Denosumab and changes in bone turnover markers during androgen deprivation therapy for prostate cancer
Bibliographic record
Abstract
Androgen deprivation therapy (ADT) for prostate cancer increases fracture risk, decreases bone mineral density, and increases bone turnover markers (BTMs) including serum type 1 C-telopeptide (sCTX), tartrate-resistant alkaline phosphatase 5b (TRAP-5b), and procollagen-1 N-terminal telopeptide (P1NP). In a prespecified exploratory analysis of a phase 3, multicenter, double-blind study, we evaluated the effects of denosumab (60 mg subcutaneously every 6 months for 3 years) versus placebo (1468 patients, 734 in each group) on BTM values. BTMs were measured at baseline, month 1, and predose at months 6, 12, 24, and 36 in the overall population. BTMs at month 1 are also reported for subgroups based on age (< 70 years versus ≥ 70 years), prior duration of ADT (≤ 6 months versus > 6 months), and baseline BTM (≤ median versus > median BTM values). Treatment with denosumab provided a rapid and sustained decrease of BTM values compared with placebo. The median change in sCTX levels at month 1 was -90% in the denosumab group and -3% in the placebo group (p < 0.0001). The median change in TRAP-5b levels at month 1 was -55% in the denosumab group and -3% in the placebo group (p < 0.0001). The maximal median change in P1NP was -64% in the denosumab group and -11% in the placebo group, (p < 0.0001). Significantly greater decreases in BTM for denosumab were also seen in subgroup analyses based on age, prior ADT treatment, and baseline BTM values. Suppression of bone turnover markers was consistent with marked increases in bone mineral density reported previously.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".