External validation of the fatty liver index and lipid accumulation product indices, using 1H-magnetic resonance spectroscopy, to identify hepatic steatosis in healthy controls and obese, insulin-resistant individuals

脂肪变性 脂肪肝 内科学 医学 胃肠病学 接收机工作特性 队列 人体测量学 磁共振成像 内分泌学 糖尿病 疾病 放射科
作者
Daniel J. Cuthbertson,Martin O. Weickert,Daniel Lythgoe,Victoria S. Sprung,Rebecca Dobson,Fariba Shoajee-Moradie,A. Margot Umpleby,A. Pfeiffer,E. Louise Thomas,Jimmy D. Bell,Helen Jones,Graham J. Kemp
出处
期刊:European journal of endocrinology [Oxford University Press]
卷期号:171 (5): 561-569 被引量:145
标识
DOI:10.1530/eje-14-0112
摘要

Simple clinical algorithms including the fatty liver index (FLI) and lipid accumulation product (LAP) have been developed as surrogate markers for non-alcoholic fatty liver disease (NAFLD), constructed using (semi-quantitative) ultrasonography. This study aimed to validate FLI and LAP as measures of hepatic steatosis, as determined quantitatively by proton magnetic resonance spectroscopy (1H-MRS).Data were collected from 168 patients with NAFLD and 168 controls who had undergone clinical, biochemical and anthropometric assessment. Values of FLI and LAP were determined and assessed both as predictors of the presence of hepatic steatosis (liver fat>5.5%) and of actual liver fat content, as measured by 1H-MRS. The discriminative ability of FLI and LAP was estimated using the area under the receiver operator characteristic curve (AUROC). As FLI can also be interpreted as a predictive probability of hepatic steatosis, we assessed how well calibrated it was in our cohort. Linear regression with prediction intervals was used to assess the ability of FLI and LAP to predict liver fat content. Further validation was provided in 54 patients with type 2 diabetes mellitus.FLI, LAP and alanine transferase discriminated between patients with and without steatosis with an AUROC of 0.79 (IQR=0.74, 0.84), 0.78 (IQR=0.72, 0.83) and 0.83 (IQR=0.79, 0.88) respectively although could not quantitatively predict liver fat. Additionally, the algorithms accurately matched the observed percentages of patients with hepatic steatosis in our cohort.FLI and LAP may be used to identify patients with hepatic steatosis clinically or for research purposes but could not predict liver fat content.
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