The use of kallikrein-related peptidases as adjuvant prognostic markers in colorectal cancer
Bibliographic record
Abstract
Several members of the human tissue kallikrein-related peptidase (KLK) family are emerging cancer biomarkers. The aim of this study was to analyse the expression of a panel of KLKs in colorectal cancer and to find out if the multiparametric combination of them can increase the accuracy of prediction of patients survival beyond the traditional clinical information. Nine KLKs (KLK5-8, KLK10, KLK11, KLK13-15) were measured using ELISA assays in cytosolic extracts of 122 colon cancer tissues and their nearby normal mucosa, obtained during surgery. The mean levels of almost all KLKs in tumour tissues were significantly different from their counterparts of normal tissue (P<0.0001). KLK 5, 6, 7, 13, 14 were significantly associated with overall survival in univariate analysis, but after adjusting for age, TNM and differentiation stage, only KLK5 (HR: 1.24 (95% CI: 1.05-1.47)), KLK7 (HR: 1.57 (95% CI: 1.04-2.37)) and KLK14 (HR: 1.43 (95% CI: 1.05-1.94)) remained significant. Addition of a panel of selected KLK markers to clinical parameters gave an increment in AUC of 0.86 beyond the clinical factors at year 1, showing that it can increase the accuracy of prediction of overall survival beyond the traditional clinical information, particularly the short-term (1 year) survival after surgery.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| 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".