Evaluating the performance of the Framingham risk equations in a population with diabetes

McEwan, P.; Williams, Janet E.; Griffiths, J. D.; Bagust, A; Peters, John R.; Hopkinson, P.; Currie, Craig John

doi:10.1111/j.1464-5491.2004.01139.x

Cited by 81 publications

(60 citation statements)

References 27 publications

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“…These approaches have been used, for example, to adapt the Framingham cardiovascular risk equations to different populations [33]. In the only available study of such an approach, which was conducted in people with diabetes, no improvement was found in the discrimination property of the Framingham Anderson model, after refitting the equation to the data from Cardiff [34], but calibration performance was not reported. In the ADVANCE cohort, recalibrated models showed greatly improved calibration, suggesting that recalibration could be used to improve the performance of the Framingham and UKPDS models in people with diabetes.…”

Section: Discussionmentioning

confidence: 99%

“…As shown in this analysis, the magnitude and direction of departures of the predicted event rates/number by risk tools from those observed can vary substantially across populations [35]. Several recalibration methods with variable levels of complexity have been suggested for updating survival models for new settings, with no indication that the more complex methods provide the best results [24,34,36].…”

Section: Discussionmentioning

confidence: 99%

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The Framingham and UK Prospective Diabetes Study (UKPDS) risk equations do not reliably estimate the probability of cardiovascular events in a large ethnically diverse sample of patients with diabetes: the Action in Diabetes and Vascular Disease: Preterax and Diamicron-MR Controlled Evaluation (ADVANCE) Study

et al. 2010

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Aims/hypothesis Available multivariable equations for cardiovascular risk assessment in people with diabetes have been derived either from the general population or from populations with diabetes. Their utility and comparative performance in a contemporary group of patients with type 2 diabetes are not well established. Diabetologia (2010) 53:821-831 DOI 10.1007/s00125-010-1681 Framingham and the UKPDS risk equations in 7,502 individuals with type 2 diabetes without prior known CVD at their enrolment in the trial. Results The risk of major CVD was overestimated by 170% (95% CI 146-195%) and 202% (176-231%) using the two Framingham equations. The risk of major coronary heart disease was overestimated by 198% (162-238%) with the UKPDS, and by 146% (117-179%) and 289% (243-341%) with the two different Framingham equations, respectively. The risks of stroke events were also overestimated with the UKPDS and one of the Framingham equations. The ability of these equations to rank risk among ADVANCE participants was modest, with c-statistics ranging from 0.57 to 0.71. Results stratified by sex, treatment allocation and ethnicity were broadly similar. Conclusions/interpretation Application of the Framingham and UKPDS risk equations to a contemporary treated group of patients with established type 2 diabetes is likely to substantially overestimate cardiovascular risk.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

The Framingham and UK Prospective Diabetes Study (UKPDS) risk equations do not reliably estimate the probability of cardiovascular events in a large ethnically diverse sample of patients with diabetes: the Action in Diabetes and Vascular Disease: Preterax and Diamicron-MR Controlled Evaluation (ADVANCE) Study

et al. 2010

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“…Some of these and other risk factors are included in the Framingham algorithm (95), which has been shown to be in general a more powerful tool for predicting future CVD events. However, even the Framingham risk equation does not include important CVD risk factors (e.g., previous CVD events, family history), and has been shown to be much less useful than other risk equations in predicting future CVD events in people with diabetes (102)(103)(104). Other newly identified CVD risk factors have been shown to be strongly associated with insulin resistance and CVD, but it is unclear if they should be added to the syndrome and given equal or greater weight than the current components.…”

