Affiliation:
1. The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China
2. Department of Medical Oncology, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China
3. Department of Pathology, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China
4. The First Affiliated Hospital of Bengbu Medical University
Abstract
Abstract
Background
To date, carbohydrate antigen 19 − 9 (CA19-9) and carcinoembryonic antigen (CEA) have been widely used for the screening, diagnosis and prediction of biliary tract cancer (BTC) patients. However, few studies with large sample sizes of carbohydrate Antigen 50 (CA50) were reported in BTC patients and combined CA50, CA19-9 and α-fetoprotein (AFP) to build a clinical diagnostic model to provide a new screening and diagnosis method.
Methods
Here, we designed a cross-sectional study and analyzed data for patients with BTC, hepatocellular carcinoma (HCC), combined hepatocellular-cholangiocarcinoma (CHC), and benign biliary-liver diseases (BBD) and healthy people (HP) from two Chinese hospitals diagnosed between January 2017 and December 2022. Receiver operating characteristic (ROC) curves and decision curve analysis (DCA) were used to evaluate the diagnostic efficacy and clinical usefulness.
Results
A total of 1121 patients were included in this study (673 in the training cohort and 448 in the validation cohort): among them, 458 with BTC were included in the experimental group, and 178 with HCC, 23 with CHC, 242 with BBD, and 220 with HP were included in the control group, respectively. ROC curves by combining CA50, CA19-9 and AFP showed that, the AUC value of the diagnostic MODEL 1 was 0.885 (95% CI 0.856–0.885, specificity 93.9%, and sensitivity 74.3% in the training cohort; 0.879 (0.841–0.917, 92.8% and 75.9%) in the validation cohort. In addition, comparing iCCA and HCC (235 in the training cohort, 157 in the validation cohort), the AUC values of the diagnostic MODEL 2 was 0.893 (95% CI 0.853–0.933, specificity 96%, and sensitivity 68.6%) in the training cohort; 0.872 (95% CI 0.818–0.927, 94.2%, and 64.6%) in the validation cohort.
Conclusion
The model combining CA50, CA19-9, and AFP not only has good diagnostic value for BTC, but also has good diagnostic value for distinguishing iCCA and HCC.
Publisher
Research Square Platform LLC
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