国家神经系统疾病临床医学研究中心数据管理与共享系统
Data Management And Sharing System of China National Clinical Research Center for Neurological Diseases
Risk scores for predicting incidence of type 2 diabetes in the Chinese population: the Kailuan prospective study
基本信息
- 负责人：Anxin Wang,Guojuan Chen
- 数据来源： Kailuan Study
- 论文编号：KAILUAN STUDY20190078
- 发表时间：2016-05-25
2016-05-25
已发表文章
主要研究背景及目的
According to the second Global Status Report on Noncommunicable Diseases 2014 released by the World Health Organization, the prevalence of diabetes in adults aged 18 years and over in China is estimated to be 9.5%. The actual number of patients with diabetes in China is therefore a shocking figure because of the country’s large population. The financial costs of diabetes-related health expenditures also weigh heavily on the nation’s economy. Thus, reducing diabetes-related morbidity in China is an important issue. Type 2 diabetes can be prevented and delayed in high-risk individuals by modifying their lifestyle. However, the inconvenience and relatively high cost of the 2-hour oral glucose tolerance test (OGTT), which is generally used to identify high-risk subjects, limits its use. On the other hand, the application of risk assessment tools based on demographic, anthropometric, and simple laboratory tests to screen high-risk subjects is both feasible and economical. A number of risk assessment tools based on readily available clinical variables have been developed to predict the incidence of new diabetes cases. These are derived from European, American, Australian, and Asian studies. However, differences in ethnicities, territories, and lifestyles may limit the application of some of these effective risk scores to the Chinese population. Developing a risk score to specifically identify subjects at high risk of type 2 diabetes that may be widely used in China is therefore both urgent and necessary. Few risk scores have been developed specifically to identify individuals at high risk of type 2 diabetes in China; most have been generated from cross-sectional data, and are limited by small sample size. In the present study, we aimed to develop and validate simple risk scores based on self-assessed information and simple laboratory measurements in the Kailuan study characterizing individuals at increased risk of developing type 2 diabetes during a follow-up period of nearly 5.35 years. Furthermore, we compared the performance of other algorithms using our cohort.
方法
In the present study, we aimed to develop such risk scores, based on simple clinical variables. We studied a population-based cohort of 73,987 adults, aged 18 years and over.
结论
In summary, the concise score, based on non-laboratory variables, could be used to identify individuals at high risk of developing diabetes within Chinese population; the accurate score, which also uses FPG and TG data, is better at identifying such individuals.
主要结果
After 5.35 ± 1.59 years of follow-up, 4,726 participants (9.58%) in the exploration cohort developed type 2 diabetes and 2,327 participants (9.44%) in the validation cohort developed type 2 diabetes. Age, gender, body mass index, family history of diabetes, education, blood pressure, and resting heart rate were selected to form the concise score with an area under the receiver operating characteristic curve (AUC) of 0.67. The variables in the concise score combined with fasting plasma glucose (FPG), and triglyceride (TG) or use of lipid-lowering drugs constituted the accurate score with an AUC value of 0.77. The utility of the two scores was confirmed in the validation cohort with AUCs of 0.66 and 0.77, respectively.