Centre of Excellence for Nutrition, Faculty of Health Sciences, North-West University, Potchefstroom Campus Private Bag X6001, Potchefstroom, 2520, South Africa.
Department of Public Health, Section of Epidemiology, University of Copenhagen, Copenhagen, Denmark.
BMC Endocr Disord. 2024 Oct 10;24(1):213. doi: 10.1186/s12902-024-01735-w.
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).
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.
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.
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.
使用非侵入性风险评分来检测未诊断的 2 型糖尿病（T2D）可确保将侵入性和昂贵的血液检查限制在最有可能被诊断出患有该疾病的人群中。本研究评估并比较了非洲糖尿病风险评分（ADRS）与其他三种糖尿病风险预测模型在基于空腹血浆葡萄糖（FPG）或糖化血红蛋白（HBA1c）检测筛查糖尿病方面的性能。
使用来自 SA-NW-PURE 研究的年龄、性别、腰围、体重指数、血压、糖尿病史和身体活动水平来对 ADRS 和其他已建立的风险预测模型进行外部验证。使用 C 统计量和非参数方法评估并比较了区分度。在重新校准前后，通过校准图评估了校准。
共纳入 937 名参与者；根据 FPG，14%的参与者患有未确诊的 T2D，根据 HbA1c，26%的参与者患有未确诊的 T2D。对于两种诊断措施，各模型的区分度均尚可，且大多相似。FPG 诊断的 C 统计量范围为简化 FINDRISC 模型的 0.69 至 ADRS 模型的 0.77，HbA1c 诊断的 C 统计量范围为简化 FINDRISC 模型的 0.77 至 ADRS 模型的 0.79。校准范围从可接受到良好，但存在高估和低估。所有模型在重新校准后均有显著改善。
各模型的表现相当，ADRS 可通过非侵入性方法识别高达 79%的病例。基于其易用性和性能，ADRS 推荐用于南非某些黑人族群的 T2D 筛查。HbA1c 作为一种诊断手段与 FPG 具有相似的性能。因此，进一步的验证研究可以使用 HbA1c 作为标准进行比较。
