Abstract

Background

The prognostic significance of tumor burden score (TBS) in relation to carcinoembryonic antigen (CEA) has not been investigated among patients undergoing hepatectomy for intrahepatic cholangiocarcinoma (ICC). This study aimed to develop and validate a simplified model, a combination of TBS and CEA (CTC grade), for predicting the long-term outcomes of postoperative ICC patients.

Methods

Patients who underwent curative − intent resection of ICC between 2011 and 2019 were identified from a large multi − institutional database. The impact of TBS, CEA, and the CTC grade on overall survival (OS) and recurrence − free survival (RFS) was evaluated in both the derivation and validation cohorts. The receiver operating characteristic curve was utilized for assessing the predictive accuracy of the model. Subgroup analyses were performed across 8th TNM stage system stratified by CTC grade to assess the discriminatory capacity within the same TNM stage.

Results

A total of 812 patients were included in the derivation cohort and 266 patients in the validation cohort. Survival varied based on CEA (low: 36.7% vs. high: 9.0%) and TBS (low: 40.3% vs. high: 17.6%) in relation to 5 − year survival (both p < 0.001). As expected, patients with low CTC grade (i.e., low TBS/low CEA) were associated with the best OS as well as RFS, while high CTC grade (i.e., high TBS/high CEA) correlated to the worst outcomes. The model exhibited well performance in both the derivation cohort (area under the curve of 0.694) and the validation cohort (0.664). The predictive efficacy of the CTC grade system remains consistently stable across TNM stages I and III/IV.

Conclusion

The CTC grade, a composite parameter derived from the combination of TBS and CEA levels, served as an easy − to − use tool and performed well in stratifying patients with ICC relative to OS and RFS.

Details

Title
Tumor burden score and carcinoembryonic antigen predict outcomes in patients with intrahepatic cholangiocarcinoma following liver resection: a multi‑institutional analysis
Author
Fu, Jun; Zheng, Lifang; Tang, Shicuan; Lin, Kongying; Zheng, Shuguo; Bi, Xinyu; Wang, Jianming; Guo, Wei; Li, Fuyu; Wang, Jian; Wang, Kui; Li, Haitao; Zeng, Yongyi
Pages
1-14
Section
Research
Publication year
2024
Publication date
2024
Publisher
BioMed Central
e-ISSN
14712407
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
3037864396
Copyright
© 2024. This work is licensed under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.