Evaluation of surrogate measures of insulin sensitivity - correlation with gold standard is not enough

Abstract

Background: Impaired insulin sensitivity is a key abnormality underlying the development of type 2 diabetes. Measuring insulin sensitivity is therefore of importance in identifying individuals at risk of developing diabetes and for the evaluation of diabetes-focused interventions. A number of measures have been proposed for this purpose. Among these the hyperinsulinemic euglycemic clamp (HEC) is considered the gold standard. However, as the HEC is a costly, time consuming and invasive method requiring trained staff, there is a need for simpler so called surrogate measures.

Main message: A frequently used approach to evaluate surrogate measures is through correlation with the HEC. We discuss limitations with this method. We suggest other aspects to take into consideration, such as repeatability, reproducibility, systematic biases and discrimination ability. In addition, we focus on three frequently used surrogate measures. We argue that they are one-to-one transformations of each other, and therefore question the benefits of further comparison between them. They give the same results in all rank-based methods, for instance Spearman correlations, Mann-Whitney tests and receiver operating characteristic (ROC) analysis.

Conclusions: We suggest investigating further aspects than correlation alone when evaluating a surrogate measure of insulin sensitivity. We recommend choosing one of the three surrogate measures HOMA-IR, QUICKI and FIRI for analysis of a clinical study.

Keywords: Correlation; Insulin sensitivity; Surrogate measure.

Fig. 1

Simulations with corresponding correlations. a Linear. b Monotonic. c Outlier. d Monotonic

Fig. 2

Simulations of QUICKI, HOMA-IR and FIRI

Fig. 3

Scatter plots of QUICKI, HOMA-IR and FIRI against M_LBM

Fig. 4

ROC curves of QUICKI, HOMA-IR and FIRI