Fibrosis-4 index as a predictor of all-cause and cardiovascular mortality in patients with chronic kidney disease

This study utilized data from the National Health and Nutrition Examination Survey (NHANES) 2005–2020 (n = 28,231, including 4,907 chronic kidney disease (CKD) patients) with weighted analyses and, through variance inflation factor (VIF) assessment to verify covariate selection, supported model validity, to demonstrate for the first time that the Fibrosis-4 (FIB4) index serves as an independent predictor of all-cause and cardiovascular disease (CVD)-related mortality in CKD patients. Weighted logistic regression confirmed FIB4 index as a significant independent predictor of CKD risk (fully adjusted odds ratios (OR) 1.85, 95% confidence interval (CI) 1.64–2.08), with strong dose-response gradient (Q4 OR 3.51–6.02). Multivariable Cox proportional hazards regression models revealed that each 1-unit increase in the FIB4 index was associated with a 34% elevated risk of all-cause mortality (hazard ratio (HR) = 1.34, 95%CI: 1.27–1.41, p < 0.001) and a 34% increased risk of CVD mortality (HR = 1.34, 95% CI: 1.24–1.44, p < 0.001). Restricted cubic spline (RCS) analysis identified nonlinear threshold effects at inflection points of 1.84 (all-cause mortality) and 1.74 (CVD mortality), with mortality risks escalating sharply beyond these thresholds (all-cause HR = 2.57; CVD HR = 2.85). Receiver operating characteristic (ROC) curve analysis demonstrated robust predictive performance (area under the curve (AUC): 0.799 for all-cause mortality; 0.801 for CVD mortality). Subgroup analyses highlighted heightened risks among non-Hispanic Black individuals, older adults, and those with low physical activity. Mediation analysis indicated that neutrophil-to-lymphocyte ratio (NLR) mediated 5.48% of the FIB4–all-cause mortality association and 5.83% of the CVD mortality association, though direct effects predominated (94.52% and 94.17%, respectively). These findings establish the FIB4 index as a practical, evidence-based tool for risk stratification in CKD patients, offering critical insights for personalized clinical management.