How good is controlled attenuation parameter and fatty liver index for assessing liver steatosis in general population: correlation with ultrasound

Background & Aims: Liver steatosis measurement by controlled attenuation parameter (CAP) is a non-invasive method for diagnosing steatosis, based on transient elastography. Its usefulness as screening procedure for hepatic steatosis in general population has not been previously evaluated. The aim of this study was to evaluate the diagnostic accuracy of CAP and fatty liver index (FLI) for detection and quantification of steatosis in general population. Methods: Recruitment was done from a prospective epidemiological study of the general adult population. Steatosis was evaluated using CAP, FLI and ultrasound (US). Steatosis scored according to Hamaguchi's US scoring, from 0 (S0) to 6 (S6) points. Hepatic steatosis defined by score >= 2 (S >= 2) and moderate/severe steatosis by score >= 4 (S >= 4). Performance of CAP and FLI for diagnosing steatosis compared with US was assessed using areas under receiver operating characteristic curves (AUROC). Results: From 219 consecutive individuals studied, 13 (5.9%) excluded because of failure/unreliable liver stiffness measurements. Steatosis prevalence: S >= 2 38.4% and S >= 4 12.1%. CAP significantly correlated with steatosis (rho = 0.73, P < 0.0001), steatosis score (rho = 0.76; P < 0.0001), FLI (rho = 0.69), waist circumference (rho = 0.62), body mass index (rho = 0.55), triglyceride (rho = 0.49), HOMA-IR (rho = 0.26), alcohol consumption (rho = 0.24) and cholesterol (rho = 0.19), not with liver stiffness measurements. Using CAP and FLI, AUROC's were 0.94 (95% CI 0.91-0.97, P < 0.001) and 0.91 for S >= 2; 0.95 (95% CI 0.90-0.99, P < 0.001) and 0.93 for S >= 4 respectively. Optimal cut-off value of CAP and FLI were 243 dB/m and 48 for S >= 2; 303.5 dB/m and 62 for S >= 4 respectively. Conclusion: Controlled attenuation parameter and FLI seem promising tools for screening and steatosis quantification in the general population. Larger studies are needed for validation.