Comparison of histologic grade between initial and follow-up biopsy in untreated, low to intermediate grade, localized prostate cancer.
Bibliographic record
Abstract
OBJECTIVE: To examine the change of histologic grade of untreated, low to intermediate grade, clinically localized prostate cancer over time on repeat prostate biopsy. METHODS AND MATERIALS: In a prospective single-arm cohort study, patients were managed with observation alone unless they met pre-defined criteria of disease progression (PSA, clinical or histologic progression). Sixty-seven (54%) of a total of 123 eligible patients underwent follow-up prostate biopsy. Median time to the follow-up biopsy was 22 months (range: 7-60). RESULTS: On the follow-up biopsy, Gleason score was unchanged in 20 patients (30%), upgraded in 19 (28%), and downgraded in 27 (40%). Twenty-one (31%) had no malignancy on the follow-up biopsy. Sixteen (37%) of 43 patients with < or = 2 positive cores on the initial biopsy had negative follow-up biopsy, while only 2 (11%) out of 18 with > or = 3 positive cores on the initial biopsy did. Five (7%) patients were upgraded to Gleason score 8. There was no correlation between the extent of grade change and baseline variables (age, clinical stage, and initial PSA) as well as PSA doubling time. CONCLUSIONS: There was no consistent histologic upgrade on the follow-up biopsy at a median of 22 months in untreated, low to intermediate grade, clinically localized 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 | 0.001 | 0.003 |
| 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".