Section: Diabetes Care 28:2289 -2304 2005mentioning

confidence: 99%

The Metabolic Syndrome: Time for a Critical Appraisal

et al. 2005

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The term "metabolic syndrome" refers to a clustering of specific cardiovascular disease (CVD) risk factors whose underlying pathophysiology is thought to be related to insulin resistance. Since the term is widely used in research and clinical practice, we undertook an extensive review of the literature in relation to the syndrome's definition, underlying pathogenesis, and association with CVD and to the goals and impact of treatment. While there is no question that certain CVD risk factors are prone to cluster, we found that the metabolic syndrome has been imprecisely defined, there is a lack of certainty regarding its pathogenesis, and there is considerable doubt regarding its value as a CVD risk marker. Our analysis indicates that too much critically important information is missing to warrant its designation as a "syndrome." Until much needed research is completed, clinicians should evaluate and treat all CVD risk factors without regard to whether a patient meets the criteria for diagnosis of the "metabolic syndrome." Diabetes Care 28:2289 -2304, 2005F or most of the 20th century, cardiovascular disease (CVD) was identified as the major cause of morbidity and mortality in the developed world. During this period there was considerable effort to understand the underlying biology of the disease and to identify the contributing risk factors. As risk factors were identified, it became apparent that more than one were often present in the same individual. Toward the end of the century, the clustering of CVD risk factors was first described, most notably the simultaneous presence of obesity, type 2 diabetes, hyperlipidemia, and hypertension (1-3). Although insulin resistance (i.e., resistance to insulin-stimulated glucose uptake) as a feature of type 2 diabetes was first described many years earlier (4), hyperinsulinemia was also found to be a key feature of type 2 diabetes (5,6), as well as hyperlipidemia (7-9), obesity (10 -13), and hypertension (12)(13)(14). In addition, a cluster of heart disease risk factors seemed clearly related to type 2 diabetes (15).This risk factor clustering, and its association with insulin resistance, led investigators to propose the existence of a unique pathophysiological condition, called the "metabolic" (1-3) or "insulin resistance" (11) syndrome. This concept was unified and extended with the landmark publication of Reaven's 1988 Banting Medal award lecture (16). Reaven postulated that insulin resistance and its compensatory hyperinsulinemia predisposed patients to hypertension, hyperlipidemia, and diabetes and thus was the underlying cause of much CVD. Although obesity was not included in Reaven's primary list of disorders caused by insulin resistance, he acknowledged that it, too, was correlated with insulin resistance or hyperinsulinemia, and that the obvious "treatment" for what he termed "syndrome X" was weight maintenance (or weight loss) and physical activity.Reaven's seminal paper was followed by many studies documenting the clustering of CVD risk factors and their relatio...

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“…Pulse pressure is a nontraditional marker of increased CVD risk that strongly predicts cardiovascular events in type 2 diabetes (2-4). Because stiffening of central arteries is associated with increased pulse pressure, understanding aortic changes in the natural history of diabetes is of interest and of particular importance because CVD risk in diabetes is not completely predicted by traditional cardiovascular risk factors and occurs at an early age (5). Improved understanding of the role played by central arterial stiffening in the pathophysiology of diabetes may shed light on the excess CVD mortality faced by these individuals.…”

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confidence: 99%

Increases in Central Aortic Impedance Precede Alterations in Arterial Stiffness Measures in Type 1 Diabetes

et al. 2007

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OBJECTIVE -Increased pulse pressure has been associated with increased cardiovascular risk in individuals with diabetes. Changes in central aortic properties can increase central pulse pressure and may adversely affect microvascular perfusion and cardiac performance. This study was performed to define early changes in central arterial properties in a group of young individuals with type 1 diabetes. RESEARCH AND DESIGN METHODS -Seventeen individuals with type 1 diabetesand their nondiabetic control subjects who were participating in the Cardio-Diab Study had arterial stiffness and pulsatile hemodynamics measured with calibrated tonometry and pulsed Doppler. Aortic characteristic impedance (Z c ) was calculated from the ratio of change in carotid pressure and aortic flow in early systole. Pulse wave velocity (PWV) was assessed from tonometry and body surface measurements.RESULTS -Duration of type 1 diabetes was 15.3 Ϯ 0.7 (mean Ϯ SD) years. In type 1 diabetic subjects, central pulse pressure was elevated (45 Ϯ 11 vs. 36 Ϯ 10 mmHg in control subjects, P ϭ 0.02), as was peripheral pulse pressure (54 Ϯ 13 vs. 43 Ϯ 10 mmHg, P ϭ 0.002). Z c was elevated in type 1 diabetes (179 Ϯ 57 vs. 136 Ϯ 42 dynes ϫ s/cm 5 in control subjects, P ϭ 0.004), whereas PWV was not different (5.9 Ϯ 0.9 vs. 5.9 Ϯ 0.7 m/s in type 1 diabetic vs. control subjects, respectively; NS). There was a moderate correlation between Z c and urinary albumin excretion (coefficient 0.39, P ϭ 0.02). CONCLUSIONS-Z c appears to be increased early in type 1 diabetes, before elevation of PWV and is associated with higher pulse pressure, which may contribute to renal microvascular damage in diabetes.

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Evaluating the performance of the Framingham risk equations in a population with diabetes

Cited by 81 publications

References 27 publications

The Metabolic Syndrome: Time for a Critical Appraisal

Increases in Central Aortic Impedance Precede Alterations in Arterial Stiffness Measures in Type 1 Diabetes

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