PARS risk charts: A 10-year study of risk assessment for cardiovascular diseases in Eastern Mediterranean Region

This study was designed to develop a risk assessment chart for the clinical management and prevention of the risk of cardiovascular disease (CVD) in Iranian population, which is vital for developing national prevention programs. The Isfahan Cohort Study (ICS) is a population-based prospective study of 6504 Iranian adults ≥35 years old, followed-up for ten years, from 2001 to 2010. Behavioral and cardiometabolic risk factors were examined every five years, while biennial follow-ups for the occurrence of the events was performed by phone calls or by verbal autopsy. Among these participants, 5432 (2784 women, 51.3%) were CVD free at baseline examination and had at least one follow-up. Cox proportional hazard regression was used to predict the risk of ischemic CVD events, including sudden cardiac death due to unstable angina, myocardial infarction, and stroke. The model fit statistics such as area under the receiver-operating characteristic (AUROC), calibration chi-square and the overall bias were used to assess the model performance. We also tested the Framingham model for comparison. Seven hundred and five CVD events occurred during 49452.8 person-years of follow-up. The event probabilities were calculated and presented color-coded on each gender-specific PARS chart. The AUROC and Harrell’s C indices were 0.74 (95% CI, 0.72–0.76) and 0.73, respectively. In the calibration, the Nam-D’Agostino χ2 was 10.82 (p = 0.29). The overall bias of the proposed model was 95.60%. PARS model was also internally validated using cross-validation. The Android app and the Web-based risk assessment tool were also developed as to have an impact on public health. In comparison, the refitted and recalibrated Framingham models, estimated the CVD incidence with the overall bias of 149.60% and 128.23% for men, and 222.70% and 176.07% for women, respectively. In conclusion, the PARS risk assessment chart is a simple, accurate, and well-calibrated tool for predicting a 10-year risk of CVD occurrence in Iranian population and can be used in an attempt to develop national guidelines for the CVD management.

[1]  Dong Zhao,et al.  Predictive value for the Chinese population of the Framingham CHD risk assessment tool compared with the Chinese Multi-Provincial Cohort Study. , 2004, JAMA.

[2]  G. Assmann,et al.  Simple Scoring Scheme for Calculating the Risk of Acute Coronary Events Based on the 10-Year Follow-Up of the Prospective Cardiovascular Münster (PROCAM) Study , 2002, Circulation.

[3]  Rick Rogers,et al.  Android Application Development - Programming with the Google SDK , 2009 .

[4]  A. Zabetian,et al.  San Antonio heart study diabetes prediction model applicable to a Middle Eastern population? Tehran glucose and lipid study , 2010, International Journal of Public Health.

[5]  Helmut Schulte,et al.  Framingham risk function overestimates risk of coronary heart disease in men and women from Germany--results from the MONICA Augsburg and the PROCAM cohorts. , 2003, European heart journal.

[6]  R. Kelishadi,et al.  The Isfahan cohort study: Rationale, methods and main findings , 2011, Journal of Human Hypertension.

[7]  M. Pencina,et al.  General Cardiovascular Risk Profile for Use in Primary Care: The Framingham Heart Study , 2008, Circulation.

[8]  Mark Woodward,et al.  Separate and combined associations of body-mass index and abdominal adiposity with cardiovascular disease: collaborative analysis of 58 prospective studies. , 2011, Lancet.

[9]  M. Woodward,et al.  Laboratory-based and office-based risk scores and charts to predict 10-year risk of cardiovascular disease in 182 countries: a pooled analysis of prospective cohorts and health surveys. , 2017, The lancet. Diabetes & endocrinology.

[10]  K. Hughes,et al.  Risk factors and incident coronary heart disease in Chinese, Malay and Asian Indian males: the Singapore Cardiovascular Cohort Study. , 2001, International journal of epidemiology.

[11]  B Neal,et al.  1999 World Health Organization-International Society of Hypertension Guidelines for the management of hypertension. Guidelines sub-committee of the World Health Organization. , 1999, Clinical and experimental hypertension.

[12]  Ralph B. D'Agostino,et al.  Evaluation of the Performance of Survival Analysis Models: Discrimination and Calibration Measures , 2003, Advances in Survival Analysis.

[13]  N. Mohammadifard,et al.  Intake of legumes and the risk of cardiovascular disease: frailty modeling of a prospective cohort study in the Iranian middle-aged and older population , 2016, European Journal of Clinical Nutrition.

[14]  K. Rabiei,et al.  The cumulative incidence of conventional risk factors of cardiovascular disease and their population attributable risk in an Iranian population: The Isfahan Cohort Study , 2014, Advanced biomedical research.

[15]  M D Feher,et al.  Prediction of cardiovascular risk , 1999, BMJ.

[16]  R. Kelishadi,et al.  Metabolic syndrome: an emerging public health problem in Iranian women: Isfahan Healthy Heart Program. , 2008, International journal of cardiology.

[17]  J. Medalie,et al.  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. , 1993, Cardiology.

[18]  M. Sadeghi,et al.  Socioeconomic status and incident cardiovascular disease in a developing country: findings from the Isfahan cohort study (ICS) , 2012, International Journal of Public Health.

[19]  Risk assessment chart for death from cardiovascular disease based on a 19-year follow-up study of a Japanese representative population. , 2006, Circulation journal : official journal of the Japanese Circulation Society.

[20]  J. Marrugat,et al.  Estimación de riesgo de enfermedad coronaria mediante la función de Framingham adaptada para la población chilena , 2009 .

[21]  Jennifer G. Robinson,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 , 2014, Circulation.

[22]  Angela Cooper,et al.  Risk assessment and lipid modification for primary and secondary prevention of cardiovascular disease: summary of NICE guidance , 2008, BMJ : British Medical Journal.

