Advertisement

Cardiovascular Risk-Assessment Models and Ethnicity: Implications for Hypertension Guidelines

  • Dong Zhao
  • Gianfranco Parati
  • Pietro Amedeo ModestiEmail author
Chapter
Part of the Updates in Hypertension and Cardiovascular Protection book series (UHCP)

Abstract

The individual-based strategy, focused on decreasing the probability of future cardiovascular disease (CVD) events in high-risk individuals through appropriate management of modifiable risk factors, requires measurement of predicted likelihood of future CVD. Different risk-assessment models have been developed. However, systematic overestimation or underestimation of CVD risk has been observed when a model designed for one population is directly applied to another population, which is the case of ethnic minorities. Implications of risk-assessment models and recommendations of risk assessment for ethnic minorities in clinical guidelines have rarely been considered. Furthermore, the number and the type of measurements which have been suggested for risk assessment may necessitate additional time and resources. Efforts are needed to develop flexible, adaptable, socioculturally acceptable, and economically attainable guidelines for better health-related outcomes in patients with hypertension.

Keywords

Risk-assessment models Cardiovascular risk Guidelines Ethnic minorities 

References

  1. 1.
    Goff DC Jr, Lloyd-Jones DM, Bennett G, et al. 2013 ACC/AHA guideline on the assessment of cardiovascular risk: a report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines. Circulation. 2014;129(25 Suppl 2):S49–73.PubMedCrossRefGoogle Scholar
  2. 2.
    Conroy RM, Pyorala K, Fitzgerald AP, et al. Estimation of ten-year risk of fatal cardiovascular disease in Europe: the SCORE project. Eur Heart J. 2003;24(11):987–1003.PubMedCrossRefGoogle Scholar
  3. 3.
    GBD 2016 Causes of Death Collaborators. Global, regional, and national age-sex specific mortality for 264 causes of death, 1980-2016: a systematic analysis for the Global Burden of Disease Study 2016. Lancet. 2017;390(10100):1151–210.CrossRefGoogle Scholar
  4. 4.
    Kim AS, Johnston SC. Global variation in the relative burden of stroke and ischemic heart disease. Circulation. 2011;124(3):314–23.PubMedCrossRefGoogle Scholar
  5. 5.
    D’Agostino RB Sr, Grundy S, Sullivan LM, et al. Validation of the Framingham coronary heart disease prediction scores: results of a multiple ethnic groups investigation. JAMA. 2001;286(2):180–7.PubMedCrossRefGoogle Scholar
  6. 6.
    Hawthorne V, Kozarevic D, Vojvodic N, et al. Prediction of mortality from coronary heart disease among diverse populations: is there a common predictive function? Heart. 2002;88(3):222–8.CrossRefGoogle Scholar
  7. 7.
    Lawes CM, Bennett DA, Parag V, et al. Blood pressure indices and cardiovascular disease in the Asia Pacific region: a pooled analysis. Hypertension. 2003;42(1):69–75.PubMedCrossRefGoogle Scholar
  8. 8.
    Lawes CM, Rodgers A, Bennett DA, et al. Blood pressure and cardiovascular disease in the Asia Pacific region. J Hypertens. 2003;21(4):707–16.PubMedCrossRefGoogle Scholar
  9. 9.
    Perkovic V, Huxley R, Wu Y, et al. The burden of blood pressure-related disease: a neglected priority for global health. Hypertension. 2007;50(6):991–7.PubMedCrossRefGoogle Scholar
  10. 10.
    Eastwood SV, Tillin T, Chaturvedi N, Hughes AD. Ethnic differences in associations between blood pressure and stroke in South Asian and European men. Hypertension. 2015;66(3):481–8.PubMedPubMedCentralCrossRefGoogle Scholar
