A systematic review of dosing frequency with bone-targeted agents for patients with bone metastases from breast cancer
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Bone-targeted agents are usually administered to breast cancer patients with bone metastases every 3-4 weeks. Less frequent ('de-escalated') treatment may provide similar benefits with improved safety and reduced cost. METHODS: To systematically review randomised trials comparing de-escalated treatment with bone-targeted agents (i.e. every 12-16 weeks) to standard treatment (i.e. every 3-4 weeks), a formal systematic review of the literature was performed. Two individuals independently screened citations and full text articles. Random effects meta-analyses of clinically important outcomes were planned provided homogeneous studies were identified. RESULTS: Five relevant studies (n=1287 patients) were identified. Sample size ranged from 38 to 425. Information on outcomes including occurrence of SREs, bone pain, urinary N-telopeptide concentrations, serum C-telopeptide concentrations, pain medication use and safety outcomes was not consistently available. Two trials were non-inferiority studies, two dose-response evaluations and one was a pilot study. Bone-targeted agents use varied between studies, as did duration of prior therapy. Patient populations were considered heterogeneous in several ways, and thus no meta-analyses were performed. Observations from the included studies suggest there is potential that 3 month de-escalated treatment may provide similar benefits compared to 3-4 weekly treatment and that lower doses of zoledronic acid and denosumab might be equally effective. CONCLUSIONS: Studies comparing standard and de-escalated treatment with bone-targeted agents in breast cancer are rare. The benefits of standard treatment compared to de-escalated therapy on important clinical outcomes remain unclear. Future pragmatic studies must be conducted to determine the merits of this approach.
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.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.011 | 0.001 |
| 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 | 0.001 |
| 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 it