Grade and stage misclassification in intermediate unfavorable‐risk prostate cancer radiotherapy candidates
Bibliographic record
Abstract
BACKGROUND: We tested for upgrading (Gleason grade group [GGG] ≥ 4) and/or upstaging to non-organ-confined stage ([NOC] ≥ pT3/pN1) in intermediate unfavorable-risk (IU) prostate cancer (PCa) patients treated with radical prostatectomy, since both change the considerations for dose and/or type of radiotherapy (RT) and duration of androgen deprivation therapy (ADT). METHODS: We relied on Surveillance, Epidemiology, and End Results (2010-2015). Proportions of (a) upgrading, (b) upstaging, or (c) upgrading and/or upstaging were tabulated and tested in multivariable logistic regression models. RESULTS: We identified 7269 IU PCa patients. Upgrading was recorded in 479 (6.6%) and upstaging in 2398 (33.0%), for a total of 2616 (36.0%) upgraded and/or upstaged patients, who no longer fulfilled the IU grade and stage definition. Prostate-specific antigen, clinical stage, biopsy GGG, and percentage of positive cores, neither individually nor in multivariable logistic regression models, discriminated between upgraded and/or upstaged patients versus others. CONCLUSIONS: IU PCa patients showed very high (36%) upgrading and/or upstaging proportion. Interestingly, the overwhelming majority of those were upstaged to NOC. Conversely, very few were upgraded to GGG ≥ 4. In consequence, more than one-third of IU PCa patients treated with RT may be exposed to suboptimal dose and/or type of RT and to insufficient duration of ADT, since their true grade and stage corresponded to high-risk PCa definition, instead of IU PCa. Data about magnetic resonance imaging were not available but may potentially help with better stage discrimination.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.010 |
| 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 | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".