Hypocalcaemia in patients with metastatic bone disease treated with denosumab
Bibliographic record
Abstract
BACKGROUND: This analysis was performed to further characterise treatment-emergent hypocalcaemia in patients with bone metastases receiving denosumab. METHODS: Laboratory abnormalities and adverse events of hypocalcaemia in patients with metastatic bone disease were analysed using data from three identically designed phase 3 trials of subcutaneous denosumab 120 mg (n = 2841) versus intravenous zoledronic acid 4 mg (n = 2836). RESULTS: The overall incidence of laboratory events of hypocalcaemia grade ⩾ 2 was higher with denosumab (12.4%) than with zoledronic acid (5.3%). Hypocalcaemia events were primarily grade 2 in severity and usually occurred within the first 6 months of treatment. Patients who reported taking calcium and/or vitamin D supplements had a lower incidence of hypocalcaemia. Prostate cancer or small-cell lung cancer, reduced creatinine clearance and higher baseline bone turnover markers of urinary N-telopeptide of type I collagen (uNTx; > 50 versus ⩽ 50 nmol/mmol) and bone-specific alkaline phosphatase (BSAP; > 20.77 μg/L [median] versus ⩽ 20.77 μg/L) values were important risk factors for developing hypocalcaemia. The risk associated with increased baseline BSAP levels was greater among patients who had > 2 bone metastases at baseline versus those with ⩽ 2 bone metastases at baseline. CONCLUSION: Hypocalcaemia was more frequent with denosumab versus zoledronic acid, consistent with denosumab's greater antiresorptive effect. Low serum calcium levels and potential vitamin D deficiency should be corrected before initiating treatment with a potent osteoclast inhibitor, and corrected serum calcium levels should be monitored during treatment. Adequate calcium and vitamin D intake appears to substantially reduce the risk of hypocalcaemia.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".