Daniel J Cuthbertson1, Martin O Weickert1, Daniel Lythgoe2, Victoria S Sprung1, Rebecca Dobson1, Fariba Shoajee-Moradie2, Margot Umpleby2, Andreas F H Pfeiffer1, E Louise Thomas2, Jimmy D Bell2, Helen Jones2, Graham J Kemp2. 1. 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 2. 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.
Abstract
BACKGROUND AND AIMS: 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). METHODS: 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. RESULTS: 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. CONCLUSIONS: FLI and LAP may be used to identify patients with hepatic steatosis clinically or for research purposes but could not predict liver fat content.
BACKGROUND AND AIMS: 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). METHODS: 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. RESULTS: 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. CONCLUSIONS: 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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