Treatment with Denosumab Reduces the Incidence of New Vertebral and Hip Fractures in Postmenopausal Women at High Risk
Bibliographic record
Abstract
CONTEXT: The FREEDOM (Fracture REduction Evaluation of Denosumab in Osteoporosis every 6 Months) trial showed denosumab significantly reduced the risk of fractures in postmenopausal women with osteoporosis. OBJECTIVE: We evaluated the effect of denosumab on the incidence of new vertebral and hip fractures in subgroups of women at higher risk for these fractures. DESIGN: FREEDOM was a 3-yr, randomized, double-blind, placebo-controlled, phase 3 trial. PARTICIPANTS AND SETTING: Postmenopausal women (N = 7808) with osteoporosis were enrolled at 213 study sites worldwide. INTERVENTIONS: Subjects received s.c. denosumab (60 mg) or placebo every 6 months and daily supplements of calcium (≥1000 mg) and vitamin D (≥400 IU). MAIN OUTCOME MEASURES: This post hoc analysis evaluated fracture incidence in women with known risk factors for fractures including multiple and/or moderate or severe prevalent vertebral fractures, aged 75 yr or older, and/or femoral neck bone mineral density T-score of -2.5 or less. RESULTS: Compared with placebo, denosumab significantly reduced the risk of new vertebral fractures in women with multiple and/or severe prevalent vertebral fractures (16.6% placebo vs. 7.5% denosumab; P < 0.001). Similarly, denosumab significantly reduced the risk of hip fractures in subjects aged 75 yr or older (2.3% placebo vs. 0.9% denosumab; P < 0.01) or with a baseline femoral neck bone mineral density T-score of -2.5 or less (2.8% placebo vs. 1.4% denosumab; P = 0.02). These risk reductions in higher-risk individuals were consistent with those seen in patients at lower risk of fracture. CONCLUSIONS: Denosumab reduced the incidence of new vertebral and hip fractures in postmenopausal women with osteoporosis at higher risk for fracture. These results highlight the consistent antifracture efficacy of denosumab in patients with varying degrees of fracture risk.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 | 0.001 |
| 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".