Performance of the UK Prospective Diabetes Study Risk Engine and the Framingham Risk Equations in Estimating Cardiovascular Disease in the EPIC- Norfolk Cohort

REBECCA K. SIMMONS PHD RUTH L. COLEMAN MSC HERMIONE C. PRICE MRCP RURY R. HOLMAN KAY-TEE KHAW PHD NICHOLAS J. WAREHAM SIMON J. GRIFFIN DM C a r d i o v a s c u l a r a n d OBJECTIVE - 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 6.0%; and 3) individuals with normoglycemia defined as A1C 6.0%. RESEARCH DESIGN AND METHODS - 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. RESULTS - 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. CONCLUSIONS - 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. - I two to four times increased risk of and microvascular events in diabetic indindividuals with type 2 diabetes have a for reducing the risk of cardiovascular cardiovascular disease (CVD) com- viduals (2,3). Multivariate equations such pared with those without diabetes (1). as the Framingham equations are used Multifactorial interventions aimed to to estimate CVD risk to target therapy to reduce hyperglycemia, hypertension, those with the highest absolute risk and to and hypercholesterolemia are effective provide patients and practitioners with prognostic information. However, although some studies have concluded that the Framingham risk equations for estimating CVD risk provide acceptable results when applied to populations outside North America (4), others have suggested that they are not applicable in those with a particularly low or high risk (5), including individuals with diabetes (6). The UK Prospective Diabetes Study (UKPDS) Risk Engine is a type 2 diabetes-specific risk calculator that includes A1C as well as traditional CVD risk factors. Version 2 of the Risk Engine estimates coronary heart disease risk and stroke risk separately. In version 3, equations have been derived that estimate CVD risk directly (7). This novel risk equation has been validated in the Collaborative Atorvastatin Diabetes Study (CARDS) cohort (8), which was a primary prevention trial, and showed good predictive ability. The CARDS trial cohort is not necessarily as widely generalizable as a true population-based sample. Thus, in this article we examined the performance of the UKPDS Risk Engine (version 3) and the Framingham risk equations (2008) in estimating CVD incidence in three population subgroups: 1) individuals with known diabetes; 2) individuals with nondiabetic hyperglycemia (A1C 6.0%); and 3) individuals with A1C 6.0% (normoglycemia). RESEARCH DESIGN AND METHODS European Prospective Investigation of Cancer (EPIC)-Norfolk is a prospective cohort study in which men and women aged 40 79 years were recruited from general practices in the Norfolk region of the U.K. Full details of the population are reported elsewhere (9). In brief, between 1993 and 1998, 25,639 individuals attended a baseline health examination. This included anthropometric and blood pressure measurements and completion of a general health questionnaire, with questions on personal and family history of disease, medication, and lifestyle factors. Participants were asked to indicate whether they were a current smoker, ex-smoker, or never smoker. They were also asked whether a doctor had ever told them that they had any of the conditions contained in a list that included diabetes, heart attack, and stroke. In addition, baseline diabetes status was also ascertained by 1) a self-report of diabetes medication; 2) diabetes medication brought to the baseline health check; 3) indication of a modification in diet in the past year because of diabetes; or 4) indication of following a diet for diabetes. Nonfasting blood samples were obtained, and starting in 1995 when funding became available, A1C was measured on fresh EDTA blood samples using highperformance liquid chromatography (Diamat automated glycated hemoglobin analyzer; Bio-Rad, Hemel Hempstead, U.K.). The population in the Norfolk area is healthier than the general U.K. population with a standardized mortality ratio of 94 (source: Office for National Statistics). However, the EPIC-Norfolk cohort is similar to a nationally representative sample for anthropometric variables, blood pressure, and serum lipids (9). We report results for follow-up to April 2007. Participants were followed for a median of 10.1 years. All EPIC-Norfolk participants were flagged for death certification at the Office of National Statistics, and vital status was obtained for the entire cohort. Trained nosologists coded death certificates according to the ICD-9 or ICD-10. Cardiovascular death (stroke, coronary heart disease, peripheral vascular disease, and other vascular causes) was defined in those whose underlying cause of death was coded as ICD-9 400 448 or ICD-10 I10 I79. Participants admitted to a hospital were identified by their National Health Service number. Hospitals were linked to the East Norfolk Health Authority database, which identifies all hospital contacts throughout England and Wales for Norfolk residents. Participants were identified as having a CVD event during follow-up if they had a hospital admission and/or died with CVD as the underlying cause. Previous validation studies in our cohort indicated high specificity of such case ascertainment (10). Estimation of cardiovascular risk The 10-year absolute risk of CVD was estimated for each participant using the UKPDS Risk Engine version 3.0 (7). This is a type 2 diabetes-specific risk assessment tool that def (...truncated)