Predictive Value of Bone Resorption and Formation Markers in Cancer Patients With Bone Metastases Receiving the Bisphosphonate Zoledronic Acid
Bibliographic record
Abstract
PURPOSE: Three large, randomized trials of patients with bone metastases recently demonstrated that zoledronic acid reduces the risk of skeletal-related events. These trials provide an opportunity for investigating the correlation between bone metabolism and clinical outcome during bisphosphonate therapy. PATIENTS AND METHODS: Urinary measurements of N-telopeptide (Ntx) and serum bone alkaline phosphatase (BAP) were obtained in 1,824 bisphosphonate-treated patients-1,462 with zoledronic acid (breast, 490; prostate, 411; myeloma, 210; non-small-cell lung, 183; other, 168) and 362 with pamidronate (breast, 254; myeloma, 108). This exploratory cohort analysis grouped patients by baseline and most recent levels of Ntx as low (< 50 nmol/mmol creatinine), moderate (50 to 99 nmol/mmol creatinine), or high (> or = 100 nmol/mmol creatinine), and BAP as low (< 146 U/L) or high (> or = 146 U/L). The relative risks for negative clinical outcomes were estimated for each group using multiple-event and Cox regression models with time-varying covariates. RESULTS: Patients with high and moderate Ntx levels had 2-fold increases in their risk of skeletal complications and disease progression compared with patients with low Ntx levels (P < .001 for all). High Ntx levels in each solid tumor category were associated with a 4- to 6-fold increased risk of death on study, and moderate Ntx levels a 2- to 4-fold increased risk compared with low Ntx levels (P < .001 for all). Bone alkaline phosphatase also showed some correlation with risk of negative clinical outcomes. CONCLUSION: The bone resorption marker Ntx provides valuable prognostic information in patients with bone metastases receiving bisphosphonates.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".