Denosumab, a new pharmacotherapy option for postmenopausal osteoporosis
Bibliographic record
Abstract
BACKGROUND: According to the 2010 Osteoporosis Canada Clinical Practice Guidelines, denosumab is a first-line option for the pharmacological management of postmenopausal osteoporosis (PMO), along with several therapeutics that may be more familiar to family practice doctors: bisphosphonates, raloxifene, teriparatide, and hormone therapy. Denosumab is indicated for postmenopausal patients at high risk for fracture or others who have failed, or are intolerant to, other osteoporosis therapies. SCOPE: We undertook a review of the efficacy and safety of denosumab in PMO, searching the English-language literature on this drug via PubMed queries as of July 2012. FINDINGS: Although established treatments reduce fracture risk among osteoporotic postmenopausal women in trials, their effectiveness in clinical practice is limited by patient adherence. Twice-yearly denosumab treatment is associated with markedly improved bone mineral density (BMD) and cortical and trabecular bone strength, and significantly reduced osteoporotic fracture. Inhibition of bone resorption is fully reversible following discontinuation. Placebo-controlled and open-label extension studies showed similar adverse event (AE) and serious AE rates, relative to placebo, over up to 5 years. Data indicate a potential advantage of denosumab over the bisphosphonate alendronate for BMD and patient adherence and preference. CONCLUSION: Owing to its efficacy, safety, and potential to improve adherence rates, denosumab is an appropriate first-line pharmacologic option for PMO management.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".