Cardiovascular Events in People With Type 2 Diabetes: Performance of Framingham, UKPDS, and ADVANCE Risk Equations
Abstract
The aim of this study was to assess the performance of the Framingham, UK Prospective Diabetes Study (UKPDS), and the Action in Diabetes and Vascular disease: Preterax and Diamicron-MR Controlled Evaluation (ADVANCE) risk equations in the prediction of 4-year cardiovascular disease CVD) in Iranian people with type 2 diabetes. The 4-year risks of CVD were estimated using the three equations in a community of 557 patients with type 2 diabetes and free of CVD at baseline. A trained physician evaluated all of the participants regarding the occurrence of CVD events during follow-up. CVD was defined as major events including fatal/non-fatal myocardial infarction as well as fatal/non-fatal stroke, minor events including treated coronary heart disease (CHD), and established peripheral arterial disease (PAD). During four years of follow-up, 64 CVD events were observed (66% minor CVD events). Despite having a good calibration (estimated to observed ratio ranging from 91.37 to 98.2 percent, Hosmer–Lemeshow χ2 (HLχ2) values <15), both general (Framingham) and diabetes-specific (UKPDS and ADVANCE) equations did not have adequate discriminative ability (Area Under the Curve (AUC) ranging from 0.48 to 0.56). Framingham, UKPDS, and ADVANCE risk equations, regardless of being general or diabetes-specific, could not precisely predict 4-year risk of CVD in Iranian individuals with type 2 diabetes.
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8. Kengne AP, Patel A, Colagiuri S, Heller S, Hamet P, Marre M, et al. 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. Diabetologia. 2010;53(5):821-31.
9. Chamnan P, Simmons RK, Sharp SJ, Griffin SJ, Wareham NJ. Cardiovascular risk assessment scores for people with diabetes: a systematic review. Diabetologia. 2009;52(10):2001.
10. Beswick A, Brindle P. Risk scoring in the assessment of cardiovascular risk. Current Opinion in Lipidology. 2006;17(4):375-86.
11. Truett J, Cornfield J, Kannel W. A multivariate analysis of the risk of coronary heart disease in Framingham. Journal of Chronic Diseases. 1967;20(7):511-24.
12. Kengne AP. The ADVANCE cardiovascular risk model and current strategies for cardiovascular disease risk evaluation in people with diabetes : review. South African Journal of Diabetes and Vascular Disease. 2013;11(3):121-5.
13. Anderson KM, Odell PM, Wilson PWF, Kannel WB. Cardiovascular disease risk profiles. American Heart Journal. 1991;121(1, Part 2):293-8.
14. D'Agostino RB, Wolf PA, Belanger AJ, Kannel WB. Stroke risk profile: adjustment for antihypertensive medication. The Framingham Study. Stroke. 1994;25(1):40-3.
15. Wilson PWF, D’Agostino RB, Levy D, Belanger AM, Silbershatz H, Kannel WB. Prediction of Coronary Heart Disease Using Risk Factor Categories. Circulation. 1998;97(18):1837-47.
16. D’Agostino RB, Vasan RS, Pencina MJ, Wolf PA, Cobain M, Massaro JM, et al. General Cardiovascular Risk Profile for Use in Primary Care. The Framingham Heart Study. 2008;117(6):743-53.
17. Assmann G, Cullen P, Schulte H. Simple Scoring Scheme for Calculating the Risk of Acute Coronary Events Based on the 10-Year Follow-Up of the Prospective Cardiovascular Mأ¼nster (PROCAM) Study. Circulation. 2002;105(3):310-5.
18. Conroy RM, on behalf of the Spg, Pyأ¶rأ¤lأ¤ K, on behalf of the Spg, Fitzgerald AP, on behalf of the Spg, et al. Estimation of ten-year risk of fatal cardiovascular disease in Europe: the SCORE project. European Heart Journal. 2003;24(11):987-1003.
19. Balkau B, Hu G, Qiao Q, Tuomilehto J, Borch-Johnsen K, Pyorala K, et al. Prediction of the risk of cardiovascular mortality using a score that includes glucose as a risk factor. The DECODE Study. Diabetologia. 2004;47(12):2118.
20. Stevens RJ, Kothari V, Adler AI, Stratton IM, Holman RR. The UKPDS risk engine: a model for the risk of coronary heart disease in Type II diabetes (UKPDS 56). Clinical science. 2001;101(6):671-9.
