Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, Beijing, China.
Department of Cardiology, Kailuan General Hospital, Tangshan, Hebei, China.
Diabetes Res Clin Pract. 2023 Mar;197:110571. doi: 10.1016/j.diabres.2023.110571. Epub 2023 Feb 7.
To develop and validate sex-specific risk prediction models based on easily obtainable clinical data for predicting 5-year risk of type 2 diabetes (T2D) among individuals with impaired fasting glucose (IFG), and generate practical tools for public use.
The data used for model training and internal validation came from a large prospective cohort (N = 18,384). Two independent cohorts were used for external validation. A two-step approach was applied to screen variables. Coefficient-based models were constructed by multivariate Cox regression analyses, and score-based models were subsequently generated. The predictive power was evaluated by the area under the curve (AUC).
During a median follow-up of 7.55 years, 5697 new-onset T2D cases were identified. Predictor variables included age, body mass index, waist circumference, diastolic blood pressure, triglycerides, fasting plasma glucose, and fatty liver. The proposed models outperformed five existing models. In internal validation, the AUCs of the coefficient-based models were 0.741 (95% CI 0.723-0.760) for men and 0.762 (95% CI 0.720-0.802) for women. External validation yielded comparable prediction performance. We finally constructed a risk scoring system and a web calculator.
The risk prediction models and derived tools had well-validated performance to predict the 5-year risk of T2D in IFG adults.
基于易于获得的临床数据，开发和验证适用于男性和女性的预测空腹血糖受损人群发生 5 年 2 型糖尿病风险的风险预测模型，并生成适用于公众的实用工具。
用于模型训练和内部验证的数据来自一个大型前瞻性队列（N=18384）。两个独立的队列用于外部验证。采用两步法筛选变量。通过多变量 Cox 回归分析构建基于系数的模型，然后生成基于评分的模型。通过曲线下面积（AUC）评估预测能力。
在中位随访 7.55 年期间，共发现 5697 例新发 2 型糖尿病病例。预测变量包括年龄、体重指数、腰围、舒张压、甘油三酯、空腹血糖和脂肪肝。所提出的模型优于五个现有的模型。在内部分验证中，基于系数的模型的 AUC 男性为 0.741（95%CI 0.723-0.760），女性为 0.762（95%CI 0.720-0.802）。外部验证得出了类似的预测性能。我们最终构建了风险评分系统和在线计算器。
该风险预测模型和衍生工具具有良好的验证性能，可预测空腹血糖受损成年人发生 5 年 2 型糖尿病的风险。
