Accurate method to estimate insulin resistance from multiple regression models using data of metabolic syndrome and oral glucose tolerance test.
OBJECTIVE
How to measure insulin resistance (IR) accurately and conveniently is a critical issue for both clinical practice and research. In the present study, we tried to modify the β-cell function, insulin sensitivity, and glucose tolerance test (BIGTT) in patients with normal glucose tolerance (NGT) and abnormal glucose tolerance (AGT) by oral glucose tolerance test (OGTT) and metabolic syndrome (MetS) components.


METHODS
There were 327 participants enrolled and divided into NGT or AGT. Data from 75% of the participants were used to build the models, and the remaining 25% were used for external validation. Steady-state plasma glucose (SSPG) concentration derived from the insulin suppression test was regarded as the standard measurement for IR. Five models were built from multiple regression: model 1 (MetS model with sex, age and MetS components); model 2 (simple OGTT model with sex, age, plasma glucose, and insulin concentrations at 0 and 120 min during OGTT); model 3 (full OGTT model with sex, age, and plasma glucose and insulin concentrations at 0, 30, 60, 90, 120, and 180 min during OGTT); model 4 (simple combined model): model 1 and model 2; and model 5 (full model): model 1 and 3.


RESULTS
In general, our models had higher r (2) compared with surrogates derived from OGTT, such as homeostasis model assessment-insulin resistance and quantitative insulin sensitivity check index. Among them, model 5 had the highest r (2) (0.505 in NGT, 0.556 in AGT, respectively).


CONCLUSIONS
Our modified BIGTT models proved to be accurate and easy methods for estimating IR, and can be used in clinical practice and research.
Division of Endocrinology and Metabolism Department of Internal Medicine Shuang Ho Hospital Taipei Taiwan ; Graduate Institute of Clinical Medicine College of Medicine Taipei Medical University Taipei Taiwan.
Chung-Ze
CZ
Wu
Division of Endocrinology and Metabolism Department of Internal Medicine Shuang Ho Hospital Taipei Taiwan.
Jiunn-Diann
JD
Lin
Department of Internal Medicine Cardinal Tien Hospital School of Medicine Fu Jen Catholic University Taipei Taiwan.
Te-Lin
TL
Hsia
Department of Family Medicine Cardinal Tien Hospital School of Medicine Fu Jen Catholic University Taipei Taiwan.
Chun-Hsien
CH
Hsu
Division of Endocrinology and Metabolism Tri-Service General Hospital National Defense Medical Center Taipei Taiwan.
Chang-Hsun
CH
Hsieh
Division of Clinical Pathology Department of Pathology Tri-Service General Hospital National Defense Medical Center Taipei Taiwan ; Department of Medical Laboratory Science and Biotechnology Yuanpei University Hsinchu Taiwan.
Jin-Biou
JB
Chang
Division of Nephrology Department of Internal Medicine Tri-Service General Hospital National Defense Medical Center Taipei Taiwan.
Jin-Shuen
JS
Chen
Graduate School of Gerontic Technology and Service Management Nan Kai University of Technology Nan Tou County Taiwan.
Chun
C
Pei
Department of Internal Medicine Cardinal Tien Hospital School of Medicine Fu Jen Catholic University Taipei Taiwan.
Dee
D
Pei
Department of Pathology Cardinal Tien Hospital School of Medicine Fu Jen Catholic University Taipei Taiwan ; School of Medicine Catholic Fu Jen University New Taipei Taiwan.
Yen-Lin
YL
Chen
Insulin resistance; Oral glucose tolerance test; Steady‐state plasma glucose