Prediction models for the risk of cardiovascular disease in patients with type 2 diabetes: A systematic review

Heart

Volumn 98, Issue 5, 2012, Pages 360-369

  Van Dieren, Susan ^a   Beulens, J W J ^a   Kengne, A P ^a,b,c   Peelen, L M ^a   Rutten, G E H M ^a   Woodward, M ^c   Van Der Schouw, Y T ^a   Moons, K G M ^a  

^a UNIVERSITY MEDICAL CENTER UTRECHT   (Netherlands)

^b UNIVERSITY OF CAPE TOWN   (South Africa)

^c UNIVERSITY OF SYDNEY   (Australia)

Author keywords

[No Author keywords available]

Indexed keywords

ACCURACY; CARDIOVASCULAR DISEASE; CARDIOVASCULAR RISK; EXTERNAL VALIDITY; FRAMINGHAM RISK SCORE; HEART INFARCTION; HUMAN; ISCHEMIC HEART DISEASE; NON INSULIN DEPENDENT DIABETES MELLITUS; PRACTICE GUIDELINE; PREDICTION; PREDICTIVE VALUE; PRIMARY PREVENTION; PRIORITY JOURNAL; REVIEW; RISK ASSESSMENT; SCORING SYSTEM; SYSTEMATIC REVIEW;

CARDIOVASCULAR DISEASES; DIABETES MELLITUS, TYPE 2; HUMANS; INCIDENCE; MODELS, CARDIOVASCULAR; PRIMARY PREVENTION; PROGNOSIS; RISK ASSESSMENT; RISK FACTORS; WORLD HEALTH;

EID: 84857067097     PISSN: 13556037     EISSN: 1468201X     Source Type: Journal    
DOI: 10.1136/heartjnl-2011-300734     Document Type: Review

References (84)

