Plasma osteopontin
Bibliographic record
Abstract
BACKGROUND: Osteopontin (OPN) is a secreted glycoprotein that is detectable in human body fluids. Its increased expression has been found in many malignancies, and a stimulatory effect on human prostate carcinoma cells in vitro has been demonstrated. Plasma OPN levels have been associated with tumor burden and survival in patients with metastatic breast carcinoma. The authors explored these associations in men with hormone-refractory prostate carcinoma (HRPC). METHODS: Plasma samples from 100 men with HRPC were collected. OPN was measured using an antigen-capture enzyme-linked immunosorbent assay technique. Multivariable analyses were performed to identify predictors of OPN and survival. RESULTS: At the time of OPN sampling, the median patient age was 73 years (range, 50-86 years), and 92% of patients had metastases. The median plasma OPN level was 198.5 ng/mL (range, 15.0-2363.0 ng/mL), the median prostate specific antigen level was 67.8 microg/L (range, 0.1-7550.0 microg/L), and the median survival was 13.7 months. OPN plasma levels were higher in patients with versus patients without bone metastases (P = 0.024). Multivariable modeling demonstrated an independent association of the OPN level with alkaline phosphatase, hemoglobin, and creatinine levels. The log-transformed OPN level (hazard ratio [HR], 2.38; P < 0.0001), performance status (HR, 2.43; P = 0.007), and a history of prior radiotherapy for localized prostate carcinoma (HR, 0.48; P = 0.0229) were independent predictors of survival in a Cox multivariate model. CONCLUSIONS: In this study, in men with established HRPC, the plasma OPN level was associated with the presence of metastases to bone and with other measures of tumor burden, and it was correlated independently and negatively with survival.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".