Retrospective Study
Copyright ©The Author(s) 2024. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Gastrointest Oncol. Mar 15, 2024; 16(3): 844-856
Published online Mar 15, 2024. doi: 10.4251/wjgo.v16.i3.844
Risk of cardiovascular death in patients with hepatocellular carcinoma based on the Fine-Gray model
Yu-Liang Zhang, Zi-Rong Liu, Zhi Liu, Yi Bai, Hao Chi, Da-Peng Chen, Ya-Min Zhang, Zi-Lin Cui
Yu-Liang Zhang, Hao Chi, Da-Peng Chen, First Central Clinical College, Tianjin Medical University, Tianjin 300070, China
Zi-Rong Liu, Zhi Liu, Yi Bai, Ya-Min Zhang, Zi-Lin Cui, Department of Hepatobiliary Surgery, Tianjin First Central Hospital, School of Medicine, Nankai University, Tianjin 300192, China
Author contributions: Cui ZL had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis; Cui ZL and Zhang YL designed the research study; Zhang YL and Cui ZL performed the primary literature and data extraction; Zhang YL, Liu ZR, Liu Z, Bai Y, Chi H and Chen DP analyzed the data; Zhang YL and Cui ZL wrote the manuscript; Cui ZL, Bai Y and Zhang YM critically revised the manuscript for important intellectual content; and all authors read and approved the final version.
Supported by Health Technology Project of Tianjin, No. ZC20175.
Institutional review board statement: The data for this study came from a public database (SEER database), so this statement does not applicable.
Informed consent statement: The data for this study came from a public database (SEER database), so this statement does not applicable.
Conflict-of-interest statement: We have no financial relationships to disclose.
Data sharing statement: The data are available on application to the SEER database (https://seer.cancer.gov/). Technical appendix and statistical code from the corresponding author at 13602184643@163.com.
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: Zi-Lin Cui, PhD, Surgeon, Department of Hepatobiliary Surgery, Tianjin First Central Hospital, School of Medicine, Nankai University, No. 24 Fukang Road, Nankai District, Tianjin 300192, China. 13602184643@163.com
Received: October 20, 2023
Peer-review started: October 20, 2023
First decision: December 5, 2023
Revised: December 15, 2023
Accepted: January 17, 2024
Article in press: January 17, 2024
Published online: March 15, 2024
Processing time: 144 Days and 3.6 Hours
Abstract
BACKGROUND

Hepatocellular carcinoma (HCC) is one of the most common types of cancers worldwide, ranking fifth among men and seventh among women, resulting in more than 7 million deaths annually. With the development of medical technology, the 5-year survival rate of HCC patients can be increased to 70%. However, HCC patients are often at increased risk of cardiovascular disease (CVD) death due to exposure to potentially cardiotoxic treatments compared with non-HCC patients. Moreover, CVD and cancer have become major disease burdens worldwide. Thus, further research is needed to lessen the risk of CVD death in HCC patient survivors.

AIM

To determine the independent risk factors for CVD death in HCC patients and predict cardiovascular mortality (CVM) in HCC patients.

METHODS

This study was conducted on the basis of the Surveillance, Epidemiology, and End Results database and included HCC patients with a diagnosis period from 2010 to 2015. The independent risk factors were identified using the Fine-Gray model. A nomograph was constructed to predict the CVM in HCC patients. The nomograph performance was measured using Harrell’s concordance index (C-index), calibration curve, receiver operating characteristic (ROC) curve, and area under the ROC curve (AUC) value. Moreover, the net benefit was estimated via decision curve analysis (DCA).

RESULTS

The study included 21545 HCC patients, of whom 619 died of CVD. Age (< 60) [1.981 (1.573-2.496), P < 0.001], marital status (married) [unmarried: 1.370 (1.076-1.745), P = 0.011], alpha fetoprotein (normal) [0.778 (0.640-0.946), P = 0.012], tumor size (≤ 2 cm) [(2, 5] cm: 1.420 (1.060-1.903), P = 0.019; > 5 cm: 2.090 (1.543-2.830), P < 0.001], surgery (no) [0.376 (0.297-0.476), P < 0.001], and chemotherapy(none/unknown) [0.578 (0.472-0.709), P < 0.001] were independent risk factors for CVD death in HCC patients. The discrimination and calibration of the nomograph were better. The C-index values for the training and validation sets were 0.736 and 0.665, respectively. The AUC values of the ROC curves at 2, 4, and 6 years were 0.702, 0.725, 0.740 in the training set and 0.697, 0.710, 0.744 in the validation set, respectively. The calibration curves showed that the predicted probabilities of the CVM prediction model in the training set vs the validation set were largely consistent with the actual probabilities. DCA demonstrated that the prediction model has a high net benefit.

CONCLUSION

Risk factors for CVD death in HCC patients were investigated for the first time. The nomograph served as an important reference tool for relevant clinical management decisions.

Keywords: Hepatocellular carcinoma, Cardiovascular disease deaths, Fine-Gray model, Risk factor, Nomograph, Predict

Core Tip: Hepatocellular carcinoma (HCC) is one of the most prevalent cancers worldwide. Studies have shown that HCC patients have chance to improve 5-year survival rate to 70%. How to avoid cardiovascular disease (CVD) death in HCC patients has become a problem worth exploring due to the course of treatment and the manifestation of certain paraneoplastic syndromes. In this study, we used Fine-Gray model to identify the independent risk factors for CVD death in HCC patients and constructed a predictive nomograph with high performance.