Development and validation of a simple index system to predict nonalcoholic fatty liver disease

Park, Young Jin; Lim, Jie Hyang; Kwon, Eun Ryoung; Kim, Hee Kyoung; Jung, Myoung Chul; Seol, Kyoung Hwan; Noh, Woo Yong; Kim, Na Eun

doi:10.3350/kjhep.2011.17.1.19

Cited by 16 publications

(15 citation statements)

References 20 publications

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“…In line with our findings, Kotronen et al also reported no significant improvement in diagnostic accuracy by the inclusion of genetic information [14]. Other algorithms to diagnose FLD incorporate different covariates from the ones considered here [15-18], thereby reflecting again the difficulty to select predictors for a generally useful diagnostic model for FLD.…”

Section: Discussionsupporting

confidence: 86%

Diagnosing Fatty Liver Disease: A Comparative Evaluation of Metabolic Markers, Phenotypes, Genotypes and Established Biomarkers

Siegert

Wang-Sattler

et al. 2013

PLoS ONE

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BackgroundTo date, liver biopsy is the only means of reliable diagnosis for fatty liver disease (FLD). Owing to the inevitable biopsy-associated health risks, however, the development of valid noninvasive diagnostic tools for FLD is well warranted.AimWe evaluated a particular metabolic profile with regard to its ability to diagnose FLD and compared its performance to that of established phenotypes, conventional biomarkers and disease-associated genotypes.MethodsThe study population comprised 115 patients with ultrasound-diagnosed FLD and 115 sex- and age-matched controls for whom the serum concentration was measured of 138 different metabolites, including acylcarnitines, amino acids, biogenic amines, hexose, phosphatidylcholines (PCs), lyso-PCs and sphingomyelins. Established phenotypes, biomarkers, disease-associated genotypes and metabolite data were included in diagnostic models for FLD using logistic regression and partial least-squares discriminant analysis. The discriminative power of the ensuing models was compared with respect to area under curve (AUC), integrated discrimination improvement (IDI) and by way of cross-validation (CV).ResultsUse of metabolic markers for predicting FLD showed the best performance among all considered types of markers, yielding an AUC of 0.8993. Additional information on phenotypes, conventional biomarkers or genotypes did not significantly improve this performance. Phospholipids and branched-chain amino acids were most informative for predicting FLD.ConclusionWe show that the inclusion of metabolite data may substantially increase the power to diagnose FLD over that of models based solely upon phenotypes and conventional biomarkers.

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Section: Discussionsupporting

confidence: 86%

Diagnosing Fatty Liver Disease: A Comparative Evaluation of Metabolic Markers, Phenotypes, Genotypes and Established Biomarkers

Siegert

Wang-Sattler

et al. 2013

PLoS ONE

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“…In this study, eight indexes, i.e. FLI [5], LAP [7,28] (derived in Europe), FSI [29] (derived in USA), FLD index [25], HSI [6], Korea index (by Park et al [30], no official name), NAFLD index [23] and ZJU index [24,31] (derived in East Asia), were included and validated, using a large population of 13,122 subjects in western China. This study confirmed the significance of FLI as a predictor of NAFLD.…”

Section: Discussionmentioning

confidence: 99%

Validation of simple indexes for nonalcoholic fatty liver disease in western China: a retrospective cross-sectional study

Zhu

Zhang

et al. 2018

Endocr J

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Abstract. Various noninvasive algorithms have been developed for predicting the presence of nonalcoholic fatty liver disease (NAFLD). The evaluation of the indexes' diagnostic performance has been reported in Europe and Asia over the past decade; however, external validation of them in China is rare. This study was aimed to evaluate various indexes for NAFLD in western China. It was a retrospective cross-sectional study, using data from a large-scale health check-up project at Sichuan provincial hospital. Receiver operating characteristic (ROC) curves of eight indexes, including the fatty liver index (FLI), the hepatic steatosis index, lipid accumulation product and etc., were developed to predict ultrasonographic NAFLD. There were 13,122 subjects in this study (2,692 NAFLD patients and 10,430 non-NAFLD participants). The area under ROC curve of FLI for predicting NAFLD was 0.880 (95% confidence interval, 0.874-0.886), which was significantly higher than other seven indexes. Accuracy, sensitivity and specificity of FLI for NAFLD were good (cut-off value = 30, 0.782, 0.832, 0.770 and cut-off value = 60, 0.838, 0.443, 0.940, respectively). Furthermore, FLI also presented advantages in expenditure and accessibility, compared with other indexes. It supports FLI as an easily accessible index for physicians and a reliable predictor for NAFLD screening in western China.

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“…Previous studies have reported an increased mean age of patients diagnosed with fatty liver compared to normal controls [29,32]. This appeared to correspond however to an increased mean WT [32] or BMI [29] with age.…”

Section: Discussionmentioning

confidence: 89%

“…This appeared to correspond however to an increased mean WT [32] or BMI [29] with age. To account for any correlation between weight and BMI with age, in this study, liver fat content was normalized to total body fat and values were compared between age categories.…”

Section: Discussionmentioning

confidence: 99%

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Noninvasive Quantification of Hepatic Steatosis: Relationship Between Obesity Status and Liver Fat Content

McLeay¹,

Morrish²,

Ponnuswamy³

et al. 2014

TOOBESJ

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Abstract:The aim of this study was to assess and compare fat content within the liver for normal (body mass index (BMI) < 25 kg/m 2 ), overweight (25-30 kg/m 2 ) and obese ( 30 kg/m 2 ) subjects using a noninvasive, non-contrast computed tomography (CT) quantification method. Adult subjects aged 18-60 yrs scheduled to undergo CT examination of the abdominal region were recruited for this study, stratified across BMI categories. Liver volume, fat content, and lean liver volume were determined using CT methods. A total of 100 subjects were recruited, including 30 normal weight, 31 overweight, and 39 obese. Total liver volume increased with BMI, with mean values of 1138 ± 277, 1374 ± 331, and 1766 ± 389 cm 3 for the normal, overweight, and obese, respectively (P < 0.001), which was due to an increase in both liver fat content and lean liver volume with BMI. Some obese subjects had no or minimal hepatic fat content. The prevalence of mild fatty liver in this study of 100 subjects was overestimated for all BMI categories using a range of qualitative diagnostic measures, with predicted prevalence of fatty liver in obese subjects ranging from 76.9% for liver-to-spleen ratio 1.1 to 89.7% for liver attenuation index (liver HU -spleen HU) 40, compared to 66.7% by quantification of fat content. Results show that total liver volume increases with BMI, however, not all obese subjects display fatty infiltration of the liver. CT quantification of liver fat content may be suitable for accurate diagnosis of hepatic steatosis in clinical practice and assessment of donor livers for transplantation.

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Development and validation of a simple index system to predict nonalcoholic fatty liver disease

Cited by 16 publications

References 20 publications

Diagnosing Fatty Liver Disease: A Comparative Evaluation of Metabolic Markers, Phenotypes, Genotypes and Established Biomarkers

Diagnosing Fatty Liver Disease: A Comparative Evaluation of Metabolic Markers, Phenotypes, Genotypes and Established Biomarkers

Validation of simple indexes for nonalcoholic fatty liver disease in western China: a retrospective cross-sectional study

Noninvasive Quantification of Hepatic Steatosis: Relationship Between Obesity Status and Liver Fat Content

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