Pain outcomes in patients with advanced breast cancer and bone metastases
Bibliographic record
Abstract
BACKGROUND: In this study, the authors evaluated the effect of denosumab versus zoledronic acid (ZA) on pain in patients with advanced breast cancer and bone metastases. METHODS: The prevention of pain, reduction in pain interference with daily life activities, and the proportion of patients requiring strong opioid analgesics were assessed in a randomized, double-blind, double-dummy phase 3 study comparing denosumab with ZA for preventing skeletal-related events in 2046 patients who had breast cancer and bone metastases. Patients completed the Brief Pain Inventory-Short Form at baseline and monthly thereafter. RESULTS: Fewer patients who received denosumab reported a clinically meaningful worsening of pain severity (≥2-point increase) from baseline compared with patients who received ZA, and a trend was observed toward delayed time to pain worsening with denosumab versus ZA (denosumab, 8.5 months; ZA, 7.4 months; P = .08). In patients who had no/mild pain at baseline, a 4-month delay in progression to moderate/severe pain was observed with denosumab compared with ZA (9.7 months vs 5.8 months; P = .002). Denosumab delayed the time to increased pain interference by approximately 1 month compared with ZA (denosumab, 16.0 months; ZA, 14.9 months; P = .09). The time to pain improvement (P = .72) and the time to decreased pain interference (P = .92) were similar between the groups. Fewer denosumab-treated patients reported increased analgesic use from no/low use at baseline to strong opioid use. CONCLUSIONS: Denosumab demonstrated improved pain prevention and comparable pain palliation compared with ZA. In addition, fewer denosumab-treated patients shifted to strong opioid analgesic use.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".