Those authors contributed equally to this work.
Editor: Takumi Kawaguchi, Kurume University School of Medicine, Japan
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.
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.
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]; HOMA-IR, 0.831 [0.821–0.842];
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.
NAFLD is closely related to insulin resistance. We determined which insulin resistance index (METS-IR and HOMA-IR) is more useful to predict the prevalence of NAFLD as well as the incidence of NAFLD by analyzing data from a community-based, prospective Korean cohort study. METS-IR showed higher predictive power for the incidence of NAFLD than HOMA-IR (iAUC: 0.683 vs. 0.551,
Non-alcoholic fatty liver disease (NAFLD) is the most common chronic liver disease worldwide. Its global prevalence increased from 20% in 2010 to 25% in 2018 [
Current evidence suggests that both hepatic and peripheral insulin resistance are strongly associated with NAFLD [
The gold standard method for direct evaluation of systemic insulin resistance is the euglycemic-hyperinsulinemic clamp (glucose clamp) [
Therefore, this study aimed to compare the use of the HOMA-IR and METS-IR for the prediction of prevalent and incident NAFLD in a large, community-based, prospective Korean cohort.
All data originated from the Korean Genome and Epidemiology Study (KoGES), a longitudinal, prospective cohort study conducted by the Korea Centers for Disease Control and Prevention to evaluate the risk factors for non-communicable diseases [
From the 10,030 participants in the baseline survey, we excluded 1) those with a history of hepatitis (n=423); 2) men with alcohol consumption ≥30 g/day or women with alcohol consumption ≥20 g/day (n=964); 3) those with insufficient data for calculation of the NAFLD-liver fat score (n=276); and 4) those with insufficient data for calculation of the METS-IR and/or HOMA-IR (n=7) (
Moreover, to compare the predictive power for the incidence of NAFLD of METS-IR and HOMA-IR, we also analyzed the data from a total of 5,438 participants without NAFLD at baseline after excluding 1) those with NAFLD at baseline (n=2,218) and 2) those without follow-up data (n=704) from 8,360 participants without NAFLD at baseline.
The KoGES_Ansan_Ansung cohort protocol was reviewed and approved by the Institutional Review Board (IRB) of the Korea Centers for Disease Control and Prevention. All the participants gave written informed consent. This study protocol conformed to the ethical guidelines of the 1964 Declaration of Helsinki and its later amendments and was approved by the IRB of Nowon Eulji Medical Center (IRB No. 2021-09-025).
Weight and height were measured to the nearest 0.1 kg and 0.001 m, respectively, for calculation of the body mass index (BMI; kg/m2). Waist circumference (WC; cm) was measured in the horizontal plane, midway between the lowest rib and the iliac crest. After at least 5 minutes of rest in a sitting position, the patient’s systolic blood pressure (SBP) and diastolic blood pressure (DBP) were measured. SBP and DBP were defined as the average of the last two of three measured values, with at least a 1-minute interval between each. We calculated the mean blood pressure (MBP) as DBP + 1/3 × (SBP − DBP).
Participants were categorized into four groups according to smoking status: never smoker, former smoker, some day smoker, or every day smoker [
Blood samples of each participant were collected after at least 8 hours of fasting and analyzed with a Hitachi 700-110 Chemistry Analyzer (Hitachi, Ltd., Tokyo, Japan). Concentrations of fasting plasma glucose (FPG), serum insulin, high-density lipoprotein (HDL) cholesterol, triglycerides, aspartate aminotransferase (AST), alanine aminotransferase (ALT), and C-reactive protein (CRP) were measured. Low-density lipoprotein (LDL) cholesterol was calculated by using the Friedewald equation in the case of a triglyceride concentration <400 mg/dL [
Participants’ dietary intake was assessed by using a validated, semi-quantitative, 103-item food frequency questionnaire [
DM was defined as having an FPG concentration ≥126 mg/dL, plasma glucose concentration 2 hours after a 75-g oral glucose tolerance test ≥200 mg/dL, glycosylated hemoglobin ≥6.5%, being treated with anti-diabetic medications, or being treated with insulin therapy [
The METS-IR and HOMA-IR were calculated by using the following formulas [
NAFLD was defined as the NAFLD-liver fat score, calculated as follows: (3) NAFLD-liver fat score = −2.89 + 1.18 × metabolic syndrome (yes: 1, no: 0) + 0.45 × DM (yes: 2, no: 0) + 0.15 × insulin (µIU/mL) + 0.04 × AST (U/L) – 0.94 × AST/ALT. An NAFLD-liver fat score >−0.640 was considered indicative of NALFD [
Clinical characteristics of the 8,360 included participants were compared between those with and those without NAFLD at baseline. Baseline characteristics of the 5,438 participants without NAFLD at baseline were compared between those who developed NAFLD after the baseline survey and those who did not. Categorical variables including sex, smoking status, drinking status, physical activity, DM, HTN, and dyslipidemia were analyzed by using chi-square test and are presented as number (%). Some continuous variables including age, BMI, WC, MBP, FPG, HDL cholesterol, AST, ALT, total energy intake, NAFLD-liver fat score, METS-IR value, and HOMA-IR, which showed P-value for Kolmogorov-Smirnov test ≥0.05, were analyzed by using Student’s t-test and are presented means±standard deviations. The other continuous variables including insulin, triglyceride, and CRP, which showed P-value for Kolmogorov-Smirnov test <0.05, were analyzed by using Mann-Whitney test and are presented as medians (25th percentile, 75th percentile).
