The Effect of Loss of Estrogen on Trabecular Bone Score in Women at Increased Risk of Breast Cancer
Bibliographic record
Abstract
In states of estrogen deficiency bone loss is evident. We investigated two interventions that cause estrogen deprivation in the setting of breast cancer prevention: 1) prophylactic salpingo- oophorectomy, being the surgical removal of the ovaries and fallopian tubes, and 2) exemestane therapy, which prevents estrogen synthesis in the body. In the literature, bone density loss following these interventions has been studied; however, bone density does not encompass all aspects of bone strength. Our aim was to investigate bone loss after these interventions using a novel measure which assesses bone architecture termed trabecular bone score (TBS). We hypothesized that due to estrogen depletion by prophylactic salpingo-oophorectomy and exemestane, a greater loss in TBS would be observed. One year following prophylactic salpingo-oophorectomy and two years on exemestane did not cause significant loss in TBS. Based on our findings, the clinical use of TBS for detecting small changes in bone is not warranted.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.002 |
| 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) | 0.002 | 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".