Predictors of clinical outcome in patients with bone metastases from prostate cancer
Bibliographic record
Abstract
4555 Background: Bone metastases are a significant cause of morbidity in patients with prostate cancer (PC). To assess the predictive value of bone markers and fractures for clinical outcome in patients with bone metastases from PC, we conducted a retrospective analysis of patients in a large, randomized, controlled trial of zoledronic acid. Methods: Data were analyzed in patients treated with 4 mg zoledronic acid or placebo who had bone marker (n = 411) or fracture (n = 640) information. Cox regression models, adjusted for treatment group, were used to assess the association between bone markers (urinary N-telopeptide [NTX] and bone alkaline phosphatase [BALP]) or fractures (time-dependent variable) and the risk of death or of experiencing a first skeletal-related event (SRE) on study. For bone marker analyses, patients were grouped by low (< 50 nmol/mmol creatinine), moderate (50 to 99), or high (≥ 100) NTX levels and by low (< 146 U/L) or high (≥ 146) BALP. Results: Patients who experienced a fracture on study (19%) had shorter survival compared with patients who did not; the hazard ratio for death was 1.29 (95% CI = 1.01, 1.65; P = .04), suggesting 29% increased risk of death among these patients. When adjusted for previous SRE and baseline ECOG performance status ≥ 2, the risk for death associated with fractures was increased by 23% and trended toward statistical significance (P = .10). Patients with high NTX levels had significantly increased risk of SREs and disease progression (P < .001) compared with patients with low NTX. Relative to low NTX levels, high and moderate NTX levels were associated with a 5.72-fold (95% CI = 4.04, 8.11; P < .001) and 4.10-fold (95% CI = 2.81, 5.97; P < .001) increased risk of death, respectively. High BALP also significantly correlated with an increased risk of a first on-study SRE (P = .028) and bone lesion progression (P < .001). Conclusions: These analyses suggest that pathologic fractures are associated with increased risk if death and that high bone marker levels are associated with increased risk of SREs, bone lesion progression, and shorter survival in patients with PC and bone metastases. The results support appropriate treatment for the prevention of fractures and to decrease bone marker levels. [Table: see text]
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".