Effects of de-escalated bisphosphonate therapy on bone turnover biomarkers in breast cancer patients with bone metastases
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
While de-escalation of bisphosphonates from 4 to 12-weekly dosing has been shown to be clinically non-inferior to standard dosing, there is evidence the de-escalation is associated with increased bone turnover biomarkers. Here we evaluated the effect of de-escalated dosing on a panel of biomarkers and determined their association with incidence of skeletal related events (SREs) in breast cancer patients with 'low risk' bone metastases. As part of a pilot randomized trial, women with baseline C-telopeptide levels <600 ng/L after >3 months of 3-4 weekly pamidronate were randomized to continue pamidronate every 4 weeks or de-escalation to 12-weekly treatment. Serum was analysed for bone biomarkers (C-telopeptide, N-telopeptide, bone-specific alkaline phosphatase, transforming growth factor-β, procollagen type 1 N-propeptide, activinA and bone sialoprotein) using ELISA. The associations between changes in biomarkers, pain scores and SREs were assessed by univariable logistic regression. Numerical increases in all biomarkers were observed between baseline and 12 weeks but were of higher magnitude in the de-escalated arm. Pain scores in the de-escalated treatment arm showed a greater magnitude of pain reduction from baseline to 12 weeks. Neither baseline levels nor changes in biomarkers from baseline to 12 weeks on treatment were associated with on study SREs. Baseline pain as measured by the FACT-BP was associated with increased risk of SRE. In conclusion, biomarkers of bone activity do not appear to predict for SREs in 'low risk' cohorts. However, baseline bone pain appears to be associated with SRE occurrence, a finding which warrants evaluation in larger cohorts.
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 | 0.000 | 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 it