Retrospective Cohort Study
Copyright ©The Author(s) 2023. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Gastrointest Oncol. Jun 15, 2023; 15(6): 1036-1050
Published online Jun 15, 2023. doi: 10.4251/wjgo.v15.i6.1036
Development of a model based on the age-adjusted Charlson comorbidity index to predict survival for resected perihilar cholangiocarcinoma
Yu Pan, Zhi-Peng Liu, Hai-Su Dai, Wei-Yue Chen, Ying Luo, Yu-Zhu Wang, Shu-Yang Gao, Zi-Ran Wang, Jin-Ling Dong, Yun-Hua Liu, Xian-Yu Yin, Xing-Chao Liu, Hai-Ning Fan, Jie Bai, Yan Jiang, Jun-Jie Cheng, Yan-Qi Zhang, Zhi-Yu Chen
Yu Pan, Zhi-Peng Liu, Hai-Su Dai, Wei-Yue Chen, Yu-Zhu Wang, Shu-Yang Gao, Yun-Hua Liu, Xian-Yu Yin, Jie Bai, Yan Jiang, Jun-Jie Cheng, Zhi-Yu Chen, Department of Hepatobiliary Surgery, Southwest Hospital, Third Military Medical University (Army Medical University), Chongqing 400038, China
Wei-Yue Chen, Clinical Research Center of Oncology, Lishui Hospital of Zhejiang University, Lishui 323000, Zhejiang Province, China
Ying Luo, Faculty of Education, Southwest University, Chongqing 400715, China
Zi-Ran Wang, Department of General Surgery, 903rd Hospital of People’s Liberation Army, Hangzhou 310000, Zhejiang Province, China
Jin-Ling Dong, Department of Clinical Pharmacy, The General Hospital of Western Theater Command, Chengdu 610000, Sichuan Province, China
Xing-Chao Liu, Department of Hepatobiliary Surgery, Sichuan Provincial People's Hospital, Chengdu 610000, Sichuan Province, China
Hai-Ning Fan, Department of Hepatobiliary Surgery, Affiliated Hospital of Qinghai University, Xining 810000, Qinghai Province, China
Yan-Qi Zhang, Department of Health Statistics, College of Military Preventive Medicine, Third Military Medical University (Army Medical University), Chongqing 400038, China
Author contributions: Pan Y, Liu ZP, Dai HS, and Chen ZY contributed to the conception; Pan Y, Liu ZP, Wang YZ, Chen WY, Luo Y, Gao SY, Chen ZY, and Dai HS designed the study; Chen ZY and Dai HS performed the administrative support; Pan Y, Dong JL, Liu YH, Yin XY, Liu XC, Fan HN, Bai J, Jiang Y, and Cheng JJ contributed to the data collection and acquisition; Pan Y, Liu ZP, Chen WY, Luo Y, Gao SY, Wang ZR, and Zhang YQ performed the data analysis; Pan Y, Liu ZP, and Dai HS contributed to the manuscript preparation; Chen ZY and Dai HS performed the critical revision; All authors agree to the final approval of the manuscript.
Supported by National Natural Science Foundation of China, No. 81874211; and Chongqing Technology Innovation and Application Development Special Key Project, No. CSTC2021jscx-gksb-N0009.
Institutional review board statement: The study was approved by the Institutional Review Board of the Southwest Hospital, China, No. KY2021129.
Informed consent statement: Patients were not required to give informed consent to the study because the analysis used anonymized clinical data, which were obtained after each patient gave written consent to treatment. For full disclosure, the details of the study are published on the home page of Southwest Hospital.
Conflict-of-interest statement: All the authors report no relevant conflicts of interest for this article.
Data sharing statement: Technical appendix, statistical code, and dataset available from the corresponding author at chenzhiyu_umn@163.com. Participants gave informed consent for data sharing.
STROBE statement: The authors have read the STROBE Statement—checklist of items, and the manuscript was prepared and revised according to the STROBE Statement—checklist of items.
Open-Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: https://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Zhi-Yu Chen, MD, PhD, Academic Editor, Academic Research, Deputy Director, Doctor, Professor, Surgeon, Department of Hepatobiliary Surgery, Southwest Hospital, Third Military Medical University (Army Medical University), No. 30 Gaotanyan Road, Chongqing 400038, China. chenzhiyu_umn@163.com
Received: February 11, 2023
Peer-review started: February 11, 2023
First decision: April 10, 2023
Revised: April 18, 2023
Accepted: May 4, 2023
Article in press: May 4, 2023
Published online: June 15, 2023
Processing time: 123 Days and 17.8 Hours
Abstract
BACKGROUND

Perihilar cholangiocarcinoma (pCCA) has a poor prognosis and urgently needs a better predictive method. The predictive value of the age-adjusted Charlson comorbidity index (ACCI) for the long-term prognosis of patients with multiple malignancies was recently reported. However, pCCA is one of the most surgically difficult gastrointestinal tumors with the poorest prognosis, and the value of the ACCI for the prognosis of pCCA patients after curative resection is unclear.

AIM

To evaluate the prognostic value of the ACCI and to design an online clinical model for pCCA patients.

METHODS

Consecutive pCCA patients after curative resection between 2010 and 2019 were enrolled from a multicenter database. The patients were randomly assigned 3:1 to training and validation cohorts. In the training and validation cohorts, all patients were divided into low-, moderate-, and high-ACCI groups. Kaplan-Meier curves were used to determine the impact of the ACCI on overall survival (OS) for pCCA patients, and multivariate Cox regression analysis was used to determine the independent risk factors affecting OS. An online clinical model based on the ACCI was developed and validated. The concordance index (C-index), calibration curve, and receiver operating characteristic (ROC) curve were used to evaluate the predictive performance and fit of this model.

RESULTS

A total of 325 patients were included. There were 244 patients in the training cohort and 81 patients in the validation cohort. In the training cohort, 116, 91 and 37 patients were classified into the low-, moderate- and high-ACCI groups. The Kaplan-Meier curves showed that patients in the moderate- and high-ACCI groups had worse survival rates than those in the low-ACCI group. Multivariable analysis revealed that moderate and high ACCI scores were independently associated with OS in pCCA patients after curative resection. In addition, an online clinical model was developed that had ideal C-indexes of 0.725 and 0.675 for predicting OS in the training and validation cohorts. The calibration curve and ROC curve indicated that the model had a good fit and prediction performance.

CONCLUSION

A high ACCI score may predict poor long-term survival in pCCA patients after curative resection. High-risk patients screened by the ACCI-based model should be given more clinical attention in terms of the management of comorbidities and postoperative follow-up.

Keywords: Perihilar cholangiocarcinoma, Age-adjusted Charlson comorbidity index, Resection, Survival, Model, Prognosis

Core Tip: Our study assessed the prognostic value of the age-adjusted Charlson comorbidity index (ACCI) and designed an online clinical model for perihilar cholangiocarcinoma (pCCA). We retrospectively evaluated 496 pCCA patients from multiple centers who underwent radical resection. This study proposed that the ACCI is an independent predictor of pCCA prognosis, and a nomogram based on the ACCI is a promising predictive model for overall survival in pCCA patients.