For the 8,360 participants at baseline, the predictive powers of the indices for prevalent NAFLD were compared by using area under the receiver operating characteristic (ROC) curves (AUCs). The cut-off points for such prediction were calculated by using the Youden index [
For the 5,438 participants without NAFLD at baseline, a Cox proportional-hazards model was fitted with spline curves to determine the dose-response relationship between each index and incident NAFLD. We calculated the hazard ratio (HR) with its 95% confidence interval (CI) for incident NAFLD for each 1-point increase in each index by using univariable and multivariable Cox proportional-hazards regression analysis. In model 1, we adjusted for age, sex, BMI, WC, physical activity, smoking status, and current drinking status. In model 2, we further adjusted for total caloric intake, serum CRP concentration, DM, HTN, dyslipidemia, and serum ALT concentration. The indices’ predictive powers and discriminatory capabilities for incident NAFLD were assessed by using Harrell’s concordance index and time-dependent ROC curve analysis [
All statistical analyses were performed with SAS statistical software (version 9.4; SAS Institute Inc., Cary, NC, USA) and R software (version 4.1.1; R Foundation for Statistical Computing, Vienna, Austria). The significance level was set at
The number of participants with NAFLD was 2,218. The mean age, BMI, WC, MBP, total caloric intake, NAFLD-liver fat score, METS-IR, and HOMA-IR; the mean concentration of FPG, serum AST, and ALT; as well as the median concentrations of serum insulin, triglycerides, and CRP were higher in participants with than in those without NAFLD at baseline (
The mean age, BMI, WC, MBP, NAFLD-liver fat score, METS-IR, and HOMA-IR; the mean concentrations of FPG, serum AST, and ALT; as well as the median concentrations of serum insulin, triglycerides, and CRP were higher in participants who developed NAFLD after baseline than in those who did not (
During a total of 55,887.0 person-years of follow-up, 2,378 participants (43.7%) newly developed NAFLD. The mean follow-up time was 13.6 years, the incidence rate per 1,000 person-years was 42.6, and the incidence rate per 2 years ranged from 4.1 to 11.0 (
The AUCs of the METS-IR and HOMA-IR were 0.824 (0.814–0.834) and 0.831 (0.821–0.842), respectively, with no significant difference in their predictive powers (
There was a positive dose-response association between the METS-IR and incident NAFLD, whereas the HOMA-IR had a J-shaped association with incident NAFLD (
Harrell’s concordance index of the METS-IR was 0.697 (95% CI, 0.689–0.705), which was significantly higher than that of the HOMA-IR (0.556; 95% CI, 0.546–0.566;
We compared the predictive power of two insulin resistance indices for prevalent and incident NAFLD by using data of a large-scale, community-based, prospective cohort. Both the METS-IR and the HOMA-IR were statistically significantly related to prevalent and incident NAFLD.
The optimal threshold of the HOMA-IR for prediction of prevalent NAFLD was 1.8, lower than the generally accepted cut-off value of 2.5 to define insulin resistance. Considering that both HOMA-IR and METS-IR had similar predictive powers for prevalent NAFLD in this study, it could be better for healthcare providers to apply HOMA-IR value of 1.8 or METS-IR value of 39.3 for the early detection of NAFLD.
