Assessing the relationship between markers of glycemic control through flexible copula regression models

Abstract

Glycated haemoglobin (HbA1c) is a sensitive marker of blood glucose in patients with diabetes. However, levels can vary considerably, even amongst individuals with similar mean blood glucose concentrations. Other glycated proteins, such as fructosamine, can also act as blood sugar markers, but estimating HbA1c and fructosamine via independent models may lead to errors of interpretation regarding disease severity. From a clinical standpoint, it would be of great interest to know the factors that affect the mean concentration of both HbA1c and fructosamine, which influence the variability in the concentrations of these glycated markers and cause HbA1c/fructosamine discordance. Flexible models are required to illustrate the behaviour of these variables as well as the association between them. This work reviews existing models that might serve in this regard. Flexible copula regression models using splines were used to provide a better understanding of the behaviour of both glycated proteins and the relationship between them under the possible influence of different covariates. This work shows the usefulness of this type of models in practise and provides a basis for their clinical interpretation by means of an understandable case study. Ultimately, to better understand the effects of each continuous covariate, they are represented at the true scale of the response variables.