Effects of Denosumab Treatment and Discontinuation on Bone Mineral Density and Bone Turnover Markers in Postmenopausal Women with Low Bone Mass
Bibliographic record
Abstract
CONTEXT: Denosumab treatment for 24 months increased bone mineral density (BMD) and reduced bone turnover markers (BTM) in postmenopausal women. OBJECTIVE: The aim was to determine the effects of prior denosumab or placebo injections on BMD, BTM, and safety over 24 months after treatment discontinuation. DESIGN: We conducted an off-treatment extension of a phase 3, randomized, double-blind, parallel-group study. PARTICIPANTS: A total of 256 postmenopausal women with a mean age of 59 yr and a mean lumbar spine T-score of -1.61 at randomization participated in the study. INTERVENTIONS: Participants received placebo or 60 mg denosumab every 6 months for 24 months, followed by 24 months off treatment. MAIN OUTCOME MEASURES: We measured the percentage changes in BMD and BTM, and evaluated safety. RESULTS: Of the 256 participants enrolled in the posttreatment phase, 87% completed the study. During 24 months of denosumab treatment, BMD increased (lumbar spine, 6.4%; total hip, 3.6%; 1/3 radius, 1.4%), and BTM decreased (serum C-terminal telopeptide of type 1 collagen, 63%; and N-terminal propeptide of type 1 procollagen, 47%), compared with placebo. After discontinuation, BMD declined, but the previously treated denosumab group maintained higher BMD than the previously treated placebo group at these sites (P ≤ 0.05). Final BMD at month 48 strongly correlated with month 0 BMD. After denosumab discontinuation, BTM increased above baseline within 3 months (serum C-terminal telopeptide of type 1 collagen) or 6 months (N-terminal propeptide of type 1 procollagen) and returned to baseline by month 48. Adverse event rates during the off-treatment phase were similar between groups. CONCLUSIONS: In postmenopausal women with low BMD, the effects of 60 mg denosumab treatment for 24 months on BMD and BTM are reversible upon discontinuation, reflecting its biological mechanism of action. Residual BMD measurements remained above those of the group previously treated with placebo.
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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 | 0.003 | 0.004 |
| 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".