J Obes Metab Syndr 2021; 30(4): 403-404
Published online December 30, 2021 https://doi.org/10.7570/jomes21065
Copyright © Korean Society for the Study of Obesity.
1Integrated Research Institute for Natural Ingredients and Functional Foods and 2Department of Family Medicine and Biomedical Research Institute, Pusan National University Yangsan Hospital, Yangsan; 3Department of Medical Education, Pusan National University School of Medicine, Yangsan, Korea
Sang Yeoup Lee
Department of Family Medicine, Pusan National University Yangsan Hospital, 20 Geumo-ro, Mulgeum-eup, Yangsan 50612, Korea
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
Insulin resistance and visceral adiposity are common features of metabolic syndrome (MetS), although the pathophysiology of MetS is very complex.1 The hyperinsulinemic-euglycemic clamp technique is the “gold standard” test for the evaluation of insulin resistance and insulin sensitivity, but this method is time-consuming and inconvenient, making it difficult to use in a clinical setting. Therefore, many surrogate markers have been developed that can be used to evaluate insulin resistance and insulin sensitivity, starting with the homeostatic model assessment of insulin resistance (HOMA-IR) and quantitative insulin sensitivity check index.2 Endukuru et al.’s study3 is very informative in that the authors evaluated almost all known surrogate markers of insulin resistance and insulin sensitivity in the same study subjects. As a result, the authors3 presented a cut-off of several surrogate markers that can detect risk groups for MetS in Southern Indian adults. At the very least it is useful data for clinical application in the relevant region, although these results need to be confirmed with a larger number of study subjects in various regions.
However, if some additional analysis was performed as follows, readers will be able to better understand and apply these findings to clinical practice. The first thing I would like to mention is the comparison of diagnostic values. In this study, the terms “higher,” “lower,” or “best” were used when presenting the area under the curve (AUC) values among various surrogate markers using the receiver operating characteristic (ROC). However, as the authors mentioned in the statistical section of the research methods, comparing diagnostic values using ROC is not simply a comparison of AUC values, so such expressions are inappropriate without providing statistical values. In other words, as in the study of Lee et al.,4 AUC comparisons should be performed using programs such as MedCalc (Ostend, Belgium) to determine the diagnostic value for MetS among surrogate markers and a
The author declares no conflict of interest.
This work was supported by a 2-Year Research Grant of Pusan National University.