Biopsies Performed at Tertiary Care Centers are Superior to Referral Biopsies in Predicting Pathologic Gleason Sum
Bibliographic record
Abstract
OBJECTIVE: Biopsy grading at tertiary care centers may or may not be superior to biopsies performed at referral institutions. METHODS: Referral biopsy and tertiary care center biopsy Gleason sums were studied in 758 men treated with radical prostatectomy (RP) at a tertiary care center between 1992 and 2004. Grade agreement was calculated using the Cohen kappa (ê). Logistic regression models predicting high-grade prostate cancer at RP were fitted using either referral or tertiary care center biopsies. Comparison of bootstrap-corrected predictive accuracy estimates were performed using the Mantel-Haenszel test. RESULTS: Grade agreement between biopsy and RP Gleason sum was higher (P = 0.003) for tertiary care center biopsies v referral biopsies (55.5% v 47.9%; P = 0.003). Upgrading occurred in 39.8% of referral biopsies v 32.6% of tertiary care center biopsies (P = 0.03). Tertiary care center biopsies were more accurate in determining RP Gleason sum than referral biopsies (71.5% v 65.6%, P = 0.04). CONCLUSION: More accurate prediction of RP Gleason grade may be achieved if biopsy is performed and graded at tertiary care centers.
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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 | 0.004 | 0.030 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".