Estimation of the 10-Year Risk of Cardiovascular Diseases: Using the SCORE, WHO/ISH, and Framingham Models in the Shahrekord Cohort Study in Southwestern Iran
Abstract
Background: Predicting the risk of cardiovascular diseases (CVDs) helps the management of high-risk individuals by the health system. We sought to determine the 10-year risk of CVDs in the Shahrekord Cohort Study (SCS).
Methods: In this cross-sectional study based on the SCS in the southwest of Iran, the demographic, anthropometric, clinical, and laboratory data of 5152 persons recruited in the SCS by census method from 2016 to 2017 were used. R software was utilized to calculate the 10-year risk of CVDs according to the World Health Organization/International Society of Hypertension (WHO/ISH) chart, the Framingham Risk Score (FRS) model, and the Systematic Coronary Risk Evaluation (SCORE) model.
Results: The mean age of the participants was 49.49±9.40 years, and 50.3% of them were female. According to the WHO/ISH chart, 94.1% of the participants were in the low-risk class, 4.1% in the moderate-risk class, and 0.4% in the high-risk class. Based on the FRS model, 72.2% of the participants were in the low-risk class, 18% in the middle-risk class, and 9.8% in the high-risk class. On the basis of the SCORE model for low-risk areas, 55.3% of the participants were in the low-risk class, 39.6% in the moderate-risk class, and 5.1% in the high-risk class. The agreement concerning risk estimation between the models was approximately 70%.
Conclusion: The risk estimated in this study was higher than that in other similar studies. For monitoring risk trends over time, it is essential to nativize a valid risk function, including ethnicity and geographical characteristics, for the Iranian population.
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21. Fatema K, Zwar NA, Milton AH, Rahman B, Ali L. Application of two versions of the WHO/international society of hypertension absolute cardiovascular risk assessment tools in a rural Bangladeshi population. BMJ Open 2015;10:e008140.
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24. Ofori S, Dodiyi-Manuel S, Akpa MR. Comparison of 3 risk estimators to guide initiation of statin therapy for primary prevention of cardiovascular disease. J Clin Lipidol 2017;6:1441-1447.
25. Otgontuya D, Oum S, Buckley BS, Bonita R. Assessment of total cardiovascular risk using WHO/ISH risk prediction charts in three low and middle income countries in Asia. BMC public Health 2013;1:539-551.
26. Van Der Heijden AA, Ortegon MM, Niessen LW, Nijpels G, Dekker JM. 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;11:2094-2098.
27. Jahangiry L, Farhangi MA, Rezaei F. Framingham risk score for estimation of 10-years of cardiovascular diseases risk in patients with metabolic syndrome. J Health Popul Nutr 2017;1:36-42.
28. Yousefzadeh G, Shokoohi M, Najafipour H, Shadkamfarokhi M. Applying the Framingham risk score for prediction of metabolic syndrome: the Kerman coronary artery disease risk study, Iran. ARYA Atheroscler 2015;3:179-185.
29. Meysamie A, Salarvand F, Khorasanizadeh M, Ghalehtaki R, Eskian M, Ghodsi S, Ghalehtaki S, Abbasi M, Etemad K, Asgari F. Cardiovascular risk assessment by FRS and SCORE in Iranian adult population. J Diabetes Metab Disord 2017;10:35-43.
30. Amiri ZS, Khajedaluee M, Rezaii A, Dadgarmoghaddam M. The risk of cardiovascular events based on the Framingham criteria in adults living in Mashhad (Iran). Electron Physician 2018;8:7164-7173.
31. Motamed N, Rabiee B, Perumal D, Poustchi H, Miresmail S J H, Farahani B, Maadi M, Saeedian F S, Ajdarkosh H, Khonsari MR. Comparison of cardiovascular risk assessment tools and their guidelines in evaluation of 10-year CVD risk and preventive recommendations: A population based study. Int J Cardiol 2017;228:52-57.
32. Faradonbeh NA, Nikaeen F, Akbari M, Almasi N, Vakhshoori M. Cardiovascular disease risk prediction among Iranian patients with diabetes mellitus in Isfahan Province, Iran, in 2014, by using Framingham risk score, atherosclerotic cardiovascular disease risk score, and high-sensitive C-reactive protein. ARYA Atheroscler 2018;4:163-168.
33. Khalili D, Hadaegh F, Soori H, Steyerberg EW, Bozorgmanesh M, Azizi F. Clinical usefulness of the Framingham cardiovascular risk profile beyond its statistical performance: the Tehran Lipid and Glucose Study. Am J Epidemiol 2012;3:177-186.
