Optimizing Clinical Benefits of Bisphosphonates in Cancer Patients with Bone Metastases
Bibliographic record
Abstract
Bisphosphonates are important treatments for bone metastases. Considerations for optimizing the clinical benefits of bisphosphonates include efficacy, compliance, and safety. Several bisphosphonates are approved for clinical use; however, few have demonstrated broad efficacy in the oncology setting and been compared directly in clinical trials. Among patients with bone metastases from breast cancer, the efficacy of approved bisphosphonates was evaluated in a Cochrane review, showing a reduction in the risk of skeletal-related events (SREs) ranging from 8% to 41% compared with placebo. Between-trial comparisons are confounded by inconsistencies in trial design, SRE definition, and endpoint selection. Zoledronic acid has demonstrated clinical benefits beyond those of pamidronate in a head-to-head trial that included patients with breast cancer or multiple myeloma. Compliance and adherence also have effects on treatment efficacy. In a comparison study, the adherence rates with oral bisphosphonates were found to be significantly lower compared with those of intravenous bisphosphonates. The safety profiles of oral and intravenous bisphosphonates differ. Oral bisphosphonates are associated with gastrointestinal side effects, whereas intravenous bisphosphonates have dose- and infusion rate-dependent effects on renal function. Osteonecrosis of the jaw is an uncommon but serious event in patients receiving monthly intravenous bisphosphonates or denosumab. The incidence of this event can be reduced with careful oral hygiene. A positive benefit-risk ratio for bisphosphonates has been established, and ongoing clinical trials will determine whether individualized therapy is possible.
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".