Bone-marker levels in patients with prostate cancer: potential correlations with outcomes
Bibliographic record
Abstract
PURPOSE OF REVIEW: The skeleton is typically the first site of metastasis in patients with prostate cancer, and bone metastases can result in severe bone pain and potentially debilitating fractures. Although bone scans are a reliable means of assessing osteoblastic lesions, tools for monitoring early changes in bone health are lacking. Biochemical markers of bone turnover might fulfill this unmet need. RECENT FINDINGS: Correlative studies have suggested that bone-marker levels may have utility in assessing disease progression and response to bone-directed therapy. Elevated levels of the markers, N-telopeptide of type I collagen and bone-specific alkaline phosphatase, are associated with higher rates of death and skeletal-related events in the bone metastasis setting. Marker levels also correlate with response to zoledronic acid treatment, and similar data with the investigational agent, denosumab, are emerging. SUMMARY: Changes in bone-marker levels reflect alterations in skeletal homeostasis and can provide important insights into bone disease progression and response to bone-directed therapy in patients with prostate cancer. More mature data from currently ongoing clinical trials will provide further insight on the utility of marker assessments as an adjunct to established monitoring methods in prostate cancer.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".