Altered Serum Annexin A2 Might Be a New Potential Diagnostic Biomarker in Human Colorectal Cancer.
Bibliographic record
Abstract
OBJECTIVE: Annexin A2 is a calcium dependent phospholipid binding protein that is a biomarker in cancers. However, the value of serum Annexin A2 in the diagnosis of colorectal cancer (CRC) is not clear. This study aimed to investigate clinical utility of serum Annexin A2 as a potential biomarker for CRC. METHODS: Annexin A2 was analyzed in 20 cases of CRC tissues and 20 controls of normal adjacent paired tissues. Serum Annexin A2 was calculated in 59 CRC patients and 44 healthy subjects. Receiver operating characteristic (ROC) curve and logistic regression were utilized to evaluate the diagnostic effectiveness and construct diagnostic model. RESULTS: =0.0111). ROC analysis indicated the diagnostic efficacy of serum Annexin A2 was better than carcinoembryonic antigen (CEA) and carbohydrate antigen 19-9 (CA199) for CRC. Furthermore, joint detection of Annexin A2 and CEA had the maximum area under the ROC curve (AUC) in discriminating CRC from healthy controls (AUC 0.931, sensitivity 86.4%, specificity 84.7%, positive predictive value 87.9%, and negative predictive value 82.2%). CONCLUSIONS: Serum Annexin A2 may be a non-invasive and promising biomarker for the diagnosis of CRC, and the joint detection of Annexin A2 and CEA may have been favorable clinical applied value in the diagnosis of CRC.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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 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".