1. Sarwar N, Gao P, Seshasai SR, et al Emerging Risk Factors Collaboration. Diabetes mellitus, fasting blood glucose concentration, and risk of vascular disease: a collaborative meta-analysis of 102 prospective studies. Lancet 2010;375:2215-22.
2. Woodward M, Zhang X, Barzi F, et al Asia Pacific Cohort Studies Collaboration. The effects of diabetes on the risks of major cardiovascular diseases and death in the Asia-Pacific region. Diabetes Care 2003;26:360-6. (Pubitemid 36929056)
3. Ryden L, Standl E, Bartnik M, et al Task Force on Diabetes and Cardiovascular Diseases of the European Society of Cardiology (ESC); European Association for the Study of Diabetes (EASD). Guidelines on diabetes, pre-diabetes, and cardiovascular diseases: executive summary. The Task Force on Diabetes and Cardiovascular Diseases of the European Society of Cardiology (ESC) and of the European Association for the Study of Diabetes (EASD). Eur Heart J 2007;28:88-136. (Pubitemid 46137814)
4. National Collaborating Centre for Chronic Conditions. Type 2 Diabetes National Clinical Guideline for Management in Primary and Secondary Care (update). http://www.nice.org.uk/nicemedia/live/11983/40803/40803.pdf (accessed Jul 2011).
5. British Cardiac Society, British Hypertension Society, Diabetes UK, HEART UK, Primary Care Cardiovascular Society, Stroke Association. JBS 2: Joint British Societies' guidelines on prevention of cardiovascular disease in clinical practice. Heart 2005;91(Suppl 5):v1-52.
6. Chamnan P, Simmons RK, Sharp SJ, et al. Cardiovascular risk assessment scores for people with diabetes: a systematic review. Diabetologia 2009;52:2001-14.
7. Stephens JW, Ambler G, Vallance P, et al. Cardiovascular risk and diabetes. Are the methods of risk prediction satisfactory? Eur J Cardiovasc Prev Rehabil 2004;11:521-8. (Pubitemid 40096856)
8. Song M, Alexander CM, Mavros P, et al. Use of the UKPDS outcomes model to predict all-cause mortality in US adults with type 2 diabetes mellitus: comparison of predicted versus observed mortality. Diabetes Res Clin Pract 2011;91:121-6.
9. Pellegrini E, Maurantonio M, Giannico IM, et al. Risk for cardiovascular events in an Italian population of patients with type 2 diabetes. Nutr Metab Cardiovasc Dis 2011;21:885-92.
10. Atlman DG, Vergouwe Y, Royston P, et al. Prognosis and prognostic research: validating a prognostic model. BMJ 2009;338:b605.
11. Moons KG, Altman DG, Vergouwe Y, et al. Prognosis and prognostic research: application and impact of prognostic models in clinical practice. BMJ 2009;338:b606.
12. Moons KG, Royston P, Vergouwe Y, et al. Prognosis and prognostic research: what, why, and how? BMJ 2009;338:b375.
13. Royston P, Moons KG, Altman DG, et al. Prognosis and prognostic research: developing a prognostic model. BMJ 2009;338:b604.
14. Hlatky MA, Greenland P, Arnett DK, et al American Heart Association Expert Panel on Subclinical Atherosclerotic Diseases and Emerging Risk Factors and the Stroke Council. Criteria for evaluation of novel markers of cardiovascular risk: A scientific statement from the American heart association. Circulation 2009;119:2408-16.
15. Justice AC, Covinsky KE, Berlin JA. Assessing the generalizability of prognostic information. Ann Intern Med 1999;130:515-24. (Pubitemid 29135805)
16. Reilly BM, Evans AT. Translating clinical research into clinical practice: impact of using prediction rules to make decisions. Ann Intern Med 2006;144:201-9. (Pubitemid 46780691)
17. Graham I, Atar D, Borch-Johnsen K, et al European Society of Cardiology (ESC); European Association for Cardiovascular Prevention and Rehabilitation (EACPR); Council on Cardiovascular Nursing; European Association for Study of Diabetes (EASD); International Diabetes Federation Europe (IDF-Europe); European Stroke Initiative (EUSI); Society of Behavioural Medicine (ISBM); European Society of Hypertension (ESH); WONCA Europe (European Society of General Practice/Family Medicine); European Heart Network (EHN); European Atherosclerosis Society (EAS). European guidelines on cardiovascular disease prevention in clinical practice: Full text: Fourth Joint Task Force of the European Society of Cardiology and other Societies on Cardiovascular Disease Prevention in Clinical Practice (constituted by representatives of nine societies and by invited experts). Eur J Cardiovasc Prev Rehabil 2007;14(Suppl 2):S1-113.
18. American Diabetes Association. Standards of medical care in diabetes - 2011. Diabetes Care Jan 2011;34(Suppl 1):S11-61.
