The effect of doxycycline on bone turnover and tumor markers in breast cancer (BC) patients with skeletal metastases
Bibliographic record
Abstract
3198 Background: Doxycycline is a tetracycline analogue which is osteotropic with high affinity for mineralized bone. In experimental systems, it has anti-cancer effects including inhibition of matrix metallo proteinases, anti-angiogenic activity and a cytostatic effect on cancer cells. Methods: 17 patients with newly diagnosed bone metastases from BC, and no prior bisphosphonate therapy were treated with Doxycycline 100 mg po bid for 3 months. Treatment was discontinued for disease progression or unacceptable toxicity. Bone scans and serum bone markers [N-telopeptide (NTx - Osteomark NTx Serum) and bone specific alkaline phosphatase (BAP - Metra BAP)] were measured as markers of bone turnover and PTHrP as a marker of tumor progression at baseline and following 12 weeks of therapy. Patients subsequently received bisphosphonate therapy. The primary outcome was a 50% relative decrease in serum bone markers. Results: 12 patients were evaluable for response, 3 patients discontinued therapy due to toxicity and were non-evaluable, and results are pending for 2 others. Median age was 62.5 years and 4 patients had other metastatic sites. 3 patients received concurrent chemotherapy and 9 patients hormonal treatment. There were no cases of pathological fractures or hypercalcemia. Results of the bone markers studies are shown below. 11 of 12 patients had normal serum NTx values and 5/12 had normal BAP at baseline despite extensive bone metastases. PTHrP levels in 9 of 12 patients either declined or remained at the same level after 12 weeks. Conclusions: Although Doxycycline for 3 months was associated with a drop in serum bone markers in some patients, it failed to satisfy the pre-specified outcome measure of a 50% decrease. A possible explanation is the lack of responsiveness of the outcome measure. Our study demonstrated the feasibility of administration of long-term Doxycycline. Further studies evaluating this agent are warranted. No significant financial relationships to disclose.
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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 | 0.000 | 0.001 |
| 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) | 0.001 | 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 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".