Safety Observations With 3 Years of Denosumab Exposure: Comparison Between Subjects Who Received Denosumab During the Randomized FREEDOM Trial and Subjects Who Crossed Over to Denosumab During the FREEDOM Extension
Bibliographic record
Abstract
Denosumab is a fully human monoclonal antibody against receptor activator of NF-κB ligand (RANKL) that decreases osteoclast formation, function and survival, and is approved for the treatment of postmenopausal women with osteoporosis at increased or high risk for fracture, among other indications. During the pivotal 3-year fracture trial FREEDOM, denosumab 60 mg subcutaneously every 6 months significantly reduced new vertebral (68%), hip (40%), and nonvertebral (20%) fractures; increased bone mineral density (BMD); and reduced bone turnover markers compared with placebo in postmenopausal women with osteoporosis. Questions have arisen regarding imbalances of certain low-frequency adverse events (AEs) observed in FREEDOM, as well as the top 5 most frequent adverse reactions listed in the United States prescribing information (USPI; back pain, pain in extremity, musculoskeletal pain, hypercholesterolemia, and cystitis). We examined the incidences of these AEs in women who originally received placebo during FREEDOM and then received denosumab for up to 3 years during the FREEDOM Extension (Crossover Group). This provided a unique opportunity for comparison with the original 3-year denosumab FREEDOM observations. We also examined the incidences of these AEs over 6 years of denosumab treatment (Long-term Group; ie, comparing a second 3 years of treatment with findings in the first 3 years). There was no indication of increasing trends regarding the imbalances of either low-frequency AEs or common AEs observed in FREEDOM. © 2017 American Society for Bone and Mineral Research.
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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 | 0.007 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".