Clinicopathologic relevance of EpCAM and CD44 in pancreatic cancer: insights from a meta-analysis
Bibliographic record
Abstract
Recent evidence suggests that EpCAM and CD44 could serve as diagnosis or prognosis markers in pancreatic cancer (PC). In this meta-analysis, we evaluated their associations with clinicopathologic features. Specifically, we compared immunohistochemical-positive and -negative PC patients for T stage (T3-T4 vs. T1-T2), N stage (N1 vs. N0), M stage (M1 vs. M0), tumor grade (well/moderately vs. poorly differentiated), UICC Stage (III, IV vs. I, II), and overall survival (OS). The diagnostic meta-analysis was performed analysing the pooled sensitivity and specificity and evaluating overall accuracy to indicate the diagnostic efficacy of the markers. The protocol of this systematic review and meta-analysis was registered on the PROSPERO website under the registration number of CRD42024568390. A systematic search of PubMed, Scopus, and ISI Web of Science was conducted on January 30th, 2025. The statistical analysis was performed using the Review Manager 5.4 software and R language (R package Mada and Metafor). The quality of the studies included was assessed using the Newcastle-Ottawa scale and the QUADAS-2 tool. Data from relevant studies were independently screened and extracted using Rayyan, by at least two authors. A total of 19 studies were eligible (9 studies for EpCAM, 9 studies for CD44, and 2 studies for both EpCAM and CD44), comprising a total of 1370 patients. The diagnostic meta-analysis demonstrated moderate accuracy for EpCAM (AUC, 95% CI of 0.802, 0.69-0.96). A statistically significant association was found for CD44 expression and T-status (OR = 2.04, 95%CI = 1.18-3.51), or N-stage (OR = 2.68, 95%CI = 1.86-3.85), or TNM stage (OR = 3.79, 95%CI = 2.14-6.71). CD44v6 overexpression predicted worse OS (HR = 2.33, p < 0.00001), while EpCAM + CD44 + co-expression was prognostic (HR = 2.02, p = 0.02). Heterogeneity was not observed among the studies included, but further research is warranted to better understand the clinical implications of these markers' positivity in PC diagnosis and prognosis.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.008 | 0.002 |
| Bibliometrics | 0.002 | 0.004 |
| 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) | 0.001 | 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 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".