  11. 11.
    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(21):2591–9.PubMedCrossRefGoogle Scholar
  12. 12.
    Marrugat J, D’Agostino R, Sullivan L, et al. An adaptation of the Framingham coronary heart disease risk function to European Mediterranean areas. J Epidemiol Community Health. 2003;57(8):634–8.PubMedPubMedCentralCrossRefGoogle Scholar
  13. 13.
    Sawano M, Kohsaka S, Okamura T, et al. Validation of the european SCORE risk chart in the healthy middle-aged Japanese. Atherosclerosis. 2016;252:116–21.PubMedCrossRefGoogle Scholar
  14. 14.
    Cappuccio FP, Oakeshott P, Strazzullo P, et al. Application of Framingham risk estimates to ethnic minorities in United Kingdom and implications for primary prevention of heart disease in general practice: cross sectional population based study. BMJ. 2002;325(7375):1271.PubMedPubMedCentralCrossRefGoogle Scholar
  15. 15.
    Quirke TP, Gill PS, Mant JW, et al. The applicability of the Framingham coronary heart disease prediction function to black and minority ethnic groups in the UK. Heart. 2003;89(7):785–6.PubMedPubMedCentralCrossRefGoogle Scholar
  16. 16.
    Bhopal R, Fischbacher C, Vartiainen E, et al. Predicted and observed cardiovascular disease in South Asians: application of FINRISK, Framingham and SCORE models to Newcastle Heart Project data. J Public Health (Oxf). 2005;27(1):93–100.CrossRefGoogle Scholar
  17. 17.
    Piepoli MF, Hoes AW, Agewall S, et al. 2016 European guidelines on cardiovascular disease prevention in clinical practice: The Sixth Joint Task Force of the European Society of Cardiology and other societies on cardiovascular disease prevention in clinical practice (constituted by representatives of 10 societies and by invited experts) developed with the special contribution of the European Association for Cardiovascular Prevention & Rehabilitation (EACPR). Eur Heart J. 2016;37(29):2315–81.PubMedPubMedCentralCrossRefGoogle Scholar
  18. 18.
    Oppenheimer GM. Becoming the Framingham study 1947-1950. Am J Public Health. 2005;95(4):602–10.PubMedPubMedCentralCrossRefGoogle Scholar
  19. 19.
    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 Investig. 2007;37(12):925–32.CrossRefGoogle Scholar
  20. 20.
    Panagiotakos DB, Fitzgerald AP, Pitsavos C, et al. Statistical modelling of 10-year fatal cardiovascular disease risk in Greece: the HellenicSCORE (a calibration of the ESC SCORE project). Hell J Cardiol. 2007;48(2):55–63.Google Scholar
  21. 21.
    Aspelund T, Thorgeirsson G, Sigurdsson G, et al. Estimation of 10-year risk of fatal cardiovascular disease and coronary heart disease in Iceland with results comparable with those of the Systematic Coronary Risk Evaluation project. Eur J Cardiovasc Prev Rehabil. 2007;14(6):761–8.PubMedCrossRefGoogle Scholar
  22. 22.
    Merry AH, Boer JM, Schouten LJ, et al. Risk prediction of incident coronary heart disease in The Netherlands: re-estimation and improvement of the SCORE risk function. Eur J Prev Cardiol. 2012;19(4):840–8.PubMedCrossRefGoogle Scholar
  23. 23.
    Marques-Vidal P, Rodondi N, Bochud M, et al. Predictive accuracy and usefulness of calibration of the ESC SCORE in Switzerland. Eur J Cardiovasc Prev Rehabil. 2008;15(4):402–8.PubMedCrossRefGoogle Scholar
  24. 24.
    Onat A, Can G, Hergenc G, et al. Coronary disease risk prediction algorithm warranting incorporation of C-reactive protein in Turkish adults, manifesting sex difference. Nutr Metab Cardiovasc Dis. 2012;22(8):643–50.PubMedCrossRefGoogle Scholar
