Bone-Targeted Agents and Skeletal-Related Events in Breast Cancer Patients with Bone Metastases: The State of the Art
Bibliographic record
Abstract
Most women with advanced breast cancer will develop bone metastases, which are associated with the development of skeletal-related events (sres) such as pathologic fractures and spinal cord compression. This article reviews the evolving definition and incidence of sres, the pathophysiology of bone metastases, and the key evidence for the safety and efficacy of the currently available systemic treatment options for preventing and delaying sres in the setting of breast cancer with bone metastases.The bisphosphonates are structural analogues of endogenous pyrophosphate; three of them (clodronate, pamidronate, and zoledronate) are currently approved for use in Canada in the setting of breast cancer with bone metastases. Denosumab is a fully human immunoglobulin G2 monoclonal antibody that binds to human rankl (receptor activator of nuclear factor κB ligand), thereby preventing osteoclast formation, function, and survival, and reducing cancer-induced destruction of bone. Denosumab has recently been approved in Canada for reducing the risk of sres from the bone metastases associated with a variety of malignancies, including breast cancer. How to predict the patients that will benefit most from prophylactic treatment, the agents to select and the timing of switches between agents, the dosing schedules and durations of treatment to choose, the potential utility of the agents in the adjuvant setting, and the utility of additional endpoints such as markers of bone resorption are among the outstanding questions with respect to the optimal use of antiresorptive agents for patients with breast cancer and bone metastases.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".