Title:Insight into the Predictive Power of Surrogate Diagnostic Indices for
Identifying Individuals with Metabolic Syndrome
Volume: 24
Issue: 11
Author(s): Shaghayegh Hosseinkhani, Katayoon Forouzanfar, Nastaran Hadizadeh, Farideh Razi, Somayeh Darzi and Fatemeh Bandarian*
Affiliation:
- Metabolomics and Genomics Research Center, Endocrinology and Metabolism Molecular-
Cellular Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran
Keywords:
Metabolic syndrome, MetS, insulin resistance, insulin indices, receiver operating characteristic, BMI.
Abstract:
Background: This study aimed to assess the diagnostic capability of insulin surrogate
measurements in identifying individuals with metabolic syndrome (MetS) and propose applicable
indices derived from fasting values, particularly in large study populations.
Methods: Data were collected from the datasets of the Surveillance of Risk Factors of NCDs in
Iran Study (STEPS). MetS was defined based on the National Cholesterol Education Program
(NCEP) criteria. Various insulin surrogate indices, including Homeostasis Model Assessment
(HOMA), Quantitative Insulin Sensitivity Check Index (QUICKI), Fasting glucose to insulin
ratio (FGIR), Reynaud, Reciprocal insulin, McAuley, Metabolic Score for Insulin Resistance
(METS-IR), Triglyceride-glucose index (TyG), TG/ HDL-C, TG/ BMI, and TG/ WC
ratio were assessed. Receiver Operating Characteristic (ROC) curves were used to assess pathologic
conditions and determine the optimal cut-off through the highest score of the Youden index.
Also, Area Under the Curve (AUC) values were established for each index totally and according
to sex, age, and BMI differences.
Results: The study population consisted of 373 individuals (49.9% women; 75.1% middle age,
39.1% obese, and 27.3% overweight), of whom 117 (31.4%) had MetS. The METS-IR (AUC:
0.856; 95% CI: 0.817-0.895), TG/ HDL-C (AUC: 0.820; 95% CI: 0.775-0.886), TyG (AUC:
0.808; 95% CI: 0.759-0.857), and McAuley (AUC: 0.804; 95% CI: 0.757-0.852) indices provided
the greatest AUC respectively for detection of MetS. The values of AUC for all the indices
were higher in men than women. This trend was consistent after data stratification based on
BMI categories, middle age, and senile individuals.
Conclusion: The present study indicated that indices of insulin, including METS-IR, TG/HDLC,
TyG, and McAuley, have an equal or better capacity in determining the risk of MetS than
HOMA-IR, are capable of identifying individuals with MetS and may provide a simple approach
for identifying populations at risk of insulin resistance.
