Prospective association between liver biomarkers and mortality risk in Chinese middle-aged and elderly populations
10.3760/cma.j.cn112338-20241209-00781
- VernacularTitle:中国中老年人肝脏生物标志物与死亡风险的前瞻性关联研究
- Author:
Shuyao SONG
1
;
Ting WU
;
Canqing YU
;
Dianjianyi SUN
;
Pei PEI
;
Huaidong DU
;
Junshi CHEN
;
Zhengming CHEN
;
Jun LYU
;
Liming LI
;
Yuanjie PANG
Author Information
1. 北京大学公共卫生学院流行病与卫生统计学系，北京 100191
- Publication Type:Journal Article
- Keywords:
Liver biomarkers;
Mortality risk;
Perspective study
- From:
Chinese Journal of Epidemiology
2025;46(4):549-556
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To analyze the prospective associations between liver biomarkers and mortality among Chinese middle-aged and elderly populations and to evaluate the mortality risk predictive value.Methods:A total of 22 758 participants from the 3 rd resurvey of the China Kadoorie Biobank were included. Cox proportional hazard models were used to analyze the prospective associations of 5 liver biomarkers with mortality. These liver biomarkers included two liver imaging biomarkers (liver fat attenuation parameter, liver stiffness measurement) and three serum liver enzyme biomarkers [gamma-glutamyl transferase (GGT), ALT, and AST]. Restricted cubic spline was used to assess the nonlinear associations between biomarkers and mortality. The area used the receiver operating characteristic curve (AUC) to evaluate the predictive ability of the models after incorporating liver biomarkers into traditional prediction models for mortality. Results:The mean age of the participants was (65.2±9.1) years, with a median follow-up of 1.5 years, during which 307 deaths occurred. Compared to individuals without hepatic steatosis, those with severe hepatic steatosis had a 79% higher risk of mortality, with a HR of 1.79 (95% CI: 1.06-3.03). Compared to individuals without hepatic fibrosis, those with advanced fibrosis and cirrhosis had higher mortality risks of 48% and 91%, respectively (both P<0.05). For each standard deviation increase in GGT, the mortality risk increased by 10% ( HR=1.10, 95% CI: 1.05-1.15), with the positive association plateauing at higher GGT levels. AST exhibited a U-shaped association with mortality risk. The AUC of the prediction model adding liver biomarkers into traditional prediction factors was 0.718 (95% CI: 0.679-0.757), with an increase of 0.030 ( P<0.001) compared with the traditional model. Conclusions:Severe hepatic steatosis, higher levels of hepatic fibrosis, and elevated GGT levels are significantly associated with higher mortality risk. AST shows a U-shaped nonlinear association with mortality risk. Incorporating liver biomarkers into traditional risk prediction models enhance the ability to predict mortality.