19. Canadian Diabetes Association. Clinical Practice Guidelines for the Prevention and Management of Diabetes in Canada. Canadian Journal of Diabetes 2008;32(Suppl 1):S1-201.
20. National Vascular Disease Prevention Alliance. Guidelines for the Assessment of Absolute Cardiovascular Disease Risk. http://www.heartfoundation. org.au/SiteCollectionDocuments/absolute-risk-assessement.pdf (accessed Jul 2011).
21. International Diabetes Federation. IDF Clinical Guidelines Task Force. Global Guideline for Type 2 Diabetes. http://www.idf.org/webdata/docs/ IDF%20GGT2D.pdf (accessed Jul 2011).
22. Kothari V, Stevens RJ, Adler AI, et al. UKPDS 60: risk of stroke in type 2 diabetes estimated by the UK Prospective Diabetes Study risk engine. Stroke 2002;33:1776-81. (Pubitemid 34761059)
23. Stevens RJ, Kothari V, Adler AI, et al United Kingdom Prospective Diabetes Study (UKPDS) Group. The UKPDS risk engine: a model for the risk of coronary heart disease in Type II diabetes (UKPDS 56). Clin Sci (Lond) 2001;101:671-9. (Pubitemid 33135349)
24. Kengne AP, Patel A, Marre M, et al; (on behalf of the ADVANCE Collaborative Group). Contemporary model for cardiovascular risk prediction in people with type 2 diabetes. Eur J Cardiovasc Prev Rehabil 2011;18:393-8.
25. Davis WA, Knuiman MW, Davis TM. An Australian cardiovascular risk equation for type 2 diabetes: the Fremantle Diabetes Study. Intern Med J 2010;40:286-92.
26. Elley CR, Robinson E, Kenealy T, et al. Derivation and validation of a new cardiovascular risk score for people with type 2 diabetes: the new zealand diabetes cohort study. Diabetes Care 2010;33:1347-52.
27. Cederholm J, Eeg-Olofsson K, Eliasson B, et al Swedish National Diabetes Register. Source Department of Public Health and Carin. Risk prediction of cardiovascular disease in type 2 diabetes: a risk equation from the Swedish National Diabetes Register. Diabetes Care 2008;31:2038-43.
28. Yang X, So WY, Kong AP, et al. Development and validation of a total coronary heart disease risk score in type 2 diabetes mellitus. Am J Cardiol 2008;101:596-601. (Pubitemid 351635559)
29. Yang X, Ma RC, So WY, et al. Development and validation of a risk score for hospitalization for heart failure in patients with Type 2 diabetes mellitus. Cardiovasc Diabetol 2008;7:9.
30. Yang X, So WY, Kong AP, et al. Development and validation of stroke risk equation for Hong Kong Chinese patients with type 2 diabetes: the Hong Kong Diabetes Registry. Diabetes Care 2007;30:65-70. (Pubitemid 46052501)
31. Donnan PT, Donnelly L, New JP, et al. Derivation and validation of a prediction score for major coronary heart disease events in a UK type 2 diabetic population. Diabetes Care 2006;29:1231-6. (Pubitemid 44125915)
32. Folsom AR, Chambless LE, Duncan BB, et al Atherosclerosis Risk in Communities Study Investigators. Prediction of coronary heart disease in middle-aged adults with diabetes. Diabetes Care 2003;26:2777-84. (Pubitemid 37205546)
33. Yudkin JS, Chaturvedi N. Developing risk stratification charts for diabetic and nondiabetic subjects. Diabet Med 1999;16:219-27.
34. Chien KL, Su TC, Hsu HC, et al. Constructing the prediction model for the risk of stroke in a Chinese population: report from a cohort study in Taiwan. Stroke 2010;41:1858-64.
35. Hippisley-Cox J, Coupland C, Robson J, et al. Derivation, validation, and evaluation of a new QRISK model to estimate lifetime risk of cardiovascular disease: cohort study using QResearch database. BMJ 2010;341:c6624.
36. McGorrian C, Yusuf S, Islam S, et al INTERHEART Investigators. Estimating modifiable coronary heart disease risk in multiple regions of the world: the INTERHEART Modifiable Risk Score. Eur Heart J 2011;32:581-9.
37. Arima H, Yonemoto K, Doi Y, et al. Development and validation of a cardiovascular risk prediction model for Japanese: the Hisayama study. Hypertens Res 2009;32:1119-22.
38. Ishikawa S, Matsumoto M, Kayaba K, et al Jichi Medical School (JMS) Cohort Study Group. Risk charts illustrating the 10-year risk of stroke among residents of Japanese rural communities: the JMS Cohort Study. J Epidemiol 2009;19:101-6.
39. Matsumoto M, Ishikawa S, Kayaba K, et al Jichi Medical School (JMS) Cohort Study Group. Risk charts illustrating the 10-year risk of myocardial infarction among residents of Japanese rural communities: the JMS Cohort Study. J Epidemiol 2009;19:94-100.
40. Pencina MJ, D'Agostino RB Sr, Larson MG, et al. Predicting the 30-year risk of cardiovascular disease: the framingham heart study. Circulation 2009;119:3078-84.
