Predictive value of prostatic adenocarcinoma after a negative prostate biopsy
Bibliographic record
Abstract
OBJECTIVE: To investigate the predictive value (PV) for all prostate cancers and for clinically significant cancer undiagnosed after a 10-core biopsy protocol, as the 10-core transrectal ultrasonography-guided biopsy is considered the standard technique of prostatic biopsy due to its high rate of detection of prostatic adenocarcinoma. PATIENTS AND METHODS: In all, 132 consecutive radical prostatectomy (RP) specimens, with their corresponding 10-core biopsies, were reviewed. Cases with unilateral core involvement by prostate cancer were retained for study. Morphometric analysis was conducted on the biopsy-negative hemi-prostates to determine the PV of the biopsy protocol with respect to the size, position and clinical significance of the lesion. RESULTS: In all, 70 resected prostates (RP) had unilateral core involvement by prostate cancer. In 38 cases, there was cancer in the biopsy-negative hemi-prostates (group 1); in the remaining 32 the hemi-prostates were free of cancer (group 2). Group 1 was categorized by morphometric criteria. Specifically, 23 cases had one to eight foci of prostate cancer in the posterior nontransitional zone (NTZ) (group 1a), while 15 had two to six foci of prostate cancer in the transitional zone (TZ), or the anterior horn (AH) of the peripheral zone or the TZ and AH (group 1b). There were two cases with clinically significant prostate cancer in group 1a, and six in group 1b. CONCLUSIONS: The PV of a negative five-core biopsy protocol on a hemi-prostate is 54% for prostate cancer and 11% for clinically significant prostate cancer. Most clinically significant prostate cancers were in the AH/TZ of 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 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".