Serum sonic hedgehog (SHH) and interleukin-(IL-6) as dual prognostic biomarkers in progressive metastatic breast cancer
Bibliographic record
Abstract
Serum from one hundred and ten breast cancer patients and thirty healthy female volunteers, were prospectively collected and evaluated for serum levels of Shh and IL-6 using human Shh and IL-6 specific enzyme-linked immunoassays. All patients were regularly monitored for event free survival (EFS) and overall survival (OS). Overall outcome analysis was based on serum Shh and IL-6 levels. In patients with progressive metastatic BC, both serum Shh and IL-6 concentrations were elevated in 44% (29 of 65) and 63% (41 of 65) of patients, respectively, at a statistically significant level [Shh (p = 0.0001) and IL-6 (p = 0.0001)] compared to the low levels in healthy volunteers. Serum levels tended to increase with metastatic progression and lymph node positivity. High serum Shh and IL-6 levels were associated with poor EFS and OS opposite to the negative or lower levels in serum Shh and IL-6. The elevated levels of both serum Shh and IL-6 were mainly observed in BC patients who had a significantly higher risk of early recurrence and bone metastasis, and associated with a worse survival for patients with progressive metastatic BC. Further studies are warranted for validating these biomarkers as prognostic tools in a larger patient cohort and in a longer follow-up study.
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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 | 0.001 | 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) | 0.000 | 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".