Undetected Cribriform and Intraductal Prostate Cancer at biopsy is associated with adverse outcomes
Bibliographic record
Abstract
Abstract Background Intraductal carcinoma (IDC) and cribriform pattern (Crib) of prostate cancer are increasingly recognised as independent prognosticators of poor outcome, both in prostate biopsies and radical prostatectomy (RP) specimens. Objective The aim of our project is to assess the impact of false negative biopsies for these two characteristics on oncological outcomes. Material and Methods Patients who underwent RP between January 2015 and December 2022 were included in the study. Predictors of Biochemical Failure were examined using a multivariate Cox proportional hazards model. Results and Limitation Among the 836 patients who underwent RP, 233 (27.9%) had Crib, and 125 (15.0%) had IDC on prostate biopsy, with 71 (8.5%) patients having both IDC and Crib. Concerning, IDC/Crib status at biopsy, 217 (26%) patients had a false-negative biopsy, 332 (39.7%) had a true-negative biopsy, 256 (30.6%) showed a true-positive biopsy, and 24 (3.7%) exhibited a false-positive biopsy, with respect to either pattern. When comparing false-negative, false-positive, true-negative and true-positive biopsies for IDC/Crib, we found that patients with a false-negative biopsy for IDC/Crib versus those with a true-negative biopsy for IDC/Crib disclosed a rate of advanced pathological stage (≥ pT3) which was twice that of patients with a true-negative biopsy for IDC/Crib: 56.8% versus 28.1%, respectively (p < 0.001). On multivariate Cox analysis, log PSA before RP (hazard ratio [HR] 2.07, 95% CI 1.53–2.82; p < 0.001), a higher percentage of positive cores at biopsy (≥ 33%) (HR 1.68, 95% CI 1.07–2.63; p = 0.024), and false negative biopsy for IDC/Crib (HR 2.14, 95% CI 1.41–3.25; p < 0.001), were each significantly associated with an increased risk of BCR. Conclusions A false-negative biopsy for IDC/Crib is independently associated with higher risk of BCR and advanced pathological stage compared to a true negative biopsy.
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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 | 0.006 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".