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Multicenter Study
. 2024 Jun;13(12):e7388.
doi: 10.1002/cam4.7388.

Diagnostic value of carbohydrate antigen 50 in biliary tract cancer: A large-scale multicenter study

Yong-Shuai Wang  1 , Wei Wang  2 , Shen-Yu Zhang  1 , Wei Cai  1 , Rui-Peng Song  1 , Tao Mei  3 , Wei Wang  4 , Feng Zhang  1 , Fei-Yu Qi  5 , Sai Zhang  1 , Yan Liu  1 , Hao-Ran Li  1 , Peng Ji  1 , Miao Gao  1 , Hua-Chuan Song  1 , Huan-Zhang Yao  1 , Fan-Zheng Meng  1 , Zheng Lu  5 , Ji-Zhou Wang  1   6   7 , Lian-Xin Liu  1   6   7
Affiliations
Multicenter Study

Diagnostic value of carbohydrate antigen 50 in biliary tract cancer: A large-scale multicenter study

Yong-Shuai Wang et al. Cancer Med. 2024 Jun.

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.

Methods: A total of 1121 patients from the Liver Cancer Clin-Bio Databank of Anhui Hepatobiliary Surgery Union between January 2017 and December 2022 were included in this study (673 in the training cohort and 448 in the validation cohort): among them, 458 with BTC, 178 with hepatocellular carcinoma (HCC), 23 with combined hepatocellular-cholangiocarcinoma, and 462 with nontumor patients. Receiver operating characteristic (ROC) curves and decision curve analysis (DCA) were used to evaluate the diagnostic efficacy and clinical usefulness.

Results: ROC curves obtained 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 70.3%, and sensitivity 84.0%) in the training cohort and 0.879 (0.841-0.917, 76.7%, and 84.3%) 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 were 0.893 (95% CI 0.853-0.933, specificity 96%, and sensitivity 68.6%) in the training cohort and 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.

Keywords: carbohydrate antigen 19‐9 (CA19‐9); carbohydrate antigen 50 (CA50); diagnostic biomarker; diagnostic model; intrahepatic cholangiocarcinoma (iCCA).

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Conflict of interest statement

No conflict of interest exists in the submission of this manuscript.

Figures

FIGURE 1
FIGURE 1
Flow chart of the study.
FIGURE 2
FIGURE 2
Differential expression levels of four tumor markers in the BTC, HCC, CHC, BBD, and HP groups. (A) Levels of serum CA50 in different groups; (B) Levels of serum CA19‐9 in different groups; (C) Levels of serum AFP in different groups; (D) Levels of serum CEA in different groups. AFP, α‐fetoprotein; BBD, benign biliary‐liver diseases; BTC, biliary tract cancer; CA19‐9, carbohydrate antigen 19‐9; CA50, carbohydrate antigen 50; CEA, carcinoembryonic antigen; CHC, combined hepatocellular‐cholangiocarcinoma; HCC, hepatocellular carcinoma; HP, healthy people.
FIGURE 3
FIGURE 3
Correlation analysis between serum CA50 and other tumor markers. (A) Correlation of CA50 versus CA19‐9; (B) Correlation of CA50 versus AFP; (C) Correlation of CA50 versus CEA. AFP, α‐fetoprotein; BBD, benign biliary‐liver diseases; BTC, biliary tract cancer; CA19‐9, carbohydrate antigen 19‐9; CA50, carbohydrate antigen 50; CEA, carcinoembryonic antigen; CHC, combined hepatocellular‐cholangiocarcinoma; HCC, hepatocellular carcinoma; HP, healthy people.
FIGURE 4
FIGURE 4
ROC results of different tumor markers and the model in the diagnosis of BTC. (A) ROC results of BTC versus HCC + HCC + BBD + HP in the training cohort; (B) ROC results of BTC versus HCC + HCC + BBD + HP in the validation cohort; (C) DCA results of BTC versus HCC + HCC + BBD + HP in the training cohort; (D) DCA results of BTC versus HCC + HCC + BBD + HP in the validation cohort. AFP, α‐fetoprotein; AUC, area under the curve; BBD, benign biliary‐liver diseases; BTC, biliary tract cancer; CA19‐9, carbohydrate antigen 19‐9; CA50, carbohydrate antigen 50; CEA, carcinoembryonic antigen; CHC, combined hepatocellular‐cholangiocarcinoma; HCC, hepatocellular carcinoma; HP, healthy people; LR, likelihood ratio; NPV, negative predictive value; PPV, positive predictive value; ROC, receiver operating characteristic curve. MODEL 1 (CA50 + CA19‐9 + AFP).
FIGURE 5
FIGURE 5
The nomogram of the MODEL 1 for BTC versus HCC + HCC + BBD + HP. (A) The static nomogram for BTC versus HCC + HCC + BBD + HP; (B) The dynamic nomogram for BTC versus HCC + HCC + BBD + HP.
FIGURE 6
FIGURE 6
ROC results of different tumor markers and the model in the diagnosis of iCCA. (A) ROC results of iCCA versus HCC in the training cohort; (B) ROC results of iCCA versus HCC in the validation cohort; (C) DCA results of iCCA versus HCC in the training cohort; (D) DCA results of iCCA versus HCC in the validation cohort. AFP, α‐fetoprotein; AUC, area under the curve; BBD, benign biliary‐liver diseases; BTC, biliary tract cancer; CA19‐9, carbohydrate antigen 19‐9; CA50, carbohydrate antigen 50; CEA, carcinoembryonic antigen; CHC, combined hepatocellular‐cholangiocarcinoma; HCC, hepatocellular carcinoma; HP, healthy people; LR, likelihood ratio; NPV, negative predictive value; PPV, positive predictive value; ROC, receiver operating characteristic curve. MODEL 2 (CA50 + CA19‐9 + AFP).
FIGURE 7
FIGURE 7
The nomogram of the MODEL for iCCA versus HCC. (A) The static nomogram for iCCA versus HCC; (B) The dynamic nomogram for iCCA versus HCC.
See this image and copyright information in PMC

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