A phase 2 trial exploring the clinical and correlative effects of combining doxycycline with bone-targeted therapy in patients with metastatic breast cancer
Bibliographic record
Abstract
BACKGROUND: Bone-targeting agents (BTAs), such as bisphosphonates and denosumab, have demonstrated no discernable effects on tumour response or disease free/overall survival in patients with bone metastases from breast cancer. Doxycycline is both osteotropic and has anti-cancer effects. When combined with zoledronate in animal models, doxycycline showed significantly increased inhibition of tumour burden and increased bone formation. We evaluated the effects of adding doxycycline to ongoing anti-cancer therapy in patients with metastatic breast cancer. METHODS: Breast cancer patients with bone metastases and ≥3 months of BTA use, entered this single-arm study. Patients received doxycycline 100 mg orally, twice a day for 12 weeks. The co-primary endpoints were; effect on validated pain scores (FACT-Bone pain and Brief Pain Inventory) and bone resorption markers (serum C-telopeptide, [sCTx]). All endpoints (pain scores, sCTx, bone-specific alkaline phosphatase, skeletal-related events, toxicity) were evaluated at baseline, 4, 8 and 12 weeks. Bone marrow was sampled at baseline and week 12 for exploratory biomarker analysis. RESULTS: Out of 37 enroled patients, 27 (73%) completed 12 weeks of therapy. No significant changes were seen in pain scores or bone turnover markers. Failure to complete treatment: drug toxicity (70%) and disease progression (30%). Sixteen (43%) patients had GI adverse events. CONCLUSIONS: Doxycycline 100 mg twice daily for 12 weeks had no significant effects on either bone pain or bone turnover markers. Its toxicity profile in this patient population would make further evaluation challenging.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".