LiverRisk score: An accurate, cost-effective tool to predict fibrosis, liver-related, and diabetes-related mortality in the general population

Shanghao Liu; Xiaohan Chen; Xuanwei Jiang; Xiaochun Yin; Ginenus Fekadu; Chuan Liu; Yan He; Huihui Chen; Wenjing Ni; Ruiying Wang; Qing-Lei Zeng; Yuping Chen; Ling Yang; Ruihua Shi; Sheng-Hong Ju; Jie Shen; Jingli Gao; Linhua Zhao; Wai-Kit Ming; Victor W Zhong; Gao-Jun Teng; Xiaolong Qi

doi:10.1016/j.medj.2024.03.003

LiverRisk score: An accurate, cost-effective tool to predict fibrosis, liver-related, and diabetes-related mortality in the general population

Med. 2024 Mar 26:S2666-6340(24)00115-6. doi: 10.1016/j.medj.2024.03.003. Online ahead of print.

Authors

Shanghao Liu¹, Xiaohan Chen², Xuanwei Jiang³, Xiaochun Yin⁴, Ginenus Fekadu², Chuan Liu¹, Yan He², Huihui Chen⁵, Wenjing Ni⁶, Ruiying Wang⁷, Qing-Lei Zeng⁸, Yuping Chen¹, Ling Yang⁹, Ruihua Shi⁴, Sheng-Hong Ju¹, Jie Shen¹⁰, Jingli Gao¹¹, Linhua Zhao¹², Wai-Kit Ming², Victor W Zhong³, Gao-Jun Teng¹³, Xiaolong Qi¹⁴

Affiliations

¹ Center of Portal Hypertension, Department of Radiology, Zhongda Hospital, Medical School, Southeast University, Nurturing Center of Jiangsu Province for State Laboratory of AI Imaging & Interventional Radiology (Southeast University), Nanjing, China; Basic Medicine Research and Innovation Center of Ministry of Education, Zhongda Hospital, Southeast University, State Key Laboratory of Digital Medical Engineering, Nanjing, China.
² Department of Infectious Diseases and Public Health, Jockey Club College of Veterinary Medicine and Life Sciences, City University of Hong Kong, Hong Kong SAR, China.
³ Department of Epidemiology and Biostatistics, School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
⁴ Department of Gastroenterology, Zhongda Hospital, Medical School, Southeast University, Nanjing, China.
⁵ Department of Ultrasound, Zhongda Hospital, Medical School, Southeast University, Nanjing, China.
⁶ Department of Infectious Diseases, Nanjing Drum Tower Hospital Clinical College of Nanjing University of Chinese Medicine, Nanjing, China.
⁷ The First Clinical Medical College of Lanzhou University, Lanzhou, China.
⁸ Department of Infectious Diseases and Hepatology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
⁹ Center of Portal Hypertension, Department of Radiology, Zhongda Hospital, Medical School, Southeast University, Nurturing Center of Jiangsu Province for State Laboratory of AI Imaging & Interventional Radiology (Southeast University), Nanjing, China.
¹⁰ Department of Endocrinology and Metabolism, Shunde Hospital, Southern Medical University (The First People's Hospital of Shunde), Foshan, China.
¹¹ Department of Intensive Care Unit, Kailuan General Hospital, Tangshan, Hebei, China.
¹² Institute of Metabolic Diseases, Guang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, China.
¹³ Basic Medicine Research and Innovation Center of Ministry of Education, Zhongda Hospital, Southeast University, State Key Laboratory of Digital Medical Engineering, Nanjing, China; Center of Interventional Radiology and Vascular Surgery, Department of Radiology, Zhongda Hospital, Medical School, Southeast University, Nanjing, China. Electronic address: gjteng@vip.sina.com.
¹⁴ Center of Portal Hypertension, Department of Radiology, Zhongda Hospital, Medical School, Southeast University, Nurturing Center of Jiangsu Province for State Laboratory of AI Imaging & Interventional Radiology (Southeast University), Nanjing, China; Basic Medicine Research and Innovation Center of Ministry of Education, Zhongda Hospital, Southeast University, State Key Laboratory of Digital Medical Engineering, Nanjing, China. Electronic address: qixiaolong@vip.163.com.

PMID: 38554711
DOI: 10.1016/j.medj.2024.03.003

Abstract

Background: Noninvasive and early assessment of liver fibrosis is of great significance and is challenging. We aimed to evaluate the predictive performance and cost-effectiveness of the LiverRisk score for liver fibrosis and liver-related and diabetes-related mortality in the general population.

Methods: The general population from the NHANES 2017-March 2020, NHANES 1999-2018, and UK Biobank 2006-2010 were included in the cross-sectional cohort (n = 3,770), along with the NHANES follow-up cohort (n = 25,317) and the UK Biobank follow-up cohort (n = 17,259). The cost-effectiveness analysis was performed using TreeAge Pro software. Liver stiffness measurements ≥10 kPa were defined as compensated advanced chronic liver disease (cACLD).

Findings: Compared to conventional scores, the LiverRisk score had significantly better accuracy and calibration in predicting liver fibrosis, with an area under the receiver operating characteristic curve (AUC) of 0.76 (0.72-0.79) for cACLD. According to the updated thresholds of LiverRisk score (6 and 10), we reclassified the population into three groups: low, medium, and high risk. The AUCs of LiverRisk score for predicting liver-related and diabetes-related mortality at 5, 10, and 15 years were all above 0.8, with better performance than the Fibrosis-4 score. Furthermore, compared to the low-risk group, the medium-risk and high-risk groups in the two follow-up cohorts had a significantly higher risk of liver-related and diabetes-related mortality. Finally, the cost-effectiveness analysis showed that the incremental cost-effectiveness ratio for LiverRisk score compared to FIB-4 was USD $18,170 per additional quality-adjusted life-year (QALY) gained, below the willingness-to-pay threshold of $50,000/QALY.

Conclusions: The LiverRisk score is an accurate, cost-effective tool to predict liver fibrosis and liver-related and diabetes-related mortality in the general population.

Funding: The National Natural Science Foundation of China (nos. 82330060, 92059202, and 92359304); the Key Research and Development Program of Jiangsu Province (BE2023767a); the Fundamental Research Fund of Southeast University (3290002303A2); Changjiang Scholars Talent Cultivation Project of Zhongda Hospital of Southeast University (2023YJXYYRCPY03); and the Research Personnel Cultivation Program of Zhongda Hospital Southeast University (CZXM-GSP-RC125).

Keywords: LiverRisk score; Translation to population health; diabetes-related mortality; general population; liver fibrosis; liver-related mortality.