Bone remodeling in postmenopausal women who discontinued denosumab treatment: Off-treatment biopsy study
Bibliographic record
Abstract
Denosumab is a fully human monoclonal antibody that neutralizes the activity of RANKL, leading to the inhibition of osteoclast maturation, bone-resorbing activity, and survival. Evaluation of trans-iliac crest bone biopsy specimens in the phase 3 pivotal fracture study with denosumab in postmenopausal women with osteoporosis showed evidence of reduced bone turnover at the tissue level in subjects receiving denosumab, and up to one-third of subjects did not have evidence of tetracycline labeling in trabecular or cortical bone. Discontinuation of denosumab therapy has demonstrated that the effects of denosumab are reversible, as assessed by biochemical markers of bone turnover (BTM) and BMD. The precise nature of changes that occur at the tissue level with denosumab discontinuation have not been explored. Fifteen subjects were enrolled in a cohort study to evaluate the effects of denosumab discontinuation at the tissue level. Subjects had discontinued osteoporosis treatment for a mean time of 25.1 months (range 21 to 29 months). Bone histomorphometry results were compared with results from placebo-treated women with osteoporosis in the denosumab phase 3 pivotal fracture bone biopsy substudy, and BTMs were compared with subjects' pretreatment values. The results of this study showed normal histology and bone remodeling similar to those observed in untreated postmenopausal women with osteoporosis. With treatment cessation, 100% of biopsy specimens had evidence of tetracycline labels. Biochemical markers were comparable to and highly correlated with pretreatment levels. These data confirm that the effects of denosumab on bone turnover at the tissue level are fully reversible.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".