2. Ahmadi A, Soori H, Mehrabi Y, Etemad K, Khaledifar A. Epidemiological pattern of myocardial infarction and modelling risk factors relevant to in-hospital mortality: the first results from the Iranian myocardial infarction registry. Kardiol Pol 2015;6:451-457.
3. Ahmadi A, Soori H, Mehrabi Y, Etemad K. Spatial analysis of myocardial infarction in Iran: national report from the Iranian myocardial infarction registry. J Res Med Sci 2015;5:434-439.
4. Ruwanpathirana T, Owen A, Reid CM. Review on cardiovascular risk prediction. Cardiovasc Ther 2015;2:62-70.
5. Allan GM, Garrison S, McCormack J. Comparison of cardiovascular disease risk calculators. Curr Opin Lipidol 2014;4:254-265.
6. Goh LGH, Welborn TA, Dhaliwal SS. Independent external validation of cardiovascular disease mortality in women utilising Framingham and SCORE risk models: a mortality follow-up study. BMC Womens Health 2014;1:118-129.
7. Cooney MT, Cooney HC, Dudina A, Graham IM. Assessment of cardiovascular risk. Am J Epidemiol 2010;5:384-393.
8. Khaledifar A, Hashemzadeh M, Solati K, Poustchi H, Bollati V, Ahmadi A, Kheiri S, Banitalebi M, Sedehi M, Malekzadeh R. The protocol of a population-based prospective cohort study in southwest of Iran to analyze common non-communicable diseases: Shahrekord cohort study. BMC public health 2018;1:660-670.
9. Poustchi H, Eghtesad S, Kamangar F, Etemadi A, Keshtkar AA, Hekmatdoost A, Mohammadi Z, Mahmoudi Z, Shayanrad A, Roozafzai F. Prospective epidemiological research studies in Iran (the PERSIAN Cohort Study): rationale, objectives, and design. Am J Epidemiol 2018;187:647-55.
10. WHO/ISH risk prediction charts for 14 WHO epidemiological sub-regions. World Health Organization, Geneva 2007. https://www.who.int/cardiovascular_diseases/guidelines/Chart_predictions/en. (23 Jun 2019).
11. D'Agostino Sr RB, Pencina MJ, Massaro JM, Coady S. Cardiovascular disease risk assessment: insights from Framingham. Glob Heart 2013;1:11-23.
12. Versteylen MO, Joosen IA, Shaw LJ, Narula J, Hofstra L. Comparison of Framingham, PROCAM, SCORE, and Diamond Forrester to predict coronary atherosclerosis and cardiovascular events. J Nucl Cardiol 2011;5:904-915.
13. Schargrodsky H, Hernández-Hernández R, Champagne BM, Silva H, Vinueza R, Ayçaguer LCS, Touboul PJ, Boissonnet CP, Escobedo J, Pellegrini F . CARMELA: assessment of cardiovascular risk in seven Latin American cities. Am J Med 2008;1:58-65.
14. Chia YC, Gray SYW, Ching SM, Lim HM, Chinna K. Validation of the Framingham general cardiovascular risk score in a multiethnic Asian population: a retrospective cohort study. BMJ Open 2015;5:e007324.
15. Selvarajah S, Kaur G, Haniff J, Cheong KC, Hiong TG, van der Graaf Y, Bots M. Comparison of the Framingham Risk Score, SCORE and WHO/ISH cardiovascular risk prediction models in an Asian population. Int J Cardiol 2014;1:211-218.
16. Gutierrez J, Alloubani A, Mari M, Alzaatreh M. Cardiovascular disease risk factors: hypertension, diabetes mellitus and obesity among Tabuk Citizens in Saudi Arabia. Open Cardiovasc Med J 2018;4:41-49.
17. Awad A, Al-Nafisi H. Public knowledge of cardiovascular disease and its risk factors in Kuwait: a cross-sectional survey. BMC Public Health 2014;1:1131-1141.
18. Mazaherinejad A, Angorani H, Tamannaie Z, Parsa HM, Parsa HM. Prevalence of atherosclerotic cardiovascular risk factors among Iranian football referees 2014-2015. MJMS 2016;3:188-195.
19. Rezabeigi Davarani E, Iranpour A, Khanjani N, Mohseni M, Nazari Robati F. Cardiovascular diseases risk factors and the relationship between knowledge level and preventive behaviors for cardiovascular diseases among women in kerman. J Res Health Sci 2016;2:119-132.
