Early detection of prostate cancer with ultrasound-guided systematic needle biopsy.
Bibliographic record
Abstract
INTRODUCTION: Prostate biopsy strategies have greatly evolved over the past 2 decades. METHODS: We performed a literature review which addressed the initial and repeat biopsy schemes, pathologic risk factors for a positive repeat biopsy, and the ideal timing as well as the number of repeat biopsy sessions. RESULTS: Extended biopsy schemes (11-13 cores) should be used at initial and repeat biopsy. In the era of extended biopsy schemes, high-grade prostatic intraepithelial neoplasia no longer represents an independent predictor of prostate cancer on repeat biopsy. Conversely, the risk is appreciably increased with atypical small acinar proliferation, and its presence warrants a repeat biopsy, which may be performed as soon as the pathologic findings of the previous biopsy become available. Second and subsequent repeat biopsies carry a low detection yield. In most instances, the decision regarding the indications and the timing of a third or subsequent biopsy may be made after a 6 to 12 months interval following the repeat biopsy. CONCLUSION: Biopsy strategies and pathologic predictors of an increased risk of prostate cancer have appreciably changed over the past 2 decades.
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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 | 0.004 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".