21. Kothari V, Stevens RJ, Adler AI, Stratton IM, Manley SE, Neil HA, et al. UKPDS 60. Risk of Stroke in Type 2 Diabetes Estimated by the UK Prospective Diabetes Study Risk Engine. 2002;33(7):1776-81.
22. Stevens RJ, Coleman RL, Adler AI, Stratton IM, Matthews DR, Holman RR. Risk factors for myocardial infarction case fatality and stroke case fatality in type 2 diabetes: UKPDS 66. Diabetes Care. 2004;27(1):201-7.
23. Donnan PT, Donnelly L, New JP, Morris AD. Derivation and validation of a prediction score for major coronary heart disease events in a UK type 2 diabetic population. Diabetes Care. 2006;29(6):1231-6.
24. Protopsaltis ID, Konstantinopoulos PA, Kamaratos AV, Melidonis AI. Comparative study of prognostic value for coronary disease risk between the UK prospective diabetes study and Framingham models. Diabetes Care. 2004;27(1):277-8.
25. Guzder RN, Gatling W, Mullee MA, Mehta RL, Byrne CD. Prognostic value of the Framingham cardiovascular risk equation and the UKPDS risk engine for coronary heart disease in newly diagnosed type 2 diabetes: results from a United Kingdom study. Diabetic Medicine. 2005;22(5):554-62.
26. Echouffo-Tcheugui JB, Kengne AP. Comparative performance of diabetes-specific and general population-based cardiovascular risk assessment models in people with diabetes mellitus. Diabetes & metabolism. 2013;39(5):389-96.
27. Bozorgmanesh M, Hadaegh F, Azizi F. Predictive accuracy of the â€کFramingham’s general CVD algorithm’in a Middle Eastern population: Tehran Lipid and Glucose Study. International journal of clinical practice. 2011;65(3):264-73.
28. D'Agostino RB, Grundy S, Sullivan LM, Wilson P. Validation of the Framingham coronary heart disease prediction scores: results of a multiple ethnic groups investigation. Jama. 2001;286(2):180-7.
29. Altman DG, Vergouwe Y, Royston P, Moons KG. Prognosis and prognostic research: validating a prognostic model. Bmj. 2009;338:b605.
30. Weng SF, Reps J, Kai J, Garibaldi JM, Qureshi N. Can machine-learning improve cardiovascular risk prediction using routine clinical data? PloS one. 2017;12(4):e0174944.
31. Muntner P, Colantonio LD, Cushman M, Goff DC, Howard G, Howard VJ, et al. Validation of the atherosclerotic cardiovascular disease Pooled Cohort risk equations. Jama. 2014;311(14):1406-15.
32. Yozgatli K, Lefrandt J, Noordzij M, Oomen P, Brouwer T, Jager J, et al. Accumulation of advanced glycation end products is associated with macrovascular events and glycaemic control with microvascular complications in Type 2 diabetes mellitus. Diabetic Medicine. 2018.
33. Vasan RS, Larson MG, Leip EP, Evans JC, O'donnell CJ, Kannel WB, et al. Impact of high-normal blood pressure on the risk of cardiovascular disease. New England journal of medicine. 2001;345(18):1291-7.
34. Jackson R, Lawes CMM, Bennett DA, Milne RJ, Rodgers A. Treatment with drugs to lower blood pressure and blood cholesterol based on an individual's absolute cardiovascular risk. The Lancet. 2005;365(9457):434-41.
35. Wei Y-C, George NI, Chang C-W, Hicks KA. Assessing sex differences in the risk of cardiovascular disease and mortality per increment in systolic blood pressure: a systematic review and meta-analysis of follow-up studies in the United States. PLoS One. 2017;12(1):e0170218.
36. Mozaffarian D, Benjamin EJ, Go AS, Arnett DK, Blaha MJ, Cushman M, et al. Executive summary: heart disease and stroke statistics—2015 update: a report from the American Heart Association. Circulation. 2015;131(4):434-41.
2. Association AD. 9. Cardiovascular disease and risk management: standards of medical care in diabetes—2018. Diabetes care. 2018;41(Supplement 1):S86-S104.
