Glycosylated Hemoglobin A1c Improves the Performance of the Nomogram for Predicting the 5-Year Incidence of Type 2 Diabetes.

ABSTRACT:

Aim

To develop and validate a model, which combines traditional risk factors and glycosylated hemoglobin A1c (HbA1c) for predicting the risk of type 2 diabetes (T2DM).

Materials and methods

This is a historical cohort study from a collected database, which included 8419 males and 7034 females without diabetes at baseline with a median follow-up of 5.8-years and 5.1-years, respectively. Multivariate cox regression analysis was used to select significant prognostic factors of T2DM. Two nomograms were constructed to predict the 5-year incidence of T2DM based on traditional risk factors (Model 1) and traditional risk factors plus HbA1c (Model 2). C-index, calibration curve, and time-dependent receiver-operating characteristic (ROC) curve were conducted in the training sets and v

SUBMITTER: Ma CM 

PROVIDER: S-EPMC7247728 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature