Strategies for Biochemical and Pathologic Quality Assurance in a Large Multi-Institutional Biorepository; The Experience of the PROCURE Quebec Prostate Cancer Biobank
Bibliographic record
Abstract
Well-characterized, high-quality fresh-frozen prostate tissue is required for prostate cancer research. As part of the PROCURE Prostate Cancer Biobank launched in 2007, four University Hospitals in Quebec joined to bank fresh frozen prostate tissues from radical prostatectomies (RP). As the biobank progressed towards allocation, the nature and quality of the tissues were determined. RP tissues were collected by standardized alternate mirror-image or biopsy-based targeted methods, and frozen for banking. Clinical/pathological parameters were captured. For quality control, two presumed benign and two presumed cancerous frozen, biobanked tissue blocks per case (10/site) were randomly selected during the five years of collection. In a consensus meeting, 4 pathologists blindly evaluated slides (n=160) and graded quality, Gleason score (GS), and size of cancer foci. The quality of tissue RNA (37/40 cases) was assessed using the RNA Integrity Number. The biobank included 1819 patients of mean age: 62.1 years; serum PSA: 8 ng/ml; prostate weight: 47.8 g; GS: 7; and pathological stage: T2 in 64.5%, T3A in 25.5% and T3B in 10% of cases. Of the 157 evaluable slides, 79 and 78 had benign and cancer tissue, respectively. GS for the 37 cancer-positive cases were: 6 in 9, 7 in 18 and >7 in 10 and, in most instances, in concordance with final GS. In 40% of slides containing cancer, foci occupied ≥50% of block surface and 42% had a diameter ≥1 cm. Tissue was well preserved and consistently yielded RNA of very good quality with RNA Integrity Number (RIN) >7 for 97% of cases (mean=8.7 ± 0.7) during the five-year collection period. This study confirms the high quality of randomly selected benign and cancerous fresh-frozen prostate tissues of the PROCURE Quebec Prostate Cancer Biobank. These results strengthen the uniqueness of this large prospective resource for prostate cancer research.
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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 | 0.113 | 0.042 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.006 | 0.008 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".