The usefulness of metabolic score for insulin resistance for the prediction of incident non-alcoholic fatty liver disease in Korean adults
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Background/Aims: The early detection and prevention of non-alcoholic fatty liver disease (NAFLD) has been emphasized considering the burden of this disease. Both hepatic and peripheral insulin resistances are strongly associated with NAFLD. We aimed to compare the predictive powers of a hepatic insulin resistance index, the homeostatic model assessment for insulin resistance (HOMA-IR), and a novel peripheral insulin resistance index, the metabolic score for insulin resistance (METS-IR), for the prediction of prevalent and incident NAFLD. Methods: Data from 8,360 adults aged 40–69 years at baseline and 5,438 adults without NAFLD who were followed-up at least once after the baseline survey in the Korean Genome and Epidemiology Study were analyzed. The survey was performed biennially, up to the eighth follow-up. Results: The predictive powers of the METS-IR and HOMA-IR for prevalent NAFLD were not significantly different (area under the receiver operating characteristic [ROC] curve [95% confidence interval]: METS-IR, 0.824 [0.814–0.834]; HOMAIR, 0.831 [0.821–0.842]; P=0.276). The area under the time-dependent ROC curve (Heagerty’s integrated area under the curve) of the METS-IR for incident NAFLD was 0.683 (0.671–0.695), significantly higher than that of the HOMA-IR (0.551 [0.539–0.563], P<0.001). Conclusions: The METS-IR is superior to the HOMA-IR for the prediction of incident NAFLD and is not inferior to the HOMA-IR for the prediction of prevalent NAFLD. This suggests that the METS-IR can be a more useful insulin resistance index than the HOMA-IR for the early detection and prevention of NAFLD in Korean population.
Abstract
Background/Aims: The early detection and prevention of non-alcoholic fatty liver disease (NAFLD) has been emphasized considering the burden of this disease. Both hepatic and peripheral insulin resistances are strongly associated with NAFLD. We aimed to compare the predictive powers of a hepatic insulin resistance index, the homeostatic model assessment for insulin resistance (HOMA-IR), and a novel peripheral insulin resistance index, the metabolic score for insulin resistance (METS-IR), for the prediction of prevalent and incident NAFLD. Methods: Data from 8,360 adults aged 40–69 years at baseline and 5,438 adults without NAFLD who were followed-up at least once after the baseline survey in the Korean Genome and Epidemiology Study were analyzed. The survey was performed biennially, up to the eighth follow-up. Results: The predictive powers of the METS-IR and HOMA-IR for prevalent NAFLD were not significantly different (area under the receiver operating characteristic [ROC] curve [95% confidence interval]: METS-IR, 0.824 [0.814–0.834]; HOMAIR, 0.831 [0.821–0.842]; P=0.276). The area under the time-dependent ROC curve (Heagerty’s integrated area under the curve) of the METS-IR for incident NAFLD was 0.683 (0.671–0.695), significantly higher than that of the HOMA-IR (0.551 [0.539–0.563], P<0.001). Conclusions: The METS-IR is superior to the HOMA-IR for the prediction of incident NAFLD and is not inferior to the HOMA-IR for the prediction of prevalent NAFLD. This suggests that the METS-IR can be a more useful insulin resistance index than the HOMA-IR for the early detection and prevention of NAFLD in Korean population.
참고문헌 (40)
- Younossi Z, "Global perspectives on nonalcoholic fatty liver disease and nonalcoholic steatohepatitis", Hepatology, 69, pp.2672~2682 (2019)
- Im HJ, "Systematic review on the prevalence of nonalcoholic fatty liver disease in South Korea", Clin Res Hepatol Gastroenterol, 45, pp.101526~ (2021)
- Marchesini G, "NAFLD incidence and remission : only a matter of weight gain and weight loss?", J Hepatol, 62, pp.15~17 (2015)
- 강성희, "KASL clinical practice guidelines: Management of nonalcoholic fatty liver disease", Clinical and Molecular Hepatology, 27(3), pp.363~401 (2021), 대한간학회
- Duseja A, "Epidemiology and risk factors of nonalcoholic fatty liver disease(NAFLD)", Hepatol Int, 7(Suppl 2), pp.755~764 (2013)
- Gruben N, "Nonalcoholic fatty liver disease : a main driver of insulin resistance or a dangerous liaison?", Biochim Biophys Acta, 1842, pp.2329~2343 (2014)
- European Association for the Study of the Liver (EASL), "EASL-EASD-EASO clinical practice guidelines for the management of non-alcoholic fatty liver disease", J Hepatol, 64, pp.1388~1402 (2016)
- Birkenfeld AL, "Nonalcoholic fatty liver disease, hepatic insulin resistance, and type 2 diabetes", Hepatology, 59, pp.713~723 (2014)
- Qureshi K, "Comparative evaluation of whole body and hepatic insulin resistance using indices from oral glucose tolerance test in morbidly obese subjects with nonalcoholic fatty liver disease", J Obes, 2010, pp.741521~ (2010)
