Using Oral Challenge Testing to Assess Insulin Action and Secretion With Mathematical Modeling

Abstract

There is no optimal method to measure insulin resistance or insulin secretion in large clinical studies or in clinical practice. The convenient methods that have been proposed as suitable for large clinical studies have been subject to criticism for limitations when studying individuals with diabetes and with different etiologies of glucose dysregulation, or in populations of diverse racial and ethnic backgrounds (1–3). It has also been pointed out that some methods reflect only part of the complex relationships that define glucose-insulin homeostasis (3,4). There is broad consensus among the scientific community that with the euglycemic-hyperinsulinemic clamp, insulin resistance can be measured (5,6), and by hyperglycemia clamping, measurement of insulin secretion is possible (5,6). Additionally, scientific consensus is that the minimal model used with the frequently sampled intravenous glucose tolerance test (FSIVGTT) provides reliable measures of both insulin secretion and insulin resistance (7). However, these testing regimens required specially trained personnel and are labor intensive, limiting their use to specialized research centers and, for practical purposes, to application in limited numbers of subjects. Standing somewhat in contrast to the sophistication of procedures like the glucose clamp or the FSIVGTT has been an unadorned oral glucose tolerance test (OGTT). An OGTT is a well-established clinical test with translatable diagnostic parameters and can be performed in most clinical centers, and indeed can be used in large clinical trials (8,9). Many investigators have worked to amplify the knowledge that can be garnered from the OGTT. An extensive body of data have been developed using glucose tracers to study splanchnic uptake and peripheral delivery of ingested glucose and the effect on endogenous glucose production and on systemic glucose disposal. Combining indirect calorimetry with an OGTT has …