Literature DB >> 20157695

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.

A P Kengne1, A Patel, S Colagiuri, S Heller, P Hamet, M Marre, C Y Pan, S Zoungas, D E Grobbee, B Neal, J Chalmers, M Woodward.   

Abstract

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. The aim of this study was to evaluate the performance of the Framingham and UK Prospective Diabetes Study (UKPDS) risk equations in participants who took part in the Action in Diabetes and Vascular disease: Preterax and Diamicron-MR Controlled Evaluation (ADVANCE) trial.
METHODS: The 4-year risks of cardiovascular disease (CVD) and its constituents were estimated using two published 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.

Entities:  

Mesh:

Substances:

Year:  2010        PMID: 20157695     DOI: 10.1007/s00125-010-1681-4

Source DB:  PubMed          Journal:  Diabetologia        ISSN: 0012-186X            Impact factor:   10.122


  34 in total

1.  Third Report of the National Cholesterol Education Program (NCEP) Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel III) final report.

Authors: 
Journal:  Circulation       Date:  2002-12-17       Impact factor: 29.690

2.  Probability of stroke: a risk profile from the Framingham Study.

Authors:  P A Wolf; R B D'Agostino; A J Belanger; W B Kannel
Journal:  Stroke       Date:  1991-03       Impact factor: 7.914

3.  Validation of the Framingham coronary heart disease prediction scores: results of a multiple ethnic groups investigation.

Authors:  R B D'Agostino; S Grundy; L M Sullivan; P Wilson
Journal:  JAMA       Date:  2001-07-11       Impact factor: 56.272

Review 4.  Accuracy and impact of risk assessment in the primary prevention of cardiovascular disease: a systematic review.

Authors:  P Brindle; A Beswick; T Fahey; S Ebrahim
Journal:  Heart       Date:  2006-04-18       Impact factor: 5.994

5.  An updated coronary risk profile. A statement for health professionals.

Authors:  K M Anderson; P W Wilson; P M Odell; W B Kannel
Journal:  Circulation       Date:  1991-01       Impact factor: 29.690

6.  Validation of the Gail et al. model of breast cancer risk prediction and implications for chemoprevention.

Authors:  B Rockhill; D Spiegelman; C Byrne; D J Hunter; G A Colditz
Journal:  J Natl Cancer Inst       Date:  2001-03-07       Impact factor: 13.506

7.  Coronary risk prediction for those with and without diabetes.

Authors: 
Journal:  Eur J Cardiovasc Prev Rehabil       Date:  2006-02

8.  Cardiovascular risk prediction tools for populations in Asia.

Authors:  F Barzi; A Patel; D Gu; P Sritara; T H Lam; A Rodgers; M Woodward
Journal:  J Epidemiol Community Health       Date:  2007-02       Impact factor: 3.710

9.  General cardiovascular risk profile for use in primary care: the Framingham Heart Study.

Authors:  Ralph B D'Agostino; Ramachandran S Vasan; Michael J Pencina; Philip A Wolf; Mark Cobain; Joseph M Massaro; William B Kannel
Journal:  Circulation       Date:  2008-01-22       Impact factor: 29.690

10.  Mortality from coronary heart disease in subjects with type 2 diabetes and in nondiabetic subjects with and without prior myocardial infarction.

Authors:  S M Haffner; S Lehto; T Rönnemaa; K Pyörälä; M Laakso
Journal:  N Engl J Med       Date:  1998-07-23       Impact factor: 91.245

View more
  42 in total

1.  Association of HbA1c levels with vascular complications and death in patients with type 2 diabetes: evidence of glycaemic thresholds.

Authors:  S Zoungas; J Chalmers; T Ninomiya; Q Li; M E Cooper; S Colagiuri; G Fulcher; B E de Galan; S Harrap; P Hamet; S Heller; S MacMahon; M Marre; N Poulter; F Travert; A Patel; B Neal; M Woodward
Journal:  Diabetologia       Date:  2011-12-21       Impact factor: 10.122

2.  Development of a new diabetes risk prediction tool for incident coronary heart disease events: the Multi-Ethnic Study of Atherosclerosis and the Heinz Nixdorf Recall Study.

Authors:  Joseph Yeboah; Raimund Erbel; Joseph Chris Delaney; Robin Nance; Mengye Guo; Alain G Bertoni; Matthew Budoff; Susanne Moebus; Karl-Heinz Jöckel; Gregory L Burke; Nathan D Wong; Nils Lehmann; David M Herrington; Stefan Möhlenkamp; Philip Greenland
Journal:  Atherosclerosis       Date:  2014-08-14       Impact factor: 5.162

Review 3.  Biomarkers of cardiovascular disease: contributions to risk prediction in individuals with diabetes.

Authors:  Katherine N Bachmann; Thomas J Wang
Journal:  Diabetologia       Date:  2017-09-28       Impact factor: 10.122

4.  Refitting of the UKPDS 68 risk equations to contemporary routine clinical practice data in the UK.

Authors:  P McEwan; H Bennett; T Ward; K Bergenheim
Journal:  Pharmacoeconomics       Date:  2015-02       Impact factor: 4.981

5.  Choosing targets for glycaemia, blood pressure and low-density lipoprotein cholesterol in elderly individuals with diabetes mellitus.

Authors:  Susan R Kirsh; David C Aron
Journal:  Drugs Aging       Date:  2011-12-01       Impact factor: 3.923

Review 6.  The Evolving Cardiovascular Disease Risk Scores for Persons with Diabetes Mellitus.

Authors:  Yanglu Zhao; Nathan D Wong
Journal:  Curr Cardiol Rep       Date:  2018-10-11       Impact factor: 2.931

7.  Performance of the UKPDS Outcomes Model 2 for Predicting Death and Cardiovascular Events in Patients with Type 2 Diabetes Mellitus from a German Population-Based Cohort.

Authors:  Michael Laxy; Verena Maria Schöning; Christoph Kurz; Rolf Holle; Annette Peters; Christa Meisinger; Wolfgang Rathmann; Kristin Mühlenbruch; Katharina Kähm
Journal:  Pharmacoeconomics       Date:  2019-12       Impact factor: 4.981

Review 8.  Applicability of the Existing CVD Risk Assessment Tools to Type II Diabetics in Oman: A Review.

Authors:  Abdulhakeem Al-Rawahi; Patricia Lee
Journal:  Oman Med J       Date:  2015-09

9.  Macrovascular Risk Equations Based on the CANVAS Program.

Authors:  Michael Willis; Christian Asseburg; April Slee; Andreas Nilsson; Cheryl Neslusan
Journal:  Pharmacoeconomics       Date:  2021-02-13       Impact factor: 4.981

10.  Administration time-dependent effects of combination therapy on ambulatory blood pressure in hypertensive subjects.

Authors:  Weizhong Huangfu; Peilin Duan; Dingcheng Xiang; Ruiying Gao
Journal:  Int J Clin Exp Med       Date:  2015-10-15
View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.