Bone-active drugs in premenopausal women with breast cancer under hormone-deprivation therapies
Bibliographic record
Abstract
BACKGROUND: Bone health management in premenopausal women with breast cancer (BC) under hormone-deprivation therapies (HDTs) is often challenging, and the effectiveness of bone-active drugs is still unknown. METHODS: This retrospective multicenter study included 306 premenopausal women with early BC undergoing HDTs. Bone mineral density (BMD) and morphometric vertebral fractures (VFs) were assessed 12 months after HDT initiation and then after at least 24 months. RESULTS: After initial assessment, bone-active drugs were prescribed in 77.5% of women (151 denosumab 60 mg/6 months, 86 bisphosphonates). After 47.0 ± 20.1 months, new VFs were found in 16 women (5.2%). Vertebral fracture risk was significantly associated with obesity (odds ratio [OR] 3.87, P = .028), family history of hip fractures or VFs (OR 3.21, P = .040], chemotherapy-induced menopause (OR 6.48, P < .001), preexisting VFs (OR 25.36, P < .001), baseline T-score less than or equal to -2.5 standard deviation (SD) at any skeletal site (OR 4.14, P = .036), and changes at lumbar and total hip BMD (OR 0.94, P = .038 and OR 0.88, P < .001, respectively). New VFs occurred more frequently in women untreated compared to those treated with bone-active drugs (14/69, 20.8% vs 2/237, 0.8%; P < .001) and the anti-fracture effectiveness remained significant after correction for BMI (OR 0.03; P < .001), family history of fractures (OR 0.03; P < .001), chemotherapy-induced menopause (OR 0.04; P < .001), and preexisting VFs (OR 0.01; P < .001). CONCLUSIONS: Premenopausal women under HDTs are at high risk of VFs in relationship with high BMI, densitometric diagnosis of osteoporosis, preexisting VFs, and family history of osteoporotic fractures. Vertebral fractures in this setting might be effectively prevented by bisphosphonates or denosumab.
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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 | 0.000 | 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 | 0.001 |
| 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".