Up- and downgrading in single intermediate-risk positive biopsy core prostate cancer
Bibliographic record
Abstract
Up- and/or downgrading rates in single intermediate-risk positive biopsy core are unknown. We identified single intermediate-risk (Gleason grade group (GGG) 2/GGG3) positive biopsy core prostate cancer patients (≤ cT2c and PSA ≤ 20 ng/mL) within the Surveillance, Epidemiology, and End Results (SEER) database (2010–2015). Subsequently, separate uni- and multivariable logistic regression models tested for independent predictors of up- and downgrading. Of 1,328 assessable patients with single core positive intermediate-risk prostate cancer at biopsy, 972 (73%) harbored GGG2 versus 356 (27%) harbored GGG3. Median PSA (5.5 vs 5.7; p = 0.3), median age (62 vs 63 years; p = 0.07) and cT1-stage (77 vs 75%; p = 0.3) did not differ between GGG2 and GGG3 patients. Of individuals with single GGG2 positive biopsy core, 191 (20%) showed downgrading to GGG1 versus 35 (4%) upgrading to GGG4 or GGG5 at RP. Of individuals with single GGG3 positive biopsy core, 36 (10%) showed downgrading to GGG1 versus 42 (12%) significant upgrading to GGG4 or GGG5 at RP. In multivariable logistic regression models, elevated PSA (10–20 ng/mL) was an independent predictor of upgrading to GGG4/GGG5 in single GGG3 positive biopsy core patients (OR:2.89; 95%-CI: 1.31–6.11; p = 0.007). In single GGG2 positive biopsy core patients, downgrading was four times more often recorded compared to upgrading. Conversely, in single GGG3 positive biopsy core patients, up- and downgrading rates were comparable and should be expected in one out of ten patients.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".