3. Liu L, Simon B, Shi J, Mallhi AK, Eisen HJ. Impact of diabetes mellitus on risk of cardiovascular disease and all-cause mortality: evidence on health outcomes and antidiabetic treatment in United States adults. World journal of diabetes. 2016;7(18):449.
4. Chen L, Magliano DJ, Zimmet PZ. The worldwide epidemiology of type 2 diabetes mellitus—present and future perspectives. Nature Reviews Endocrinology. 2012;8:228.
5. Esteghamati A, Larijani B, Aghajani MH, Ghaemi F, Kermanchi J, Shahrami A, et al. Diabetes in Iran: prospective analysis from first nationwide diabetes report of National Program for Prevention and Control of Diabetes (NPPCD-2016). Scientific reports. 2017;7(1):13461.
6. Noshad S, Afarideh M, Heidari B, Mechanick JI, Esteghamati A. Diabetes care in Iran: Where we stand and where we are headed. Annals of global health. 2015;81(6):839-50.
7. Javanbakht M, Mashayekhi A, Baradaran HR, Haghdoost A, Afshin A. Projection of diabetes population size and associated economic burden through 2030 in Iran: evidence from micro-simulation Markov model and Bayesian meta-analysis. PloS one. 2015;10(7):e0132505.
8. Kengne AP, Patel A, Colagiuri S, Heller S, Hamet P, Marre M, et al. 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. Diabetologia. 2010;53(5):821-31.
9. Chamnan P, Simmons RK, Sharp SJ, Griffin SJ, Wareham NJ. Cardiovascular risk assessment scores for people with diabetes: a systematic review. Diabetologia. 2009;52(10):2001.
10. Beswick A, Brindle P. Risk scoring in the assessment of cardiovascular risk. Current Opinion in Lipidology. 2006;17(4):375-86.
11. Truett J, Cornfield J, Kannel W. A multivariate analysis of the risk of coronary heart disease in Framingham. Journal of Chronic Diseases. 1967;20(7):511-24.
12. Kengne AP. The ADVANCE cardiovascular risk model and current strategies for cardiovascular disease risk evaluation in people with diabetes : review. South African Journal of Diabetes and Vascular Disease. 2013;11(3):121-5.
13. Anderson KM, Odell PM, Wilson PWF, Kannel WB. Cardiovascular disease risk profiles. American Heart Journal. 1991;121(1, Part 2):293-8.
14. D'Agostino RB, Wolf PA, Belanger AJ, Kannel WB. Stroke risk profile: adjustment for antihypertensive medication. The Framingham Study. Stroke. 1994;25(1):40-3.
15. Wilson PWF, D’Agostino RB, Levy D, Belanger AM, Silbershatz H, Kannel WB. Prediction of Coronary Heart Disease Using Risk Factor Categories. Circulation. 1998;97(18):1837-47.
16. D’Agostino RB, Vasan RS, Pencina MJ, Wolf PA, Cobain M, Massaro JM, et al. General Cardiovascular Risk Profile for Use in Primary Care. The Framingham Heart Study. 2008;117(6):743-53.
17. Assmann G, Cullen P, Schulte H. Simple Scoring Scheme for Calculating the Risk of Acute Coronary Events Based on the 10-Year Follow-Up of the Prospective Cardiovascular Mأ¼nster (PROCAM) Study. Circulation. 2002;105(3):310-5.
18. Conroy RM, on behalf of the Spg, Pyأ¶rأ¤lأ¤ K, on behalf of the Spg, Fitzgerald AP, on behalf of the Spg, et al. Estimation of ten-year risk of fatal cardiovascular disease in Europe: the SCORE project. European Heart Journal. 2003;24(11):987-1003.
19. Balkau B, Hu G, Qiao Q, Tuomilehto J, Borch-Johnsen K, Pyorala K, et al. Prediction of the risk of cardiovascular mortality using a score that includes glucose as a risk factor. The DECODE Study. Diabetologia. 2004;47(12):2118.
20. Stevens RJ, Kothari V, Adler AI, Stratton IM, Holman RR. The UKPDS risk engine: a model for the risk of coronary heart disease in Type II diabetes (UKPDS 56). Clinical science. 2001;101(6):671-9.
21. Kothari V, Stevens RJ, Adler AI, Stratton IM, Manley SE, Neil HA, et al. UKPDS 60. Risk of Stroke in Type 2 Diabetes Estimated by the UK Prospective Diabetes Study Risk Engine. 2002;33(7):1776-81.
