Downgrading of biopsy based Gleason score in prostatectomy specimens
Bibliographic record
Abstract
AIMS: To assess the frequency and possible causes of downgrading from a Gleason score (GS) 7 at biopsy to a GS ≤6 at radical prostatectomy (RP) in a Canadian referral centre. METHODS: Data were extracted from diagnostic reports of inhouse biopsies and matching prostatectomy specimens from 2008 to 2011 with a GS 7 at biopsy. Biopsies and corresponding prostatectomy specimens of downgraded cases were reviewed. Pathological features were assessed and possible predictors for downgrading were identified. RESULTS: Based on pathology reports, 29 (8.9%, 95% CI 5.8% to 11.9%) of the 327 eligible cases were downgraded from biopsy GS 7 to RP GS 6, 72% of them representing a GS ≤6 with tertiary grade 4 at RP. Agreement at review of downgraded RP specimens for Gleason grading was fair and of borderline significance (κ=0.34, 95% CI -0.01 to 0.68, p=0.055) with 65% agreement for tertiary grade. The predominant Gleason grade 4 pattern found in the downgraded biopsies was ill-formed glands. The number of cores with Gleason grade 4 component was found to be the strongest negative predictor of downgrading (prereview OR=0.56 (95% CI 0.39 to 0.80, p=0.002), postreview OR=0.19 (95% CI 0.07 to 0.52, p=0.001)). CONCLUSIONS: The frequency of GS 7 in biopsies subsequently downgraded in RP is low and is associated with International Society of Urological Pathology modified Gleason grade 4 patterns. Downgrading could be attributed in most cases to the presence of a tertiary Gleason grade 4 pattern in the RP specimen. Inter-observer agreement for the presence of tertiary grade 4 in RP specimens is moderate.
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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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".