Construction and evaluation of a predictive nomogram model for the prognosis of intrahepatic cholangiocarcinoma patients undergoing curative resection based on the albumin-bilirubin score and tumor burden score grade
10.3760/cma.j.cn113884-20230621-00176
- VernacularTitle:基于ATS的肝内胆管癌患者根治性切除术后预后预测列线图模型的构建与评估
- Author:
Haofeng ZHANG
1
;
Hao YUAN
;
Qingshan LI
;
Guan HUANG
;
Zhenwei YANG
;
Pengyu CHEN
;
Zuochao QI
;
Chenxi XIE
;
Bo MENG
;
Haibo YU
Author Information
1. 郑州大学人民医院(河南省人民医院)肝胆胰腺外科，郑州 450003
- Keywords:
Cholangiocarcinoma;
Nomograms;
Prognosis;
Tumor burden score;
Albumin-bilirubin score;
Radical surgery
- From:
Chinese Journal of Hepatobiliary Surgery
2023;29(11):836-842
- CountryChina
- Language:Chinese
-
Abstract:
Objective:A predictive nomogram model for the prognosis of intrahepatic cholangiocarcinoma (ICC) patients after curative resection was constructed based on the albumin-bilirubin score and tumor burden score (ATS) grade, and the predictive performance of the nomogram model was evaluated.Methods:Retrospective analysis of clinical data was made, from ICC patients who underwent curative resection at Zhengzhou University People's Hospital and Zhengzhou University Cancer Hospital from January 2016 to January 2020. A total of 258 patients were included in the study, with 140 males and 118 females, with an average age of (56.5±9.5) years. The 258 ICC patients were randomly divided into a training set ( n=174) and a testing set ( n=84) in a 7∶3 ratio. Single-factor and multi-factor Cox regression analyses were performed to identify prognostic factors for ICC patients of the training set, and then a nomogram model was constructed. The performance of the nomogram model was evaluated by using the concordance index (C-index), calibration curve, and risky decision curve analysis. Results:In the training set, univariate Cox regression analysis indicated that albumin-bilirubin (ALBI), tumor burden score (TBS), carcinoembryonic antigen (CEA), tumor differentitation, lymphvascular invasion and ATS significantly influenced overall survival after radical resection for ICC (all P<0.05). Multifactorial Cox regression analysis revealed that ATS grade, CEA, tumor differentiation, lymphovascular invasion, and AJCC N stage are independent risk factors for the prognosis of ICC patients after curative resection (all P<0.05). Assessment of the postoperative survival prediction model based on multifactorial Cox regression yielded a C-index of 0.775(95% CI: 0.747-0.841) for the training set and 0.731(95% CI: 0.668-0.828) for the testing set. The calibration curves for both the training and testing sets indicated strong predictive capability of the model. Additionally, the risk decision curve also suggested high net benefit of the model. Conclusions:The preoperative ATS grade is an independent factor affecting the survival after ICC radical resection. The nomogram model constructed based on ATS grade demonstrates excellent predictive value for postoperative prognosis in ICC patients.
