Denosumab: A New Injectable Treatment for Postmenopausal Osteoporosis
Bibliographic record
Abstract
Background/Introduction: Osteoporosis results in a significant increase in fractures, leading to morbidity and mortality. Adherence is a concern with commonly used antiresorptive agents, the bisphosphonates. Denosumab, which inhibits bone resorption by a different mechanism and is administered subcutaneously every 6 months, may provide an advantage in decreasing fracture risk in those with osteoporosis. Objective: To review the available data with respect to the mechanism of action, efficacy and safety of denosumab for the management of postmenopausal osteoporosis. Methods: Several databases were searched to identify phase III randomized controlled trials (RCT) that examined the effect of denosumab on bone mineral density (BMD) and/or fracture rate and the safety of denosumab in the management of postmenopausal osteoporosis. Results: In 2 of the 4 trials identified, denosumab was significantly better than placebo at increasing BMD, and in 1 trial reduced the risk of vertebral, nonvertebral and hip fractures. No head-to-head trials comparing fracture risk reduction of denosumab to bisphosphonates were found, however, 2 trials did report increased BMD with denosumab compared to alendronate. In the 4 studies reviewed, adverse effects reported more frequently with denosumab included rash and eczema, as well as bronchitis and influenza-like illness. There is potential for an increased risk of other infections and malignancies. Conclusions: The results of RCT trials suggest that denosumab is effective at maintaining or increasing BMD compared to placebo or alendronate in women with either osteopenia or osteoporosis and in 1 trial demonstrated a significant reduction in fracture rate compared to placebo. Overall, denosumab appeared to be well tolerated in the studies reviewed. Continued monitoring is needed to determine long-term safety and efficacy.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.004 |
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".