Serial Plasma Osteopontin Levels Have Prognostic Value in Metastatic Breast Cancer
Bibliographic record
Abstract
PURPOSE: Osteopontin is a malignancy-associated protein measurable in blood and tumor tissue. To evaluate its prognostic value in advanced disease, we conducted a prospective clinical study measuring serial osteopontin plasma levels in women with metastatic breast cancer throughout the course of their disease. EXPERIMENTAL DESIGN: One hundred fifty-eight women with newly diagnosed metastatic breast cancer were enrolled in the study. Plasma osteopontin was measured using our validated ELISA, at baseline and every 3 to 12 weeks during and after therapy until death. Multivariate time-dependent survival analyses were conducted using models that right censored patient outcomes 3, 6, and 12 months after the last known osteopontin measurement. RESULTS: Osteopontin was measured in 1,378 samples (median, 9 per patient). Ninety-nine patients had elevated baseline osteopontin (median, 177 ng/mL; range, 1-2,648 ng/mL). In univariate analysis, elevated baseline osteopontin was associated with short survival (P = 0.02). In a multivariate model incorporating standard prognostic factors, baseline osteopontin was significantly associated with survival duration (relative risk, 1.001; P = 0.038). Metastasis-free interval, visceral metastases, and Eastern Cooperative Oncology Group status 2 to 4 also retained significance. In a multivariate model incorporating standard prognostic factors and changes in sequential osteopontin levels, an osteopontin increase of >250 ng/mL at any time was the variable with the most prognostic value for poor survival (relative risk, 3.26; P = 0.0003), and poor Eastern Cooperative Oncology Group status also retained significance. CONCLUSIONS: This is the first study to show that in women with metastatic breast cancer, increases in osteopontin levels over time are strongly associated with poor survival. Sequential monitoring of osteopontin may have use in making treatment decisions for these patients.
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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 | 0.003 |
| 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".