The prognostic significance of cholesterol, high-density lipoprotein and glucose (CHG) index in evaluating all-cause mortality risk in metabolic dysfunction-associated steatotic liver disease (MASLD) individuals: evidence from two cohort studies

BACKGROUND: The prognostic assessment of metabolic dysfunction-associated steatotic liver disease (MASLD) is of critical importance. Although previous international studies have suggested an association between the cholesterol, high-density lipoprotein, and glucose (CHG) index and mortality in MASLD patients, its generalizability in the Chinese population remains unclear, and there is a lack of predictive tools directly applicable for individual risk stratification. METHODS: A total of 6936 participants with MASLD were sourced from the China Health and Retirement Longitudinal Study (CHARLS) database from 2011 to 2020. Survival differences were visualized using the Kaplan-Meier method. Multivariate Cox regression was employed to assess the association between the CHG index and mortality risk. Smooth curve fitting analysis was conducted to examine the nonlinear relationship between them. Mediation analysis was performed to explore the mediating roles of C-reactive protein (CRP) and triglyceride glucose-weight-adjusted waist index (TyG-WWI). To evaluate the predictive value of the CHG index, we implemented a set of eight distinct machine learning (ML) models. Subgroup and sensitivity analyses were conducted to verify the robustness of the results. Concurrently, the National Health and Nutrition Examination Survey (NHANES) database (1999–2018) was utilized for external validation. RESULTS: The median follow-up duration was 7.44 years. A total of 615 mortality events were recorded. After adjusting for multiple confounding factors, an elevated CHG index was significantly associated with an increased risk of mortality (highest vs. lowest tertile, HR = 1.49, 95% CI [1.21–1.84], P = 0.0002). Kaplan-Meier curves demonstrated that higher CHG index levels were significantly associated with reduced survival (P < 0.0001). Smooth curve fitting and threshold effect analysis revealed a nonlinear relationship between them. Mediation analysis indicated that CRP and TyG-WWI mediated 13.36% and 45.33% of the effect of CHG index on mortality, respectively (all P < 0.05). Logistic Regression model showed superior discrimination. Decision curve analysis confirmed that the Logistic Regression model provided significant clinical net benefit across a wide range of risk thresholds. The primary analyses were replicated using data from the representative NHANES cohort, revealing a significant positive association between CHG index and mortality. CONCLUSIONS: Elevated CHG index is significantly associated with an increased risk of mortality in the Chinese MASLD population, demonstrating a nonlinear relationship. Furthermore, indicators related to inflammation and insulin resistance (IR) significantly mediate these associations. The CHG index serves as an important tool for predicting long-term adverse outcomes in this population. RESEARCH INSIGHTS: What is currently known about this topic? 1. International studies have suggested that the CHG index is associated with mortality in patients with MASLD. 2. However, its generalizability in Chinese populations remains unclear, and there is a lack of prediction tools that can be directly applied for individual risk stratification. What is the key research question? 1. How does the CHG index influence mortality risk in Chinese MASLD individuals? What is new? 1. This is the first Chinese cohort study to investigate the relationship between CHG index and mortality risk in MASLD individuals. 2. A prediction model was constructed using ML. 3. Mediation analysis revealed the mediating role of inflammatory and IR-related indicators for the first time. How might this study influence clinical practice? 1. This research may promote the integration of the CHG index into routine risk assessment for MASLD patients. By providing a low-cost risk-stratification tool, it could facilitate early intervention. The identified threshold effect may offer evidence-based support for establishing personalized management cut-off values.