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What should be the criteria for diagnosis of nondiabetes, pre-diabetes, and diabetes? Michael Stern (San Antonio, TX) opened the conference by discussing approaches to identifying pre-diabetes, noting that, of course, there is always pre-diabetes before diabetes and that, of course, diabetes is associated with a number of complications such that pre-diabetes cannot be considered a benign condition (as it is clearly associated, for example, with increased cardiovascular risk). Pre-diabetes is, however, an asymptomatic condition not associated with functional impairment, Stern argued, suggesting that if a state is associated with future morbidity and mortality, one should not use the paradigm of treating illness in devising approaches to manage the condition. Citing the adage “prediction is very difficult, especially about the future,” variously attributed to Niels Bohr and Yogi Bera, he pointed out that predictions applying to a group differ somewhat from those applying to individuals. He reviewed a wellrecognized approach to assessing the performance of continuous risk factors, the receiver operating characteristic (ROC) curve of sensitivity vs. falsepositive rate, with the area under the curve (AUC) a measure of the reliability of the test, ranging from 0.5 for a test no better than a flip of a coin to 1.0 for a completely reliable test (1). Relative risk ratios that are considered important are associated with a very modest AUCROC, with an odds ratio of 1.5 only associated with an AUCROC of 0.56 and relative risk ratios of 9 –10 required for AUCROC 0.8. It should be noted, however, that the analysis to which Stern referred simply noted the complexity of relative risk in establishing disease likelihood in an individual of a population with modest a priori disease risk, such that the populationattributable risk for a threefold increase in relative risk may be quite substantial. Stern emphasized what he considered to be the greater usefulness of continuous rather than dichotomous risk scores. With the latter, sensitivity, specificity, and target population are fixed, while with the former all are flexible if one “tweaks the cut point,” allowing one to optimize test behavior. He suggested that a continuous risk score such as the Framingham equation predicting 10-year likelihood of cardiovascular disease is more useful than a dichotomous measure, such as, in a sense, the concept of prediabetes. Using data from a San Antonio epidemiologic study, his group calculated a diabetes risk score, showing it to be a better predictive approach than either impaired fasting glucose (IFG) (fasting glucose 100–125 mg/dl) or impaired glucose tolerance (IGT) (glucose 2-h postload 75-g oral glucose 140–199 mg/dl). The model includes as factors age, sex, Hispanic vs. non-Hispanic white ethnicity, fasting glucose, systolic blood pressure, HDL cholesterol, BMI, and family history, although Stern noted that ethnicity limits the degree to which the model can be generalized (2). The model has somewhat better ability to predict diabetes than either fasting or postload blood glucose alone. Furthermore, Stern noted, the use of variables such as LDL cholesterol allows considerably greater cardiovascular disease prediction than available with IFG and IGT, similar to the performance of the Framingham model (3). To establish that risk factors are valid for predictive models, a prospective cohort study must be performed with the new risk factor along with conventional risk factors measured at baseline, with outcomes of interest measured at followup, and with independent validation datasets showing the same characteristics. “A considerable effort is required to improve upon the models that we already have,” Stern said. An important barrier to adoption of predictive models is that health professionals tend to consider that they lack naturally occurring cut points, he noted. In fact, however, cut points for established risk factors such as glucose, blood pressure, and lipids also tend to be arbitrary, as are the various criteria used for metabolic syndrome. He concluded that the notion of pre-diabetes as a condition necessitating treatment requires careful examination. It is an asymptomatic state, the significance of which lies in its ability to predict adverse health outcomes for individuals diagnosed. As there is no evidence that early intervention (prior to diagnosis of diabetes) is better than late intervention (after diabetes is present), he suggested that “it is a very profound question” as to whether the concept of prediabetes should be applied to individuals. Rather, he suggested, it needs to be demonstrated, both in terms of cost versus benefit and in terms of outcome, at what point glycemic intervention should begin; strong clinical trial data for glucose interventions, just as we now have for lipid and blood pressure interventions, must be developed. Jacqueline Dekker (Amsterdam, the Netherlands) discussed the Hoorn Study, emphasizing the need for evidence-based prevention of diabetes and vascular complications. She discussed the complex history of criteria for diabetes and prediabetes. The World Health Organization (WHO) and the American Diabetes Association (ADA) definitions of diabetes accept fasting plasma glucose 126 mg/dl ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●

American College of Endocrinology Pre-Diabetes Consensus Conference: Part Two