  25. 25.
    Hippisley-Cox J, Coupland C, Vinogradova Y, et al. Derivation and validation of QRISK, a new cardiovascular disease risk score for the United Kingdom: prospective open cohort study. BMJ. 2007;335(7611):136.PubMedPubMedCentralCrossRefGoogle Scholar
  26. 26.
    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(7659):1475–82.PubMedPubMedCentralCrossRefGoogle Scholar
  27. 27.
    Icaza G, Nunez L, Marrugat J, et al. Estimation of coronary heart disease risk in Chilean subjects based on adapted Framingham equations. Rev Med Chil. 2009;137(10):1273–82.PubMedGoogle Scholar
  28. 28.
    Wu Y, Liu X, Li X, et al. Estimation of 10-year risk of fatal and nonfatal ischemic cardiovascular diseases in Chinese adults. Circulation. 2006;114(21):2217–25.PubMedCrossRefGoogle Scholar
  29. 29.
    Chow CK, Joshi R, Celermajer DS, et al. Recalibration of a Framingham risk equation for a rural population in India. J Epidemiol Community Health. 2009;63(5):379–85.PubMedCrossRefGoogle Scholar
  30. 30.
    Bozorgmanesh M, Hadaegh F, Azizi F. Predictive accuracy of the ‘Framingham’s general CVD algorithm’ in a Middle Eastern population: Tehran lipid and glucose study. Int J Clin Pract. 2011;65(3):264–73.PubMedCrossRefGoogle Scholar
  31. 31.
    Goldbourt U, Yaari S, Medalie JH. Factors predictive of long-term coronary heart-disease mortality among 10,059 male israeli civil-servants and municipal employees—a 23-year mortality follow-up in the Israeli ischemic-heart-disease study. Cardiology. 1993;82(2–3):100–21.PubMedCrossRefGoogle Scholar
  32. 32.
    Group NDR. Risk assessment chart for death from cardiovascular disease based on a 19-year follow-up study of a Japanese representative population. Circ J. 2006;70(10):1249–55.CrossRefGoogle Scholar
  33. 33.
    Jee SH, Jang Y, Oh DJ, et al. A coronary heart disease prediction model: the Korean Heart Study. BMJ Open. 2014;4(5):e005025.PubMedPubMedCentralCrossRefGoogle Scholar
  34. 34.
    Lee J, Heng D, Chia KS, et al. Risk factors and incident coronary heart disease in Chinese, Malay and Asian Indian males: the Singapore Cardiovascular Cohort Study. Int J Epidemiol. 2001;30(5):983–8.PubMedCrossRefGoogle Scholar
  35. 35.
    Sritara P, Cheepudomwit S, Chapman N, et al. Twelve-year changes in vascular risk factors and their associations with mortality in a cohort of 3499 Thais: the Electricity Generating Authority of Thailand Study. Int J Epidemiol. 2003;32(3):461–8.PubMedCrossRefGoogle Scholar
  36. 36.
    Kengne AP, Awah PK. Classical cardiovascular risk factors and all-cause mortality in rural Cameroon. QJM. 2009;102(3):209–15.PubMedCrossRefGoogle Scholar
  37. 37.
    Zhao D, Liu J, Xie W, et al. Cardiovascular risk assessment: a global perspective. Nat Rev Cardiol. 2015;12(5):301–11.PubMedCrossRefGoogle Scholar
  38. 38.
    D’Agostino RB, Vasan RS, Pencina MJ, et al. General cardiovascular risk profile for use in primary care: the Framingham heart study. Circulation. 2008;118(4):E86–E.Google Scholar
  39. 39.
    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(5):562–70.PubMedCrossRefGoogle Scholar
  40. 40.
    Pyorala K, De Backer G, Graham I, et al. Prevention of coronary heart disease in clinical practice. Recommendations of the Task Force of the European Society of Cardiology, European Atherosclerosis Society and European Society of Hypertension. Eur Heart J. 1994;15(10):1300–31.PubMedCrossRefGoogle Scholar
  41. 41.
