Active surveillance in patients with a PSA >10 ng/mL
Bibliographic record
Abstract
INTRODUCTION: The use of prostate-specific antigen (PSA) in active surveillance (AS) for prostate cancer is controversial. Some consider it an unreliable marker and others as sufficient evidence to exclude patients from AS. We analyzed our cohort of AS patients with a PSA over 10 ng/mL. METHODS: We included patients who had clinical T1c-T2a Gleason ≤6 disease, and ≤3 positive cores with ≤50% core involvement at diagnostic biopsy and ≥2 total biopsies. Patients were divided into 3 groups: (1) those with baseline PSA >10 ng/mL, (2) those with a PSA rise >10 ng/mL during follow-up; and (3) those with a PSA <10 ng/mL throughout AS. Adverse histology was defined as biopsy parameters exceeding the entry criteria limits. We further compared this cohort to a concurrent institutional cohort with equal biopsy parameters treated with immediate radical prostatectomy. RESULTS: Our cohort included 698 patients with a median follow-up of 46.2 months. In total, 82 patients had a baseline PSA >10 ng/mL and 157 had a PSA rise >10 ng/mL during surveillance. No difference in adverse histology incidence was detected between groups (p = 0.3). Patients with a PSA greater than 10 were older and had higher prostate volumes. Hazard ratios for groups with a PSA >10 were protective against adverse histology. Larger prostate volume and minimal core involvement appear as factors related to this successful selection of patients to be treated with AS. CONCLUSION: These results suggest that a strict cut-off PSA value for all AS patients is unwarranted and may result in overtreatment. Though lacking long-term data and validation, AS appears safe in select patients with a PSA >10 ng/mL and low volume Gleason 6 disease.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".