Interestingly, the baseline METS-IR and HOMA-IR were both predictive of incident NAFLD over the study period. In addition, the predictive powers of the two indices for incident NAFLD had maintained at both 8 and 16 years after baseline. The optimal thresholds for the prediction of incident NAFLD (35.7 for the METS-IR and 1.4 for the HOMA-IR) were lower than those for prevalent NAFLD (39.3 and 1.8). The METS-IR may be preferable to the HOMA-IR for the prediction of incident NAFLD, as it had a higher predictive power (Heagerty’s iAUC, 0.683 vs. 0.551). Joint use of the METS-IR and HOMA-IR did not increase the predictive power for incident NAFLD over that of the METS-IR alone. This suggests that peripheral insulin resistance is more closely related to the development of NAFLD than hepatic insulin resistance.
There are several possible explanations for the superior predictive power of the METS-IR to that of the HOMA-IR for incident NAFLD in this study. First, as mentioned above, the development of NAFLD could be more closely related to peripheral than to hepatic insulin resistance. NAFLD is closely related to metabolic dysfunctions such as overweight/obesity, abdominal obesity, hypertriglyceridemia, low HDL cholesterolemia, chronic inflammation, impaired fasting glucose/DM, and insulin resistance [
Several limitations of this study warrant discussion. First, NAFLD was defined according to a surrogate marker, namely, the NAFLD-liver fat score. In addition, there was a lack of information about the use of certain medications which can induce NAFLD. Second, insulin resistance was not classified into hepatic insulin resistance and peripheral insulin resistance, because there was a lack of data regarding plasma glucose and serum insulin concentrations 30 minutes after the 75-g oral glucose tolerance test, which are required to calculate hepatic insulin resistance [
In conclusion, both the METS-IR and the HOMA-IR are highly predictive of prevalent NAFLD in middle aged and older Korean adults. Moreover, the METS-IR is superior to the HOMA-IR for the prediction of incident NAFLD. Our findings suggest that the METS-IR is more useful than the HOMA-IR for the early detection and prevention of NAFLD in Korean population. Further clinical trials are warranted to determine which index is most valuable with regard to NAFLD.
Study concept and design: Jun-Hyuk Lee, Jee Hye Han, and Sang Bong Ahn; Data collection: Jun-Hyuk Lee, Kyongmin Park, Hye Sun Lee, and Hoon-Ki Park; Data analysis and interpretation: Jun-Hyuk Lee, Jee Hye Han, and Sang Bong Ahn; Manuscript writing: Jun-Hyuk Lee, Jee Hye Han, and Sang Bong Ahn; Final approval of the manuscript: All authors.
The authors have no conflicts to disclose.
This paper was supported by Eulji University in 2021 (grant number: EJRG-21-13). Data in this study were from the Korean Genome and Epidemiology Study (KoGES; 4851-302), National Research Institute of Health, Centers for Disease Control and Prevention, Ministry for Health and Welfare, Republic of Korea.
alanine aminotransferase
aspartate aminotransferase
area under the receiver operating characteristic curve
body mass index
confidence interval
C-reactive protein
diastolic blood pressure
diabetes mellitus
fasting plasma glucose
high-density lipoprotein
homeostatic model assessment for insulin resistance
hazard ratio
hypertension
integrated area under the receiver operating characteristic curve
Institutional Review Board
Korean Genome and Epidemiology Study
low-density lipoprotein
mean blood pressure
metabolic equivalent of task
metabolic score for insulin resistance
non-alcoholic fatty liver disease
non-alcoholic steatohepatitis
receiver operating characteristic
systolic blood pressure
waist circumference
Flow chart of the study population selection. KoGES, Korean Genome and Epidemiology Study; METS-IR, metabolic score for insulin resistance; HOMA-IR, homeostatic assessment for insulin resistance; NAFLD, non-alcoholic fatty liver disease; AUROC, area under the receiver operating characteristic curve.
Comparison of predictive power for prevalent non-alcoholic fatty liver disease of metabolic score for insulin resistance and homeostasis model assessment for insulin resistance. For the 8,360 participants at baseline, the predictive powers for prevalent NAFLD of METS-IR and HOMA-IR were compared by using area under the receiver operating characteristic curves. The cut-off points for such prediction were calculated by using the Youden index. ROC, receiver operating characteristic; NAFLD, non-alcoholic fatty liver disease; METS-IR, metabolic score for insulin resistance; HOMA-IR, homeostatic assessment model for insulin resistance; AUC, area under the receiver operating characteristic curve.
