The probability of Gleason score upgrading between biopsy and radical prostatectomy can be accurately predicted
Bibliographic record
Abstract
The objective of this study was to test the external validity of a previously developed nomogram for the prediction of Gleason score upgrading (GSU) between biopsy and radical prostatectomy (RP). The study population consisted of 973 assessable patients treated with RP at a tertiary care institution. The accuracy of the nomogram was quantified with the receiver operating characteristics curve-derived area under the curve. The performance characteristics (predicted vs observed rate of GSU) were tested within a calibration plot. Overall, GSU was recorded in 39.8% (n = 387) of patients at RP. Of patients with GSU, 70 (18.1%), 23 (5.9%) and 32 (8.3%), respectively, had extracapsular extension, seminal vesicle invasion and lymph node invasion. The accuracy of the nomogram was 74.9% (confidence interval 72.1-77.6%). The model tended to underestimate the observed rate of GSU and the discordance between the predicted and observed rate of GSU ranged from -7 to +10%. The current tool represents the most accurate method of predicting GSU between biopsy and RP. Nonetheless it is not perfect and its performance characteristics should be known prior to its use in clinical decision-making.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".