Correlation of N-telopeptide of type I collagen (NTX) with survival and fractures in patients (pts) with bone metastases from renal cell carcinoma (RCC)
Bibliographic record
Abstract
e16016 Background: The osteolysis marker NTX has shown prognostic significance in pts with bone metastases from a broad range of solid tumors, but its potential in pts with RCC has not been investigated. Methods: This was an exploratory correlative analysis of NTX levels and outcomes in the RCC subset of pts treated with zoledronic acid (ZOL) in a 21-month phase III trial (Rosen et al. J Clin Oncol. 2002). In North American pts in this study, urinary NTX was measured approximately every 3 mo and was expressed per mmol creatinine (CR). Endpoints included overall survival (OS), disease progression in bone, and pathologic fractures. Relative risks and 95% confidence intervals for pts with elevated NTX (NTX ≥ 64 nmol/mmol CR) versus normal NTX (< 64 nmol/mmol CR) were calculated by Cox regression for baseline and most recent (≤ 6 mo prior) NTX assessments. Results: Among 55 ZOL-treated RCC pts, 29 had baseline NTX data (median = 60 nmol/mmol CR). Whereas baseline NTX levels showed trends for outcomes, recent NTX levels profoundly correlated with outcomes ( Table ). An elevated recent NTX measurement correlated with a > 13-fold increased risk of death and a > 11-fold increased risk of progression in bone. Correlations were also significant for first and all on-study fractures. Conclusions: In pts with RCC receiving ZOL, serial NTX assessments may provide important prognostic insight. Although based on a small sample size, correlations between recent NTX levels and outcomes in RCC pts are more profound than those previously reported in pts with other solid tumors (Brown et al. J Natl Cancer Inst. 2005). Elevated NTX could alert physicians to the need to more closely monitor bone lesions and intervene to prevent fractures in RCC pts. This may be especially important in the context of new systemic therapies that are improving the outlook in the advanced RCC setting. [Table: see text] [Table: see text]
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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".