22. Stevens RJ, Coleman RL, Adler AI, Stratton IM, Matthews DR, Holman RR. Risk factors for myocardial infarction case fatality and stroke case fatality in type 2 diabetes: UKPDS 66. Diabetes Care. 2004;27(1):201-7.
23. Donnan PT, Donnelly L, New JP, Morris AD. Derivation and validation of a prediction score for major coronary heart disease events in a UK type 2 diabetic population. Diabetes Care. 2006;29(6):1231-6.
24. Protopsaltis ID, Konstantinopoulos PA, Kamaratos AV, Melidonis AI. Comparative study of prognostic value for coronary disease risk between the UK prospective diabetes study and Framingham models. Diabetes Care. 2004;27(1):277-8.
25. Guzder RN, Gatling W, Mullee MA, Mehta RL, Byrne CD. Prognostic value of the Framingham cardiovascular risk equation and the UKPDS risk engine for coronary heart disease in newly diagnosed type 2 diabetes: results from a United Kingdom study. Diabetic Medicine. 2005;22(5):554-62.
26. Echouffo-Tcheugui JB, Kengne AP. Comparative performance of diabetes-specific and general population-based cardiovascular risk assessment models in people with diabetes mellitus. Diabetes & metabolism. 2013;39(5):389-96.
27. Bozorgmanesh M, Hadaegh F, Azizi F. Predictive accuracy of the â€کFramingham’s general CVD algorithm’in a Middle Eastern population: Tehran Lipid and Glucose Study. International journal of clinical practice. 2011;65(3):264-73.
28. D'Agostino RB, Grundy S, Sullivan LM, Wilson P. Validation of the Framingham coronary heart disease prediction scores: results of a multiple ethnic groups investigation. Jama. 2001;286(2):180-7.
29. Altman DG, Vergouwe Y, Royston P, Moons KG. Prognosis and prognostic research: validating a prognostic model. Bmj. 2009;338:b605.
30. Weng SF, Reps J, Kai J, Garibaldi JM, Qureshi N. Can machine-learning improve cardiovascular risk prediction using routine clinical data? PloS one. 2017;12(4):e0174944.
31. Muntner P, Colantonio LD, Cushman M, Goff DC, Howard G, Howard VJ, et al. Validation of the atherosclerotic cardiovascular disease Pooled Cohort risk equations. Jama. 2014;311(14):1406-15.
32. Yozgatli K, Lefrandt J, Noordzij M, Oomen P, Brouwer T, Jager J, et al. Accumulation of advanced glycation end products is associated with macrovascular events and glycaemic control with microvascular complications in Type 2 diabetes mellitus. Diabetic Medicine. 2018.
33. Vasan RS, Larson MG, Leip EP, Evans JC, O'donnell CJ, Kannel WB, et al. Impact of high-normal blood pressure on the risk of cardiovascular disease. New England journal of medicine. 2001;345(18):1291-7.
34. Jackson R, Lawes CMM, Bennett DA, Milne RJ, Rodgers A. Treatment with drugs to lower blood pressure and blood cholesterol based on an individual's absolute cardiovascular risk. The Lancet. 2005;365(9457):434-41.
35. Wei Y-C, George NI, Chang C-W, Hicks KA. Assessing sex differences in the risk of cardiovascular disease and mortality per increment in systolic blood pressure: a systematic review and meta-analysis of follow-up studies in the United States. PLoS One. 2017;12(1):e0170218.
36. Mozaffarian D, Benjamin EJ, Go AS, Arnett DK, Blaha MJ, Cushman M, et al. Executive summary: heart disease and stroke statistics—2015 update: a report from the American Heart Association. Circulation. 2015;131(4):434-41.
| Files | ||
| Issue | Vol 59, No 10 (2021) | |
| Section | Articles | |
| DOI | https://doi.org/10.18502/acta.v59i10.7768 | |
| Keywords | ||
| Cardiovascular disease (CVD) Risk Event Framingham | ||
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How to Cite
1.
Yaghoubvand E, Aghili R, Khajavi A, Khamseh ME. Cardiovascular Events in People With Type 2 Diabetes: Performance of Framingham, UKPDS, and ADVANCE Risk Equations. Acta Med Iran. 2021;59(10):610-616.