Cox proportional spline curves showing dose-response association between metabolic score for insulin resistance/homeostatic model assessment for insulin resistance and the incidence of non-alcoholic fatty liver disease. (A) Metabolic score for insulin resistance. (B) Homeostatic model assessment for insulin resistance. For the 5,438 participants without NAFLD at baseline, a Cox proportional-hazards model was fitted with spline curves to determine the dose-response relationship between METS-IR/HOMA-IR and incident NAFLD. METS-IR, metabolic score for insulin resistance; NAFLD, non-alcoholic fatty liver disease; HOMA-IR, homeostatic assessment model for insulin resistance.
Forest plot showing the predictive power for incident non-alcoholic fatty liver disease by subgroups according to obesity and diabetes mellitus status. Heagerty’s integrated AUC was used as time-dependent AUC over the 16-year of follow-up period, with an unadjusted survival analysis framework approach. A bootstrapping method to calculate the differences and 95% CI of Heagerty’s integrated AUC between the METS-IR and HOMA-IR. DM, diabetes mellitus; METS-IR, metabolic score for insulin resistance; HOMA-IR, homeostatic model assessment for insulin resistance; AUC, area under the receiver operating characteristic curve; CI, confidence interval.
Baseline characteristics of the population with or without NAFLD at the baseline survey
Variable | Without NAFLD (n=6,142) | With NAFLD (n=2,218) | Total (n=8,360) | |
---|---|---|---|---|
Men sex | 2,526 (41.1) | 958 (43.2) | 3,484 (41.7) | 0.096 |
Age (years) | 51.7±8.9 | 54.3±8.7 | 52.4±8.9 | <0.001 |
Body mass index (kg/m2) | 23.8±2.9 | 26.5±3.0 | 24.6±3.2 | <0.001 |
Waist circumference (cm) | 79.9±8.1 | 88.9±7.7 | 82.3±8.9 | <0.001 |
MBP (mmHg) | 94.0±12.8 | 102.8±12.4 | 96.3±13.3 | <0.001 |
Smoking status | 0.004 | |||
Never smoker | 4,039 (66.7) | 1,377 (63.0) | 5,416 (65.7) | |
Former smoker | 760 (12.5) | 334 (15.3) | 1,094 (13.3) | |
Some day smoker | 129 (2.1) | 52 (2.4) | 181 (2.2) | |
Every day smoker | 1,129 (18.6) | 421 (19.3) | 1,550 (18.8) | |
Current drinker | 2,591 (42.6) | 833 (38.0) | 3,424 (41.3) | <0.001 |
Physical activity | 0.021 | |||
Low, <7.5 METs-hr/wk | 472 (8.0) | 210 (9.9) | 682 (8.5) | |
Moderate, 7.5–30 METs-hr/wk | 3,639 (61.6) | 1,295 (61.1) | 4,934 (61.5) | |
High, >30 METs-hr/wk | 1,794 (30.4) | 615 (29.0) | 2,409 (30.0) | |
FPG (mg/dL) | 82.8±13.4 | 96.5±30.0 | 86.4±20.2 | <0.001 |
Insulin (µIU/mL) | 6.3 (4.8, 8.2) | 10.1 (7.5, 12.6) | 7.0 (5.2, 9.7) | <0.001 |
Triglyceride (mg/dL) | 119.0 (92.0, 156.0) | 187.0 (144.0, 256.0) | 133.0 (98.0, 185.0) | <0.001 |
HDL cholesterol (mg/dL) | 46.1±10.0 | 40.3±8.5 | 44.5±9.9 | <0.001 |
AST (U/L) | 26.5±7.1 | 34.9±29.6 | 28.7±16.8 | <0.001 |
ALT (U/L) | 22.1±8.9 | 39.6±45.0 | 26.8±25.6 | <0.001 |
CRP (mg/dL) | 0.1 (0.1, 0.2) | 0.2 (0.1, 0.3) | 0.2 (0.1, 0.3) | <0.001 |
Total energy intake (kcal/day) | 1,929.2±699.5 | 1,977.1±731.8 | 1,941.9±708.5 | 0.009 |
Type 2 diabetes | 196 (3.2) | 699 (31.5) | 895 (10.7) | <0.001 |
Hypertension | 1,800 (29.3) | 1,371 (61.8) | 3,171 (37.9) | <0.001 |
Dyslipidemia | 2,375 (38.7) | 1,613 (72.7) | 3,988 (47.7) | <0.001 |
NAFLD-liver fat score | -1.9±0.6 | 0.5±1.5 | -1.3±1.4 | <0.001 |
METS-IR | 35.8±5.6 | 43.3±6.2 | 37.8±6.6 | <0.001 |
HOMA-IR | 1.3±0.6 | 2.6±2.0 | 1.7±1.3 | <0.001 |
Values are presented as mean±standard deviation, median (25th percentile, 75th percentile), or number (%).
