Abstract
BACKGROUND: The use of non-invasive risk scores to detect undiagnosed type 2 diabetes (T2D) ensures the restriction of invasive and costly blood tests to those most likely to be diagnosed with the disease. This study assessed and compared the performance of the African Diabetes Risk Score (ADRS) with three other diabetes risk prediction models for identifying screen-detected diabetes based on fasting plasma glucose (FPG) or glycated haemoglobin (HBA1c). METHODS: Age, sex, waist circumference, body mass index, blood pressure, history of diabetes and physical activity levels from the SA-NW-PURE study were used to externally validate the ADRS and other established risk prediction models. Discrimination was assessed and compared using C-statistics and nonparametric methods. Calibration was assessed using calibration plots, before and after recalibration. RESULTS: Nine hundred and thirty-seven participants were included; 14% had prevalent undiagnosed T2D according to FPG and 26% according to HbA1c. Discrimination was acceptable and was mostly similar between models for both diagnostic measures. The C-statistics for diagnosis by FPG ranged from 0.69 for the Simplified FINDRISC model to 0.77 for the ADRS model and 0.77 for the Simplified FINDRISC model to 0.79 for the ADRS model for diagnosis by HbA1c. Calibration ranged from acceptable to good, though over- and underestimation were present. All models improved significantly following recalibration. CONCLUSIONS: The models performed comparably, with the ADRS offering a non-invasive way to identify up to 79% of cases. Based on its ease of use and performance, the ADRS is recommended for screening for T2D in certain Black population groups in South Africa. HbA1c as a means of diagnosis also showed comparable performance with FPG. Therefore, further validation studies can potentially use HbA1c as the standard to compare to.