Addition of cribriform pattern 4 and intraductal prostatic carcinoma into the CAPRA-S tool improves post-radical prostatectomy patient stratification in a multi-institutional cohort
Bibliographic record
Abstract
AIMS: Pre-surgical risk classification tools for prostate cancer have shown better patient stratification with the addition of cribriform pattern 4 (CC) and intraductal prostatic carcinoma (IDC) identified in biopsies. Here, we analyse the additional prognostic impact of CC/IDC observed in prostatectomies using Cancer of Prostate Risk Assessment post-surgical (CAPRA-S) stratification. METHODS: A retrospective cohort of treatment-naïve radical prostatectomy specimens from three North American academic institutions (2010-2018) was assessed for the presence of CC/IDC. Patients were classified, after calculating the CAPRA-S scores, into low-risk (0-2), intermediate-risk (3-5) and high-risk (6-12) groups. Kaplan-Meier curves were created to estimate biochemical recurrence (BCR)-free survival. Prognostic performance was examined using Harrell's concordance index, and the effects of CC/IDC within each risk group were evaluated using the Cox proportional hazards models. RESULTS: Our cohort included 825 prostatectomies (grade group (GG)1, n=94; GG2, n=475; GG3, n=185; GG4, n=13; GG5, n=58). CC/IDC was present in 341 (41%) prostatectomies. With a median follow-up of 4.2 years (range 2.9-6.4), 166 (20%) patients experienced BCR. The CAPRA-S low-risk, intermediate-risk and high-risk groups comprised 357 (43%), 328 (40%) and 140 (17%) patients, and discriminated for BCR-free survival (p<0.0001). For CAPRA-S scores 3-5, the addition of CC/IDC status improved stratification for BCR (HR 2.27, 95% CI 1.41 to 3.66, p<0.001) and improved the overall c-index (0.689 vs 0.667, analysis of variance p<0.001). CONCLUSION: The addition of CC/IDC into the CAPRA-S classification significantly improved post-radical prostatectomy patient stratification for BCR among the intermediate-risk group (CAPRA-S scores 3-5). The reporting of CC and IDC should be included in future prostate cancer stratification tools for improved outcome prediction.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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".