NAFLD, non-alcoholic fatty liver disease; MBP, mean blood pressure; MET, metabolic equivalent of task; FPG, fasting plasma glucose; HDL, high-density lipoprotein; AST, aspartate aminotransferase; ALT, alanine aminotransferase; CRP, C-reactive protein; METS-IR, metabolic score for insulin resistance; HOMA-IR, homeostatic model assessment for insulin resistance.
Baseline characteristics of participants without NAFLD at baseline who followed-up at least once after baseline survey
Variable | Not developed NAFLD (n=3,060) | Newly developed NAFLD (n=2,378) | Total (n=5,438) | |
---|---|---|---|---|
Men sex | 1,280 (41.8) | 979 (41.2) | 2,259 (41.5) | 0.643 |
Age (years) | 51.4±9.0 | 52.0±8.5 | 51.7±8.8 | 0.011 |
Body mass index (kg/m2) | 23.0±2.7 | 24.9±2.7 | 23.8±2.9 | <0.001 |
Waist circumference (cm) | 77.6±7.7 | 83.1±7.4 | 80.0±8.1 | <0.001 |
MBP (mmHg) | 92.1±12.5 | 96.3±12.4 | 94.0±12.6 | <0.001 |
Smoking status | 0.895 | |||
Never smoker | 2,031 (67.2) | 1,554 (66.3) | 3,585 (66.8) | |
Former smoker | 380 (12.6) | 306 (13.0) | 686 (12.8) | |
Some day smoker | 65 (2.2) | 49 (2.1) | 114 (2.1) | |
Every day smoker | 547 (18.1) | 436 (18.6) | 983 (18.3) | |
Current drinker | 1,287 (42.4) | 1,034 (43.9) | 2,321 (43.1) | 0.299 |
Physical activity | 0.312 | |||
Low, <7.5 METs-hr/wk | 222 (7.5) | 171 (7.5) | 393 (7.5) | |
Moderate, 7.5–30 METs-hr/wk | 1,813 (61.5) | 1,360 (59.6) | 3,173 (60.7) | |
High, >30 METs-hr/wk | 911 (30.9) | 750 (32.9) | 1,661 (31.8) | |
FPG (mg/dL) | 80.9±8.4 | 84.6±14.8 | 82.5±11.8 | <0.001 |
Insulin (µIU/mL) | 6.2 (4.7, 7.9) | 6.6 (5.0, 8.7) | 6.3 (4.8, 8.2) | <0.001 |
Triglyceride (mg/dL) | 109.0 (85.0, 141.0) | 133.0 (104.0, 181.0) | 119.0 (92.0, 156.0) | <0.001 |
HDL cholesterol (mg/dL) | 47.7±10.3 | 43.9±9.0 | 46.0±9.9 | <0.001 |
AST (U/L) | 26.1±6.7 | 26.8±7.1 | 26.4±6.9 | <0.001 |
ALT (U/L) | 20.8±8.1 | 23.8±9.5 | 22.1±8.9 | <0.001 |
CRP (mg/dL) | 0.1 (0.0, 0.2) | 0.2 (0.1, 0.3) | 0.1 (0.1, 0.2) | <0.001 |
Total energy intake (kcal/day) | 1,930.9±690.7 | 1,949.9±728.3 | 1,939.2±707.3 | 0.336 |
Type 2 diabetes | 49 (1.6) | 108 (4.5) | 157 (2.9) | <0.001 |
Hypertension | 736 (24.1) | 848 (35.7) | 1,584 (29.1) | <0.001 |
Dyslipidemia | 948 (31.0) | 1,143 (48.1) | 2,091 (38.5) | <0.001 |
NAFLD-liver fat score | -2.1±0.6 | -1.7±0.6 | -1.9±0.6 | <0.001 |
METS-IR | 33.9±4.9 | 38.3±5.3 | 35.8±5.5 | <0.001 |
HOMA-IR | 1.3±0.6 | 1.4±0.6 | 1.3±0.6 | <0.001 |
Values are presented as mean±standard deviation, median (25th percentile, 75th percentile), or number (%).
