Prognostic Value of Prostate Secretory Protein of 94 Amino Acids and its Binding Protein after Radical Prostatectomy
Bibliographic record
Abstract
PURPOSE: To establish the prognostic value of total and free prostate secretory protein of 94 amino acids (PSP94) and the PSP94-binding protein (PSPBP) following radical prostatectomy. EXPERIMENTAL DESIGN: One hundred and eighty-five serum samples were obtained from patients with localized prostate cancer prior to treatment with radical prostatectomy at Virginia Urology (Richmond, VA). Patients were followed up for a median of 48 months (range, 1-66 months) and biochemical relapse was indicated as total prostate-specific antigen (tPSA) levels increasing to > 0.1 ng/mL. The available clinical variables included initial tPSA, Gleason score, surgical margin status, and clinical stage. Total PSP94, free PSP94, and the PSPBP were quantified in the pretreatment serum using new ELISA tests (Medicorp, Inc. and Ambrilia Biopharma, Inc., Montreal, Quebec, Canada). Univariate and multivariate Cox proportional hazards models were used to assess the ability of PSP94 and PSPBP to predict time to recurrence. RESULTS: Thirty-one patients had biochemical recurrence. Gleason score, margin status, clinical stage, and initial tPSA significantly predicted recurrence risk (all P < 0.001). In addition, PSPBP was negatively associated with recurrence risk (P = 0.005), and, consistent with previous studies, the bound/free PSP94 ratio was positively associated with recurrence risk (P = 0.008). Multivariate analysis showed that PSPBP, as well as the bound/free PSP94 ratio, were independent predictors of biochemical relapse risk adjusting for tPSA, Gleason score, and margin status. CONCLUSIONS: Bound/free PSP94 and PSPBP are novel and independent prognostic markers following radical prostatectomy for prostate cancer.
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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 | 0.002 |
| 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".