Preoperative Plasma Endoglin Levels Predict Biochemical Progression After Radical Prostatectomy
Bibliographic record
Abstract
PURPOSE: Endoglin (CD105) is a transmembrane glycoprotein expressed by human vascular endothelial cells thought to play a pivotal role in endothelial cell proliferation. The aim of this study was to evaluate the association of preoperative plasma endoglin levels with established clinical and pathologic features of prostate cancer and disease progression after radical prostatectomy. EXPERIMENTAL DESIGN: Preoperative plasma endoglin levels were measured in 425 patients who underwent radical prostatectomy for clinically localized prostate cancer using a commercially available ELISA assay. Multivariate logistic regression was used to test the association of plasma endoglin levels with biochemical progression after radical prostatectomy. RESULTS: Median follow-up for patients alive at the time of analysis was 36.8 months (interquartile range, 44.1). Of 425 patients, 77 patients (18.1%) experienced biochemical progression after radical prostatectomy. Preoperative plasma endoglin levels were significantly elevated in patients with higher preoperative total serum prostate-specific antigen (P < 0.001) and adverse pathologic features. Preoperative plasma endoglin was an independent predictor of biochemical progression after surgery after adjusting for the effects of standard preoperative and postoperative features (P < 0.001 and P = 0.026, respectively). CONCLUSIONS: Preoperative plasma endoglin levels are associated with established features of advanced prostate cancer. More importantly, higher preoperative plasma endoglin levels are independent predictors of an increased risk of biochemical progression in patients treated with radical prostatectomy and bilateral pelvic lymphadenectomy.
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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".