41. D'Agostino RB Sr, Vasan RS, Pencina MJ, et al. General cardiovascular risk profile for use in primary care: The Framingham heart study. Circulation 2008;117:743-53. (Pubitemid 351640675)
42. Hippisley-Cox J, Coupland C, Vinogradova Y, et al. Predicting cardiovascular risk in England and Wales: prospective derivation and validation of QRISK2. BMJ 2008;336:1475-82. (Pubitemid 351977019)
43. Assmann G, Schulte H, Cullen P, et al. Assessing risk of myocardial infarction and stroke: new data from the Prospective Cardiovascular Munster (PROCAM) study. Eur J Clin Invest 2007;37:925-32. (Pubitemid 350151189)
44. Ridker PM, Buring JE, Rifai N, et al. Development and validation of improved algorithms for the assessment of global cardiovascular risk in women: the Reynolds Risk Score. JAMA 2007;297:611-19.
45. Woodward M, Brindle P, Tunstall-Pedoe H; SIGN group on risk estimation. Adding social deprivation and family history to cardiovascular risk assessment: the ASSIGN score from the Scottish Heart Health Extended Cohort (SHHEC). Heart 2007;93:172-6. (Pubitemid 46180289)
46. Asia Pacific Cohort Studies Collaboration. Coronary risk prediction for those with and without diabetes. Eur J Cardiovasc Prev Rehabil 2006;13:30-6.
47. Lee ET, Howard BV, Wang W, et al. Prediction of coronary heart disease in a population with high prevalence of diabetes and albuminuria: the Strong Heart Study. Circulation 2006;113:2897-905. (Pubitemid 44297230)
48. Mainous AG 3rd, Koopman RJ, Diaz VA, et al. A coronary heart disease risk score based on patient-reported information. Am J Cardiol 2007;99:1236-41. (Pubitemid 46659859)
49. Wu Y, Liu X, Li X, et al USA-PRC Collaborative Study of Cardiovascular and Cardiopulmonary Epidemiology Research Group; China Multicenter Collaborative Study of Cardiovascular Epidemiology Research Group. Estimation of 10-year risk of fatal and nonfatal ischemic cardiovascular diseases in Chinese adults. Circulation 2006;114:2217-25. (Pubitemid 44789496)
50. Ferrario M, Chiodini P, Chambless LE, et al CUORE Project Research Group. Prediction of coronary events in a low incidence population. Assessing accuracy of the CUORE Cohort Study prediction equation. Int J Epidemiol 2005;34:413-21. (Pubitemid 40645332)
51. Menotti A, Lanti M, gabiti-Rosei E, et al. Riskard 2005. New tools for prediction of cardiovascular disease risk derived from Italian population studies. Nutr Metab Cardiovasc Dis 2005;15:426-40. (Pubitemid 43986478)
52. Balkau B, Hu G, Qiao Q, et al. Prediction of the risk of cardiovascular mortality using a score that includes glucose as a risk factor. The DECODE Study. Diabetologia 2004;47:2118-28. (Pubitemid 40174684)
53. Liu J, Hong Y, D'Agostino RB Sr, et al. Predictive value for the Chinese population of the Framingham CHD risk assessment tool compared with the Chinese Multi-Provincial Cohort Study. JAMA 2004;291:2591-9. (Pubitemid 38702777)
54. Pignone M, Sheridan SL, Lee YZ, et al. Heart to Heart: a computerized decision aid for assessment of coronary heart disease risk and the impact of risk-reduction interventions for primary prevention. Prev Cardiol 2004;7:26-33.
55. Schau B, Boysen G, Truelsen T, et al. Development and validation of a model to estimate stroke incidence in a population. J Stroke Cerebrovasc Dis 2003;12:22-8. (Pubitemid 36292854)
56. 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 Munster (PROCAM) study. Circulation 2002;105:310-15. (Pubitemid 34106178)
57. Lumley T, Kronmal RA, Cushman M, et al. A stroke prediction score in the elderly: validation and Web-based application. J Clin Epidemiol 2002;55:129-36. (Pubitemid 34065279)
58. Menotti A, Lanti M, Puddu PE, et al. The risk functions incorporated in Riscard 2002: a software for the prediction of cardiovascular risk in the general population based on Italian data. Ital Heart J 2002;3:114-21. (Pubitemid 34591554)
59. Moons KG, Bots ML, Salonen JT, et al. Prediction of stroke in the general population in Europe (EUROSTROKE): Is there a role for fibrinogen and electrocardiography? J Epidemiol Community Health 2002;56(Suppl 1):i30-6. (Pubitemid 34098454)
60. Thomsen TF, Davidsen M, Ibsen H, et al. A new method for CHD prediction and prevention based on regional risk scores and randomized clinical trials; PRECARD and the Copenhagen Risk Score. J Cardiovasc Risk 2001;8:291-7. (Pubitemid 33010689)
61. Knuiman MW, Vu HT, Bartholomew HC. Multivariate risk estimation for coronary heart disease: the Busselton Health Study. Aust N Z J Public Health 1998;22:747-53. (Pubitemid 29142088)
