Pharmacotherapy of bone metastases in breast cancer patients – an update
Bibliographic record
Abstract
INTRODUCTION: Bone metastases in breast cancer patients are a common clinical problem and pose a threat to the quality of life of such patients. Multiple randomized trials have demonstrated the benefit of both bisphosphonates and denosumab in reducing the incidence and delaying the onset of skeletal related events (SREs) in breast cancer patients with bone metastases. AREAS COVERED: We review the current literature on the use of bisphosphonates and denosumab along with strategies to maximize benefit and minimize risk of these agents. We also review potential future targets. EXPERT OPINION: Despite the potent osteoclast inhibiting effects of the bone-targeted agents in current clinical use, we have likely maximized their ability to inhibit SREs and must in turn focus on minimizing their potential toxicity. The future will likely involve more novel treatment strategies as well as the development of new agents. The current 'one size fits all' approach for the management of breast cancer bone metastases will be replaced by 'tailored' treatment for each individual patient as we usher in the era of 'personalized medicine.' In addition, new bone-targeted agents (e.g., sclerostin inhibitors) and combinations will continue to be explored, as will the evaluation of the bone-targeting properties of more conventional non-osteoclast targeting therapies.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".