ABSTRACT
BACKGROUND: In Hong Kong, fasting plasma glucose (FPG) is the most popular screening test for diabetes mellitus (DM) in primary care. Individuals with impaired fasting glucose (IFG) are commonly encountered. OBJECTIVES: To explore the determinants of regression to normoglycaemia among primary care patients with IFG based on non-invasive variables and to establish a nomogram for the prediction of regression from IFG. METHODS: This cohort study consisted of 1197 primary care patients with IFG. These subjects were invited to repeat a FPG test and 75-g 2-hour oral glucose tolerance test (2h-OGTT) to determine the glycaemia change. Normoglycaemia was defined as FPG <5.6 mmol/L and 2h-OGTT <7.8 mmol/L. Stepwise logistic regression model was developed to predict the regression to normoglycaemia with non-invasive variables, using a randomly selected training dataset (810 subjects). The model was validated on the remaining testing dataset (387 subjects). Area under the receiver operating characteristic curve (AUC) and Hosmer-Lemeshow test were used to evaluate discrimination and calibration of the model. A nomogram was constructed based on the model. RESULTS: After a mean follow-up period of 6.1 months, 180 subjects (15.0%) had normoglycaemia based on the repeated FPG and 2h-OGTT results at follow-up. Subjects without central obesity or hypertension, with moderate-to-high-level physical activity and a lower baseline FPG level, were more likely to regress to normoglycaemia. The prediction model had acceptable discrimination (AUC = 0.705) and calibration (P = 0.840). CONCLUSION: The simple-to-use nomogram could facilitate identification of subjects with low risk of progression to DM and thus aid in clinical decision making and resource prioritization in the primary care setting.
