammographic density and breast cancer risk may, at least in part, be attributable to biological processes in the breast that give rise to these histological features that are known to be related to breast cancer risk.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| 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 it