Pancreatic cancer serum biomarker PC-594: Diagnostic performance and comparison to CA19-9
Bibliographic record
Abstract
AIM: To investigate serum PC-594 fatty acid levels as a potential biomarker in North American pancreatic cancer (PaC) patients, and to compare its performance to CA19-9. METHODS: Using tandem mass spectrometry, we evaluated serum PC-594 levels from 84 North American patients with confirmed PaC and 99 cancer-free control subjects. We determined CA19-9 levels by ELISA. Significance between PaC patients and controls, and association with clinical variables was determined by analysis of variance and t-tests. Diagnostic performance was evaluated by receiver-operator characteristic (ROC) curve analysis, and PC-594 correlation with age and CA19-9 determined by regression analysis. RESULTS: Mean PC-594 levels were 3.7 times lower in PaC patients compared to controls (P < 0.0001). The mean level in PaC patient serum was 0.76 ± 0.07 μmol/L, and the mean level in control subjects was 2.79 ± 0.15 μmol/L. There was no correlation between PC-594 and age, disease stage or gender (P > 0.05). Using 1.25 μmol/L as a PC-594 threshold produced a relative risk (RR) of 9.4 (P < 0.0001, 95%CI: 5.0-17.7). The area under the receiver-operator characteristic curve (ROC-AUC) was 0.93 (95%CI: 0.91-0.95) for PC-594 and 0.85 (95%CI: 0.82-0.88) for CA19-9. Sensitivity at 90% specificity was 87% for PC-594 and 71% for CA19-9. Six PaC patients with CA19-9 above 35 U/mL showed normal PC-594 levels, while 24 PaC patients with normal CA19-9 showed low PC-594 levels. Eighty-five of the 99 control subjects (86%) showed normal levels of both markers. CONCLUSION: PC-594 biomarker levels are significantly reduced in North American PaC patients, and showed superior diagnostic performance compared to CA19-9.
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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".