The Role of Molecular Forms of Prostate-Specific Antigen (PSA or hK3) and of Human Glandular Kallikrein 2 (hK2) in the Diagnosis and Monitoring of Prostate Cancer and in Extra-Prostatic Disease
Bibliographic record
Abstract
Prostate-specific antigen (PSA or hK3) is a glandular kallikrein with abundant expression in the prostate that is widely used to detect and monitor prostate cancer (PCa), although the serum level is frequently elevated also in benign and inflammatory prostatic diseases. PSA testing is useful for early detection of localized PCa and for the detection of disease recurrence after treatment. However, PSA has failed to accurately estimate cancer volume and preoperative staging. There is no PSA level in serum that definitively distinguishes men with benign conditions from those with prostate cancer, although PCa is rare in men with PSA levels in serum < 2.0 ng/ml. This prompted searches for enhancing parameters to combine with PSA testing, such as PSA density, PSA velocity, and age-specific reference ranges. Due to the protease structure, PSA occurs in different molecular forms in serum and their concentrations vary according to the type of prostatic disease. Human glandular kallikrein 2 (hK2) is very similar to PSA, but expressed at higher levels in prostate adenocarcinoma than in normal prostate epithelium. Blood testing for hK2 combined with different PSA forms improves discrimination of men with benign prostatic disease from those with prostate cancer. Many data have also been reported on the extra-prostatic expression of both PSA and hK2, and it is now believed that they may both have functions in tissues outside the prostate.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".