Department of Obesity and EndocrinologyClinical Sciences Centre, University Hospital Aintree, Liverpool, UKDepartment of Obesity and EndocrinologyInstitute of Ageing and Chronic Disease, University of Liverpool, Liverpool, UKWarwickshire Institute for the Study of DiabetesEndocrinology and Metabolism, University Hospitals Coventry and Warwickshire NHS Trust, Coventry, UKDivision of Metabolic and Vascular HealthWarwick Medical School, University of Warwick, Warwick, UKCancer Research UK Liverpool Cancer Trials UnitUniversity of Liverpool, Liverpool, UKDepartment of Diabetes and Metabolic MedicineFaculty of Health and Medical Sciences, University of Surrey, Guildford, UKDepartment of Clinical NutritionGerman Institute of Human Nutrition, Potsdam-Rehbruecke, GermanyThe Department of EndocrinologyDiabetes and Nutrition, Charité-University-Medicine Berlin, Berlin, GermanyMetabolic and Molecular Imaging GroupImperial College London, MRC Clinical Sciences Centre, London, UKResearch Institute for Sport and Exercise SciencesLiverpool John Moores University, Liverpool, UKDepartment of Musculoskeletal BiologyInstitute of Ageing and Chronic Disease, Magnetic Resonance and Image Analysis Research Centre, University of Liverpool, Liverpool, UK Department of Obesity and EndocrinologyClinical Sciences Centre, University Hospital Aintree, Liverpool, UKDepartment of Obesity and EndocrinologyInstitute of Ageing and Chronic Disease, University of Liverpool, Liverpool, UKWarwickshire Institute for the Study of DiabetesEndocrinology and Metabolism, University Hospitals Coventry and Warwickshire NHS Trust, Coventry, UKDivision of Metabolic and Vascular HealthWarwick Medical School, University of Warwick, Warwick, UKCancer Research UK Liverpool Cancer Trials UnitUniversity of Liverpool, Liverpool, UKDepartment of Diabetes and Metabolic MedicineFaculty of Health and Medical Sciences, University of Surrey, Guildford, UKDepartment of Clinical NutritionGerman Institute of Human Nutrition, Pot
Department of Obesity and EndocrinologyClinical Sciences Centre, University Hospital Aintree, Liverpool, UKDepartment of Obesity and EndocrinologyInstitute of Ageing and Chronic Disease, University of Liverpool, Liverpool, UKWarwickshire Institute for the Study of DiabetesEndocrinology and Metabolism, University Hospitals Coventry and Warwickshire NHS Trust, Coventry, UKDivision of Metabolic and Vascular HealthWarwick Medical School, University of Warwick, Warwick, UKCancer Research UK Liverpool Cancer Trials UnitUniversity of Liverpool, Liverpool, UKDepartment of Diabetes and Metabolic MedicineFaculty of Health and Medical Sciences, University of Surrey, Guildford, UKDepartment of Clinical NutritionGerman Institute of Human Nutrition, Potsdam-Rehbruecke, GermanyThe Department of EndocrinologyDiabetes and Nutrition, Charité-University-Medicine Berlin, Berlin, GermanyMetabolic and Molecular Imaging GroupImperial College London, MRC Clinical Sciences Centre, London, UKResearch Institute for Sport and Exercise SciencesLiverpool John Moores University, Liverpool, UKDepartment of Musculoskeletal BiologyInstitute of Ageing and Chronic Disease, Magnetic Resonance and Image Analysis Research Centre, University of Liverpool, Liverpool, UK.
Eur J Endocrinol. 2014 Nov;171(5):561-9. doi: 10.1530/EJE-14-0112.
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.
简单的临床算法，包括脂肪肝指数（FLI）和脂质堆积产物（LAP），已经被开发出来作为非酒精性脂肪性肝病（NAFLD）的替代标志物，这些标志物是使用（半定量）超声构建的。本研究旨在验证 FLI 和 LAP 作为肝脂肪变性的测量指标，这些指标是通过质子磁共振波谱（1H-MRS）定量确定的。
从接受临床、生化和人体测量评估的 168 例 NAFLD 患者和 168 例对照中收集数据。确定 FLI 和 LAP 的值，并评估其作为肝脂肪变性（肝脂肪>5.5%）存在的预测因子，以及通过 1H-MRS 测量的实际肝脂肪含量的预测因子。使用接收者操作特征曲线（AUROC）下的面积来评估 FLI 和 LAP 的判别能力。由于 FLI 也可以解释为肝脂肪变性的预测概率，我们评估了它在我们的队列中的校准程度。使用线性回归和预测区间来评估 FLI 和 LAP 预测肝脂肪含量的能力。在 54 例 2 型糖尿病患者中提供了进一步的验证。
FLI、LAP 和丙氨酸转氨酶能够区分有或无脂肪变性的患者，AUROC 分别为 0.79（IQR=0.74，0.84）、0.78（IQR=0.72，0.83）和 0.83（IQR=0.79，0.88），但不能定量预测肝脂肪。此外，这些算法准确地匹配了我们队列中观察到的肝脂肪变性患者的百分比。
FLI 和 LAP 可用于临床识别或研究目的的肝脂肪变性患者，但不能预测肝脂肪含量。
