Effects of denosumab on bone mineral density and bone turnover in postmenopausal women transitioning from alendronate therapy
Bibliographic record
Abstract
Patients treated with bisphosphonates for osteoporosis may discontinue or require a switch to other therapies. Denosumab binds to RANKL and is a potent inhibitor of bone resorption that has been shown to increase bone mineral density (BMD) and decrease fracture risk in postmenopausal women with osteoporosis. This was a multicenter, international, randomized, double-blind, double-dummy study in 504 postmenopausal women > or = 55 years of age with a BMD T-score of -2.0 or less and -4.0 or more who had been receiving alendronate therapy for at least 6 months. Subjects received open-label branded alendronate 70 mg once weekly for 1 month and then were randomly assigned to either continued weekly alendronate therapy or subcutaneous denosumab 60 mg every 6 months and were followed for 12 months. Changes in BMD and biochemical markers of bone turnover were evaluated. In subjects transitioning to denosumab, total hip BMD increased by 1.90% at month 12 compared with a 1.05% increase in subjects continuing on alendronate (p < .0001). Significantly greater BMD gains with denosumab compared with alendronate also were achieved at 12 months at the lumbar spine, femoral neck, and 1/3 radius (all p < .0125). Median serum CTX levels remained near baseline in the alendronate group and were significantly decreased versus alendronate (p < .0001) at all time points with denosumab. Adverse events and serious adverse events were balanced between groups. No clinical hypocalcemic adverse events were reported. Transition to denosumab produced greater increases in BMD at all measured skeletal sites and a greater reduction in bone turnover than did continued alendronate with a similar safety profile in both groups.
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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) | 0.001 | 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".