Simmons Rebecca K, Coleman Ruth L, Price Hermione C, Holman Rury R, Khaw Kay-Tee, Wareham Nicholas J, Griffin Simon J
1MRC Epidemiology Unit, Cambridge, UK.
Diabetes Care. 2009 Apr;32(4):708-13. doi: 10.2337/dc08-1918. Epub 2008 Dec 29.
The purpose of this study was to examine the performance of the UK Prospective Diabetes Study (UKPDS) Risk Engine (version 3) and the Framingham risk equations (2008) in estimating cardiovascular disease (CVD) incidence in three populations: 1) individuals with known diabetes; 2) individuals with nondiabetic hyperglycemia, defined as A1C >or=6.0%; and 3) individuals with normoglycemia defined as A1C <6.0%.
This was a population-based prospective cohort (European Prospective Investigation of Cancer-Norfolk). Participants aged 40-79 years recruited from U.K. general practices attended a health examination (1993-1998) and were followed for CVD events/death until April 2007. CVD risk estimates were calculated for 10,137 individuals.
Over 10.1 years, there were 69 CVD events in the diabetes group (25.4%), 160 in the hyperglycemia group (17.7%), and 732 in the normoglycemia group (8.2%). Estimated CVD 10-year risk in the diabetes group was 33 and 37% using the UKPDS and Framingham equations, respectively. In the hyperglycemia group, estimated CVD risks were 31 and 22%, respectively, and for the normoglycemia group risks were 20 and 14%, respectively. There were no significant differences in the ability of the risk equations to discriminate between individuals at different risk of CVD events in each subgroup; both equations overestimated CVD risk. The Framingham equations performed better in the hyperglycemia and normoglycemia groups as they did not overestimate risk as much as the UKPDS Risk Engine, and they classified more participants correctly.
Both the UKPDS Risk Engine and Framingham risk equations were moderately effective at ranking individuals and are therefore suitable for resource prioritization. However, both overestimated true risk, which is important when one is using scores to communicate prognostic information to individuals.
本研究旨在检验英国前瞻性糖尿病研究（UKPDS）风险引擎（第3版）和弗雷明汉风险方程（2008年）在估计三类人群心血管疾病（CVD）发病率方面的表现：1）已知糖尿病患者；2）非糖尿病性高血糖个体，定义为糖化血红蛋白（A1C）≥6.0%；3）血糖正常个体，定义为A1C＜6.0%。
这是一项基于人群的前瞻性队列研究（欧洲癌症前瞻性调查 - 诺福克）。从英国全科医疗诊所招募的40 - 79岁参与者参加了健康检查（1993 - 1998年），并随访至2007年4月以观察CVD事件/死亡情况。对10137名个体计算了CVD风险估计值。
在10.1年期间，糖尿病组有69例CVD事件（25.4%），高血糖组有160例（17.7%），血糖正常组有732例（8.2%）。使用UKPDS和弗雷明汉方程，糖尿病组估计的10年CVD风险分别为33%和37%。在高血糖组中，估计的CVD风险分别为31%和22%，血糖正常组的风险分别为20%和14%。在每个亚组中，风险方程区分不同CVD事件风险个体的能力没有显著差异；两个方程均高估了CVD风险。弗雷明汉方程在高血糖组和血糖正常组中表现更好，因为它们不像UKPDS风险引擎那样高估风险，并且正确分类的参与者更多。
UKPDS风险引擎和弗雷明汉风险方程在对个体进行排序方面都有一定效果，因此适用于资源优先分配。然而，两者都高估了真实风险，这在使用评分向个体传达预后信息时很重要。
