Validation of type 2 diabetes subgroups by simple clinical parameters: a retrospective cohort study of NHANES data from 1999 to 2014

Abstract

ObjectivesTo verify whether a simplified method based on age, body mass index (BMI) and glycated haemoglobin (HbA1c) is feasible in classifying patients with type 2 diabetes (T2D), and evaluate the predictive ability of subgroups in several health and mortality outcomes.DesignRetrospective cohort study.SettingThe National Health and Nutrition Examination Survey 1999–2014 cycle.ParticipantsA total of 1960 participants with diabetes and the age at diagnosis greater than 30.Primary and secondary outcome measuresParticipants with T2D were assigned to previously defined (by Ahlqvist) subgroups based on five variables: age, BMI, HbA1c, homoeostasis model assessment (HOMA) 2 estimates of β-cell function (HOMA2-B), and insulin resistance (HOMA2-IR), and on three variables: age, BMI and HbA1c. The classification performances of the three variables were evaluated based on 10-fold cross validation, with accuracy, precision and recall as evaluation criteria. Outcomes were assessed using logistic regression and Cox regression analysis.ResultsWithout HOMA measurements, it is difficult to identify severe insulin-resistant diabetes, but other subgroups can be ideally identified. There is no significant difference between the five variables and the three variables in the ability to predict the prevalence of poor cardiovascular health (CVH), chronic kidney disease, non-alcoholic fatty liver disease and advanced liver fibrosis, and the risk of all-cause, cardiovascular disease and cancer-related mortality (p>0.05), except the prevalence of poor CVH in mild age-related diabetes (p<0.05).ConclusionsA simple classification based on age, BMI and HbA1c could be used to identify T2D with several health and mortality risks, which is accessible in most individuals with T2D. Due to its simplicity and practicality, more patients with T2D can benefit from subgroup specific treatment paradigms.