- Santoleri D, "Resolving the paradox of hepatic insulin resistance", Cell Mol Gastroenterol Hepatol, 7, pp.447~456 (2019)
- Sonia M. Najjar, "Hepatic Insulin Clearance: Mechanism and Physiology", Physiology, 34(3), pp.198~215 (2019), American Physiological Society[DOI]
- Hwang JH, "Increased intrahepatic triglyceride is associated with peripheral insulin resistance : in vivo MR imaging and spectroscopy studies", Am J Physiol Endocrinol Metab, 293, pp.E1663~E1669 (2007)
- Utzschneider KM, "Review : the role of insulin resistance in nonalcoholic fatty liver disease", J Clin Endocrinol Metab, 91, pp.4753~4761 (2006)
- DeFronzo RA, "Glucose clamp technique : a method for quantifying insulin secretion and resistance", Am J Physiol, 237, pp.E214~E223 (1979)
- Matthews DR, "Homeostasis model assessment : insulin resistance and beta-cell function from fasting plasma glucose and insulin concentrations in man", Diabetologia, 28, pp.412~419 (1985)
- Salgado AL, "Insulin resistance index(HOMA-IR)in the differentiation of patients with non-alcoholic fatty liver disease and healthy individuals", Arq Gastroenterol, 47, pp.165~169 (2010)
- Isokuortti E, "Use of HOMA-IR to diagnose non-alcoholic fatty liver disease : a population-based and interlaboratory study", Diabetologia, 60, pp.1873~1882 (2017)
- Bello-Chavolla OY, "METS-IR, a novel score to evaluate insulin sensitivity, is predictive of visceral adiposity and incident type 2 diabetes", Eur J Endocrinol, 178, pp.533~544 (2018)
- Kim Y, "Cohort profile : the Korean genome and epidemiology study(KoGES)consortium", Int J Epidemiol, 46, pp.e20~ (2017)
- "Follow-up status according to each KoGES cohort (Kor)"[URL]
- "Adult Tobacco Use Information"[URL]
- Ainsworth BE, "Compendium of physical activities : an update of activity codes and MET intensities", Med Sci Sports Exerc, 32(9), pp.498~504 (2000)
- 장민혜, "성인에서 신체활동이 골절 발생에 미치는 영향: 한국 지역사회 코호트 자료에 기반", 대한스포츠의학회지, 35(2), pp.97~102 (2017), 대한스포츠의학회[DOI]
- Friedewald WT, "Estimation of the concentration of low-density lipoprotein cholesterol in plasma, without use of the preparative ultracentrifuge", Clin Chem, 18, pp.499~502 (1972)
- Ahn Y, "Validation and reproducibility of food frequency questionnaire for Korean genome epidemiologic study", Eur J Clin Nutr, 61, pp.1435~1441 (2007)
- American Diabetes Association, "2. Classification and Diagnosis of Diabetes: Standards of Medical Care in Diabetes—2019", Diabetes Care, 42(Supplement_1), pp.S13~S28 (2018), American Diabetes Association[DOI]
- Chobanian AV, "The seventh report of the joint national committee on prevention, detection, evaluation, and treatment of high blood pressure : the JNC 7 report", JAMA, 289, pp.2560~2572 (2003)
- Expert Panel on Detection, "Executive summary of the third report of the national cholesterol education program(NCEP)Expert panel on detection, evaluation, and treatment of high blood cholesterol in adults(Adult Treatment Panel III)", JAMA, 285, pp.2486~2497 (2001)
- Kotronen A, "Prediction of non-alcoholic fatty liver disease and liver fat using metabolic and genetic factors", Gastroenterology, 137, pp.865~872 (2009)
- Youden WJ, "Index for rating diagnostic tests", Cancer, 3, pp.32~35 (1950)
- Harrell FE Jr, "Regression models for prognostic prediction : advantages, problems, and suggested solutions", Cancer Treat Rep, 69, pp.1071~1077 (1985)
- Heagerty PJ, "Time-dependent ROC curves for censored survival data and a diagnostic marker", Biometrics, 56, pp.337~344 (2000)
- Heagerty PJ, "Survival model predictive accuracy and ROC curves", Biometrics, 61, pp.92~105 (2005)
- Kamarudin AN, "Time-dependent ROC curve analysis in medical research : current methods and applications", BMC Med Res Methodol, 17, pp.53~ (2017)
- Contal C, "An application of changepoint methods instudying the effect of age on survival in breast cancer", Comput StatData Anal, 30, pp.253~270 (1999)
- Jarvis H, "Metabolic risk factors and incident advanced liver disease in non-alcoholic fatty liver disease(NAFLD) : a systematic review and meta-analysis of population-based observational studies", PLoS Med, 17, pp.e1003100~ (2020)
- 이상열, "Differences in Insulin Sensitivity and Secretory Capacity Based on OGTT in Subjects with Impaired Glucose Regulation", The Korean Journal of Internal Medicine, 22(4), pp.270~274 (2007), 대한내과학회
- Roh E, "Comparison of pancreatic volume and fat amount linked with glucose homeostasis between healthy Caucasians and Koreans", Diabetes Obes Metab, 20, pp.2642~2652 (2018)
- 이윤정, "High-Carbohydrate Diets and Food Patterns and Their Associations with Metabolic Disease in the Korean Population", Yonsei Medical Journal, 59(7), pp.834~842 (2018), 연세대학교의과대학[DOI]
- Abdul-Ghani MA, "Muscle and liver insulin resistance indexes derived from the oral glucose tolerance test", Diabetes Care, 30, pp.89~94 (2007)