Pathological upgrading and upstaging of patients eligible for active surveillance according to currently used protocols
Bibliographic record
Abstract
OBJECTIVES: To investigate the ability of six contemporary active surveillance protocols to appropriately select active surveillance candidates among Korean men who underwent radical prostatectomy. METHODS: Between January 2001 and December 2011, 1968 patients underwent radical prostatectomy for prostate cancer at Samsung Medical Center, Seoul, Korea. Patients met the criteria for active surveillance according to six currently used criteria, including those from the Johns Hopkins Hospital, the University of Toronto, the University of California at San Francisco, the Prospective Prostate Cancer Research International Active Surveillance, the University of Miami and the Memorial Sloan-Kettering Cancer Center. The rates of Gleason score upgrading, upstaging and misclassification at final pathology were assessed. RESULTS: Among 1006 assessable patients, the percentage of men eligible for active surveillance varied from 13.5% to 38.5%, depending on the criteria used. The rates of upgrading ranged from 41.6% to 50.6%. Extracapsular extension was reported in 4.1% to 8.5% of patients, whereas seminal vesicle invasion was reported in 0.5% to 1.6% of patients. The upstaging rates according to the six active surveillance criteria varied from 4.5% to 9.3%, and the rates of misclassification varied from 44.5% to 54.8%. CONCLUSIONS: Currently available active surveillance criteria might not be suitable in Korean patients with prostate cancer, as they have a high likelihood of underestimating 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 | 0.005 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".