A phase II, multicentre trial evaluating the efficacy of de-escalated bisphosphonate therapy in metastatic breast cancer patients at low-risk of skeletal-related events
Bibliographic record
Abstract
The optimal frequency of intravenous (IV) bisphosphonate administration is unclear. We thus performed a study evaluating the effects of switching from 3-4 to 12 weekly therapy in patients with biochemically defined low-risk bone metastases. Patients with serum C-telopeptide (CTx) levels ≤600 ng/L after ≥3 months of 3-4 weekly IV pamidronate were switched to 12 weekly therapy for 48 weeks. Primary endpoint was the proportion of patients maintaining CTx levels in the lower-risk range. All endpoints (serum CTx and bone-specific alkaline phosphatase (BSAP), skeletal-related events (SREs) and self-reported pain) were measured at baseline, 6, 12, 24, 36 and 48 weeks. Treatment failure was defined as biochemical failure (CTx > 600 ng/L) or a SRE. Exploratory biomarkers including; serum TGF-β, activin-A, bone sialoprotein (BSP), procollagen type 1 N-terminal propeptide and urinary N-telopeptide (NTx) were assessed at baseline as predictors for failure to complete treatment. Seventy-one patients accrued and 43 (61 %) completed 48 weeks of de-escalated therapy. Reasons for failure to complete treatment included; biochemical failure (CTx > 600 ng/L) (n = 10, 14.1 %), on-study SRE (n = 9, 12.7 %), disease progression (n = 7, 9.9 % including death from disease [n = 1, 1.4 %]) or patient choice (n = 2, 2.8 %). Elevated baseline levels of CTx, BSAP, NTx and BSP were associated with treatment failure. The majority of patients in this biochemically defined low-risk population could switch from 3-4 weekly to 12 weekly bisphosphonate therapy with no effect on CTx levels or SREs during the 48 week study. Larger trials are required to assess the roles of biomarkers as predictors of adequacy of de-escalated therapy.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| 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".