Aromatase inhibitors and mammographic breast density in postmenopausal women receiving hormone therapy
Bibliographic record
Abstract
In Brief Objective: One of the main concerns regarding long-term use of hormone therapy (HT) in symptomatic menopausal women is the perceived increased risk of breast cancer. A method to reduce breast cancer risk in this population of women is urgently needed. We hypothesized that adding aromatase inhibitors (AIs) to HT would reduce local breast estrogen exposure and breast cancer risk without altering the beneficial systemic effects of HT on menopausal symptoms or bone density. The aim of this study was to investigate the effect of AIs and HT on mammographic breast density (MBD) as a surrogate marker of breast cancer risk in postmenopausal women receiving low-dose HT. Design: This was a retrospective cohort study conducted at private clinics affiliated with a university hospital. One group of postmenopausal women (n = 28) received low-dose HT daily plus letrozole 2.5 mg three times weekly. Postmenopausal women receiving HT alone (n = 28) served as controls. MBD, the primary outcome, was measured using quantitative image analysis software as well as by visual analysis by a radiologist. Hypoestrogenic effects, adverse reactions, and bone mineral densities were secondary outcome measures. Results: The mammograms of 18 women in the study group and 22 women in the control group were suitable for comparison. A statistically significant reduction in MBD occurred in the women who received HT plus an AI, whereas no significant change was observed in the women receiving HT alone. There was no significant increase in hypoestrogenic symptoms during the use of AIs, and bone mineral densities were not significantly reduced. Conclusions: Adding an AI to HT may lower MBD in postmenopausal women. AIs could be good candidates for primary chemoprevention of breast cancer in postmenopausal women using HT. This study investigated the effect of adding an aromatase inhibitor to current hormone therapy in healthy postmenopausal women at increased risk of breast cancer. A significant reduction in mammographic breast density was found, with no significant hypoestrogenic side effects, in the study group compared with a group of control women who received hormone therapy alone.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".