NAFLD, non-alcoholic fatty liver disease; MBP, mean blood pressure; MET, metabolic equivalent of task; FPG, fasting plasma glucose; HDL, high-density lipoprotein; AST, aspartate aminotransferase; ALT, alanine aminotransferase; CRP, C-reactive protein; METS-IR, metabolic score for insulin resistance; HOMA-IR, homeostatic model assessment for insulin resistance.
Incidence of non-alcoholic fatty liver disease during follow-up
Year range | Follow-up | Total | Incidence cases | Incidence rate (cases/2 years) |
---|---|---|---|---|
2001–2002 | Baseline | 5,438 | ||
2003–2004 | 2 years | 3,745 | 411 | 11.0 |
2005–2006 | 4 years | 4,443 | 405 | 9.1 |
2007–2008 | 6 years | 4,116 | 432 | 10.5 |
2009–2010 | 8 years | 4,163 | 384 | 9.2 |
2011–2012 | 10 years | 3,931 | 184 | 4.7 |
2013–2014 | 12 years | 3,745 | 180 | 4.8 |
2015–2016 | 14 years | 3,844 | 235 | 6.1 |
2017–2018 | 16 years | 3,582 | 147 | 4.1 |
Cox proportional hazard regression model for incident non-alcoholic fatty liver disease of two different insulin resistant indices
Incident NAFLD |
|||
---|---|---|---|
HR | 95% CI | ||
METS-IR (per 1 increment) | |||
Unadjusted | 1.12 | 1.11–1.13 | <0.001 |
Model 1 | 1.12 | 1.10–1.13 | <0.001 |
Model 2 | 1.11 | 1.09–1.13 | <0.001 |
HOMA-IR (per 1 increment) | |||
Unadjusted | 1.41 | 1.32–1.51 | <0.001 |
Model 1 | 1.28 | 1.19–1.37 | <0.001 |
Model 2 | 1.30 | 1.21–1.39 | <0.001 |
Model 1: adjusted for age, sex, body mass index, waist circumference, physical activity, smoking status, and drinking status; model 2: adjusted for the variables used in model 1 plus daily total energy intake, serum C-reactive protein level, type 2 diabetes mellitus, hypertension, dyslipidemia, and serum alanine aminotransferase level.
NAFLD, non-alcoholic fatty liver disease; HR, hazard ratio; CI, confidence interval; METS-IR, metabolic score for insulin resistance; HOMA-IR, homeostatic model assessment for insulin resistance.
Comparison of predictive ability for incident non-alcoholic fatty liver disease between METS-IR and HOMA-IR using time-dependent receiver operating characteristics curves analysis
Cut-off point | Harrell’s C index | Heagerty’s iAUC | Heagerty’s incident/dynamic AUC (8 years) | Heagerty’s incident/dynamic AUC (16 years) | |
---|---|---|---|---|---|
METS-IR, (1) | 35.7 | 0.697 (0.689 to 0.705) | 0.683 (0.671 to 0.695) | 0.669 (0.663 to 0.675) | 0.670 (0.662 to 0.678) |
HOMA-IR, (2) | 1.4 | 0.556 (0.546 to 0.566) | 0.551 (0.539 to 0.563) | 0.557 (0.553 to 0.561) | 0.556 (0.548 to 0.564) |
METS-IR+HOMA-IR, (3) | 0.700 (0.692 to 0.708) | 0.685 (0.673 to 0.697) | 0.673 (0.667 to 0.679) | 0.672 (0.664 to 0.680) | |
Difference (1)-(2) | 0.131 (0.113 to 0.149) | 0.131 (0.113 to 0.149) | 0.112 (0.104 to 0.12) | 0.114 (0.104 to 0.124) | |
Difference (1)-(3) | -0.003 (-0.011 to 0.005) | -0.002 (-0.016 to 0.012) | -0.005 (-0.009 to -0.001) | -0.002 (-0.008 to 0.004) | |
Difference (2)-(3) | -0.144 (-0.150 to -0.138) | -0.133 (-0.145 to -0.121) | -0.116 (-0.120 to -0.112) | -0.116 (-0.122 to -0.110) | |
<0.001 | <0.001 | <0.001 | <0.001 | ||
0.453 | 0.775 | 0.012 | 0.505 | ||
<0.001 | <0.001 | <0.001 | <0.001 |
Significance was set at
METS-IR, metabolic score for insulin resistance; HOMA-IR, homeostatic model assessment for insulin resistance; iAUC, integrated area under the receiver operating characteristic curve; AUC, area under the receiver operating characteristic curve.