62. Wilson PW, D'Agostino RB, Levy D, et al. Prediction of coronary heart disease using risk factor categories. Circulation 1998;97:1837-47. (Pubitemid 28213628)
63. Wood D, De Backer G, Faergeman O, et al. Prevention of coronary heart disease in clinical practice. Recommendations of the Second Joint Task Force of European and other Societies on Coronary Prevention. Eur Heart J 1998;19:1434-503. (Pubitemid 28470470)
64. Zodpey SP, Kulkarni HR, Vasudeo ND, et al. A risk scoring system for prediction of coronary heart disease based on multivariate analysis: development and validation. Indian Heart J 1994;46:77-83.
65. Anderson KM, Odell PM, Wilson PW, et al. Cardiovascular disease risk profiles. Am Heart J 1991;121:293-8.
66. Anderson KM, Wilson PW, Odell PM, et al. An updated coronary risk profile. A statement for health professionals. Circulation 1991;83:356-62.
67. Kengne AP, Patel A, Colagiuri S, 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;53:821-31.
68. Davis WA, Colagiuri S, Davis TM. Comparison of the Framingham and United Kingdom Prospective Diabetes Study cardiovascular risk equations in Australian patients with type 2 diabetes from the Fremantle Diabetes Study. Med J Aust 2009;190:180-4.
69. van Dieren S, Peelen LM, Nothlings U, et al. External validation of the UK Prospective Diabetes Study (UKPDS) risk engine in patients with type 2 diabetes. Diabetologia 2011;54:264-70.
70. Song SH, Brown PM. Coronary heart disease risk assessment in diabetes mellitus: comparison of UKPDS risk engine with Framingham risk assessment function and its clinical implications. Diabet Med 2004;21:238-45. (Pubitemid 38299617)
71. Guzder RN, Gatling W, Mullee MA, et al. 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. Diabet Med 2005;22:554-62. (Pubitemid 40593130)
72. van der Heijden AA, Ortegon MM, Niessen LW, et al. Prediction of coronary heart disease risk in a general, pre-diabetic, and diabetic population during 10 years of follow-up: accuracy of the Framingham, SCORE, and UKPDS risk functions: The Hoorn Study. Diabetes Care 2009;32:2094-8.
73. Simmons RK, Coleman RL, Price HC, et al. Performance of the UK Prospective Diabetes Study Risk Engine and the Framingham Risk Equations in Estimating Cardiovascular Disease in the EPIC- Norfolk Cohort. Diabetes Care 2009;32:708-13.
74. Coleman RL, Stevens RJ, Retnakaran R, et al. Framingham, SCORE, and DECODE risk equations do not provide reliable cardiovascular risk estimates in type 2 diabetes. Diabetes Care 2007;30:1292-3.
75. Game FL, Jones AF. Coronary heart disease risk assessment in diabetes mellitus - a comparison of PROCAM and Framingham risk assessment functions. Diabet Med 2001;18:355-9. (Pubitemid 32679382)
76. Game FL, Bartlett WA, Bayly GR, et al. Comparative accuracy of cardiovascular risk prediction methods in patients with diabetes mellitus. Diabetes Obes Metab 2001;3:279-86. (Pubitemid 32785338)
77. McEwan P, Williams JE, Griffiths JD, et al. Evaluating the performance of the Framingham risk equations in a population with diabetes. Diabet Med 2004;21:318-23. (Pubitemid 38519665)
78. Hall LM, Jung RT, Leese GP. Controlled trial of effect of documented cardiovascular risk scores on prescribing. Br Med J 2003;326:251-2. (Pubitemid 36169586)
79. Hetlevik I, Holrnen J, Krüger Ø. Implementing clinical guidelines in the treatment of hypertension in general practice: Evaluation of patient outcome related to implementation of a computer-based clinical decision support system. Scand J Prim Health Care 1999;17:35-40. (Pubitemid 29200197)
80. Montgomery AA, Fahey T, Peters TJ, et al. Evaluation of computer based clinical decision support system and risk chart for management of hypertension in primary care: randomised controlled trial. BMJ 2000;320:686-90. (Pubitemid 30179394)
81. Moons KG. Criteria for scientific evaluation of novel markers: a perspective. Clin Chem 2010;56:537-41.
82. Conroy RM, Pyörälä K, Fitzgerald AP, et al; SCORE project group. Estimation of tenyear risk of fatal cardiovascular disease in Europe: The SCORE project. Eur Heart J 2003;24:987-1003. (Pubitemid 36712275)
83. Chen L, Tonkin AM, Moon L, et al. Recalibration and validation of the SCORE risk chart in the Australian population: the AusSCORE chart. Eur J Cardiovasc Prev Rehabil 2009;16:562-70.
84. Steyerberg EW, Borsboom GJ, van Houwelingen HC, et al. Validation and updating of predictive logistic regression models: a study on sample size and shrinkage. Stat Med 2004;23:2567-86. (Pubitemid 39149268)