20. Conroy RM, Pyörälä K, Fitzgerald Ae, Sans S, Menotti A, De Backer G, De Bacquer D, Ducimetiere P, Jousilahti P, Keil U . Estimation of ten-year risk of fatal cardiovascular disease in Europe: the SCORE project. Eur Heart J 2003;11:987-1003.
21. Fatema K, Zwar NA, Milton AH, Rahman B, Ali L. Application of two versions of the WHO/international society of hypertension absolute cardiovascular risk assessment tools in a rural Bangladeshi population. BMJ Open 2015;10:e008140.
22. Khanal MK, Ahmed MM, Moniruzzaman M, Banik PC, Dhungana R R, Bhandari P, Devkota S, Shayami A . Total cardiovascular risk for next 10 years among rural population of Nepal using WHO/ISH risk prediction chart. BMC Res Notes 2017;1:120-127.
23. Mendis S, Lindholm LH, Anderson SG, Alwan A, Koju R, Onwubere B, Kayani AM, Abeysinghe N, Duneas A, Tabagari. Total cardiovascular risk approach to improve efficiency of cardiovascular prevention in resource constrain settings. J Clin Epidemiol 2011;12:1451-1462.
24. Ofori S, Dodiyi-Manuel S, Akpa MR. Comparison of 3 risk estimators to guide initiation of statin therapy for primary prevention of cardiovascular disease. J Clin Lipidol 2017;6:1441-1447.
25. Otgontuya D, Oum S, Buckley BS, Bonita R. Assessment of total cardiovascular risk using WHO/ISH risk prediction charts in three low and middle income countries in Asia. BMC public Health 2013;1:539-551.
26. Van Der Heijden AA, Ortegon MM, Niessen LW, Nijpels G, Dekker JM. 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;11:2094-2098.
27. Jahangiry L, Farhangi MA, Rezaei F. Framingham risk score for estimation of 10-years of cardiovascular diseases risk in patients with metabolic syndrome. J Health Popul Nutr 2017;1:36-42.
28. Yousefzadeh G, Shokoohi M, Najafipour H, Shadkamfarokhi M. Applying the Framingham risk score for prediction of metabolic syndrome: the Kerman coronary artery disease risk study, Iran. ARYA Atheroscler 2015;3:179-185.
29. Meysamie A, Salarvand F, Khorasanizadeh M, Ghalehtaki R, Eskian M, Ghodsi S, Ghalehtaki S, Abbasi M, Etemad K, Asgari F. Cardiovascular risk assessment by FRS and SCORE in Iranian adult population. J Diabetes Metab Disord 2017;10:35-43.
30. Amiri ZS, Khajedaluee M, Rezaii A, Dadgarmoghaddam M. The risk of cardiovascular events based on the Framingham criteria in adults living in Mashhad (Iran). Electron Physician 2018;8:7164-7173.
31. Motamed N, Rabiee B, Perumal D, Poustchi H, Miresmail S J H, Farahani B, Maadi M, Saeedian F S, Ajdarkosh H, Khonsari MR. Comparison of cardiovascular risk assessment tools and their guidelines in evaluation of 10-year CVD risk and preventive recommendations: A population based study. Int J Cardiol 2017;228:52-57.
32. Faradonbeh NA, Nikaeen F, Akbari M, Almasi N, Vakhshoori M. Cardiovascular disease risk prediction among Iranian patients with diabetes mellitus in Isfahan Province, Iran, in 2014, by using Framingham risk score, atherosclerotic cardiovascular disease risk score, and high-sensitive C-reactive protein. ARYA Atheroscler 2018;4:163-168.
33. Khalili D, Hadaegh F, Soori H, Steyerberg EW, Bozorgmanesh M, Azizi F. Clinical usefulness of the Framingham cardiovascular risk profile beyond its statistical performance: the Tehran Lipid and Glucose Study. Am J Epidemiol 2012;3:177-186.
| Files | ||
| Issue | Vol 15 No 3 (2020): J Teh Univ Heart Ctr | |
| Section | Original Article(s) | |
| DOI | https://doi.org/10.18502/jthc.v15i3.4219 | |
| Keywords | ||
| Risk assessment Heart diseases Cohort studies | ||
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How to Cite
1.
Samaniyan Bavarsada P, Kheirib S, Ahmadi A. Estimation of the 10-Year Risk of Cardiovascular Diseases: Using the SCORE, WHO/ISH, and Framingham Models in the Shahrekord Cohort Study in Southwestern Iran. J Tehran Heart Cent. 2020;15(3):105-112.