    The Association of Physicians of India. Indian hypertension guidelines II [online]. 2011. http://www.apiindia.org/hsi_guideline_ii.html.
  42. 42.
    National Heart Foundation of Australia. Guide to management of hypertension 2008: assessing and managing raised blood pressure in adults, updated December 2010 [online]. 2010. http://www.heartfoundation.org.au/SiteCollectionDocuments/HypertensionGuidelines2008to2010Update.pdf.
  43. 43.
    Ogihara T, Kikuchi K, Matsuoka H, et al. The Japanese society of hypertension guidelines for the management of hypertension (JSH 2009). Hypertens Res. 2009;32(1):3–107.PubMedGoogle Scholar
  44. 44.
    Sanchez RA, Ayala M, Baglivo H, et al. Latin American guidelines on hypertension. Latin American Expert Group. J Hypertens. 2009;27(5):905–22.PubMedCrossRefGoogle Scholar
  45. 45.
    Liu LS, Writing Group of Chinese Guidelines for the Management of Hypertension. 2010 Chinese guidelines for the management of hypertension. Zhonghua Xin Xue Guan Bing Za Zhi. 2011;39(7):579–615.PubMedGoogle Scholar
  46. 46.
    Seedat YK, Rayner BL, Southern African Hypertension Society. South African hypertension guideline 2011. S Afr Med J. 2011;102(1 Pt 2):57–83.PubMedGoogle Scholar
  47. 47.
    Mancia G, Fagard R, Narkiewicz K, et al. 2013 ESH/ESC guidelines for the management of arterial hypertension: the Task Force for the management of arterial hypertension of the European Society of Hypertension (ESH) and of the European Society of Cardiology (ESC). J Hypertens. 2013;31(7):1281–357.PubMedCrossRefGoogle Scholar
  48. 48.
    James PA, Oparil S, Carter BL, et al. 2014 evidence-based guideline for the management of high blood pressure in adults: report from the panel members appointed to the Eighth Joint National Committee (JNC 8). JAMA. 2014;311(5):507–20.PubMedCrossRefGoogle Scholar
  49. 49.
    Owolabi M, Olowoyo P, Miranda JJ, et al. Gaps in hypertension guidelines in low- and middle-income versus high-income countries: a systematic review. Hypertension. 2016;68(6):1328–37.PubMedPubMedCentralCrossRefGoogle Scholar
  50. 50.
    Joint Committee for Developing Chinese guidelines on Prevention, Treatment of Dyslipidemia in Aults. Chinese guidelines on prevention and treatment of dyslipidemia in adults. Zhonghua Xin Xue Guan Bing Za Zhi. 2007;35(5):390–419.Google Scholar
  51. 51.
    Modesti PA, Agostoni P, Agyemang C, et al. Cardiovascular risk assessment in low-resource settings: a consensus document of the European Society of Hypertension Working Group on Hypertension and Cardiovascular Risk in Low Resource Settings. J Hypertens. 2014;32(5):951–60.PubMedPubMedCentralCrossRefGoogle Scholar
  52. 52.
    Mendis S, Lindholm LH, Anderson SG, et al. Total cardiovascular risk approach to improve efficiency of cardiovascular prevention in resource constrain settings. J Clin Epidemiol. 2011;64(12):1451–62.PubMedCrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Dong Zhao
    • 1
  • Gianfranco Parati
    • 2
    • 3
  • Pietro Amedeo Modesti
    • 4
    Email author
  1. 1.Department of EpidemiologyCapital Medical University, Beijing Anzhen Hospital and National Institute of Heart, Lung and Blood DiseaseBeijingChina
  2. 2.Istituto Auxologico Italiano, IRCCS, Department of Cardiovascular, Neural and Metabolic SciencesSan Luca HospitalMilanItaly
  3. 3.Department of Medicine and SurgeryUniversity of Milano-BicoccaMilanItaly
  4. 4.Department of Clinical and Experimental MedicineUniversity of FlorenceFirenzeItaly

Personalised recommendations