Serum Markers in Patients with Resectable Pancreatic Adenocarcinoma: Macrophage Inhibitory Cytokine 1 versus CA19-9
Why this work is in the frame
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Bibliographic record
Abstract
PURPOSE: More accurate serum markers of pancreatic cancer could improve the early detection and prognosis of this deadly disease. We compared the diagnostic utility of a panel of candidate serum markers of pancreatic cancer. EXPERIMENTAL DESIGN: We collected preoperative serum from 50 patients with resectable pancreatic adenocarcinoma, as well as sera from 50 patients with chronic pancreatitis and 50 age/sex-matched healthy controls from our institution. Sera were analyzed for the following candidate markers of pancreatic cancer: CA19-9, macrophage inhibitory cytokine 1 (MIC-1), osteopontin, tissue inhibitor of metalloproteinase 1, and hepatocarcinoma-intestine-pancreas protein levels. RESULTS: By logistic regression analysis, MIC-1 and CA19-9 were significant independent predictors of diagnosis. Receiver operating characteristic curve analysis showed that MIC-1 was significantly better than CA19-9 in differentiating patients with pancreatic cancer from healthy controls (area under the curve is 0.99 and 0.78, respectively; P = 0.003), but not in distinguishing pancreatic cancer from chronic pancreatitis (area under the curve of 0.81 and 0.74, respectively; P = 0.63). Hepatocarcinoma-intestine-pancreas/pancreatitis-associated protein, osteopontin, and tissue inhibitor of metalloproteinase 1 serum levels did not provide additional diagnostic power. CONCLUSION: In the differentiation of patients with resectable pancreatic cancer from controls, serum MIC-1 outperforms other markers including CA19-9.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it