[23]  Dong Zhao,et al.  Cardiovascular risk assessment: a global perspective , 2015, Nature Reviews Cardiology.

[24]  Rod Jackson,et al.  Treatment with drugs to lower blood pressure and blood cholesterol based on an individual's absolute cardiovascular risk , 2005, The Lancet.

[25]  G. Can,et al.  Coronary disease risk prediction algorithm warranting incorporation of C-reactive protein in Turkish adults, manifesting sex difference. , 2012, Nutrition, metabolism, and cardiovascular diseases : NMCD.

[26]  R. D'Agostino,et al.  Validation of the Framingham coronary heart disease prediction scores: results of a multiple ethnic groups investigation. , 2001, JAMA.

[27]  N. Sarraf-zadegan,et al.  Isfahan Healthy Heart Programme: a comprehensive integrated community-based programme for cardiovascular disease prevention and control. Design, methods and initial experience , 2003, Acta cardiologica.

[28]  Diabetes Uk,et al.  JBS 2: Joint British Societies9 guidelines on prevention of cardiovascular disease in clinical practice , 2005 .

[29]  B. Neal,et al.  Recalibration of a Framingham risk equation for a rural population in India , 2009, Journal of Epidemiology & Community Health.

[30]  H. Tunstall-Pedoe,et al.  Estimation of ten-year risk of fatal cardiovascular disease in Europe: the SCORE project. , 2003, European heart journal.

[31]  A. Hoes,et al.  2016 European Guidelines on cardiovascular disease prevention in clinical practice. , 2016, Revista espanola de cardiologia.

[32]  J. Mckenney,et al.  National Cholesterol Education Program Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel III) , 2002 .

[33]  J. Marrugat,et al.  [Estimation of coronary heart disease risk in Chilean subjects based on adapted Framingham equations]. , 2009, Revista medica de Chile.

[34]  M. Mayo-Smith,et al.  Differences in Generalists' and Cardiologists' Perceptions of Cardiovascular Risk and the Outcomes of Preventive Therapy in Cardiovascular Disease , 1996, Annals of Internal Medicine.

[35]  F. Azizi,et al.  A simple risk score effectively predicted type 2 diabetes in Iranian adult population: population-based cohort study. , 2011, European journal of public health.

[36]  R. Bhopal,et al.  Why might South Asians be so susceptible to central obesity and its atherogenic consequences? The adipose tissue overflow hypothesis. , 2007, International journal of epidemiology.

[37]  J. Danesh,et al.  Separate and combined associations of body-mass index and abdominal adiposity with cardiovascular disease: collaborative analysis of 58 prospective studies , 2011, The Lancet.

[38]  K. Majidzadeh-A,et al.  Sagittal abdominal diameter to triceps skinfold thickness ratio: a novel anthropometric index to predict premature coronary atherosclerosis. , 2013, Atherosclerosis.

[39]  S. Yusuf,et al.  Obesity and the risk of myocardial infarction in 27 000 participants from 52 countries: a case-control study , 2005, The Lancet.

[40]  Shah Ebrahim,et al.  JOINT ESC GUIDELINES 2016 European Guidelines on cardiovascular disease prevention in clinical practice – Web Addenda , 2016 .

[41]  M. Woodward,et al.  Adding social deprivation and family history to cardiovascular risk assessment: the ASSIGN score from the Scottish Heart Health Extended Cohort (SHHEC) , 2005, Heart.

[42]  M. Drazner,et al.  2013 ACCF/AHA guideline for the management of heart failure: a report of the American College of Cardiology Foundation/American Heart Association Task Force on Practice Guidelines. , 2013, Journal of the American College of Cardiology.

[43]  Treatment of Obesity in Adults Clinical Guidelines on the Identification, Evaluation, and Treatment of Overweight and Obesity in Adults--The Evidence Report. National Institutes of Health. , 1998, Obesity research.

[44]  P. Poole‐Wilson,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. , 1994, European heart journal.

[45]  M. Bakhtiyari,et al.  The Incidence of Coronary Heart Disease and the Population Attributable Fraction of Its Risk Factors in Tehran: A 10-Year Population-Based Cohort Study , 2014, PloS one.

[46]  J. Hippisley-Cox,et al.  Derivation and validation of QRISK, a new cardiovascular disease risk score for the United Kingdom: prospective open cohort study , 2007, BMJ : British Medical Journal.

[47]  J. Robson,et al.  Lipid modification: cardiovascular risk assessment and the modification of blood lipids for the primary and secondary prevention of cardiovascular disease , 2007, Heart.

[48]  T. Jørgensen,et al.  A cross-validation of risk-scores for coronary heart disease mortality based on data from the Glostrup Population Studies and Framingham Heart Study. , 2002, International journal of epidemiology.

[49]  N. Sarrafzadegan,et al.  Incidence of cardiovascular diseases in an Iranian population: the Isfahan Cohort Study. , 2013, Archives of Iranian medicine.

[50]  P. Poole‐Wilson,et al.  Prevention of coronary heart disease in clinical practice , 1994 .

[51]  J. Mckenney,et al.  Executive Summary of The 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). , 2001, JAMA.

[52]  Tae-Yong Lee,et al.  A coronary heart disease prediction model: the Korean Heart Study , 2014, BMJ Open.

[53]  N. Sarrafzadegan,et al.  Appropriate cut-off values of waist circumference to predict cardiovascular outcomes: 7-year follow-up in an Iranian population. , 2012, Internal medicine.

[54]  Gretchen A. Stevens,et al.  A novel risk score to predict cardiovascular disease risk in national populations (Globorisk): a pooled analysis of prospective cohorts and health examination surveys. , 2015, The lancet. Diabetes & endocrinology.

[55]  F. Hadaegh,et al.  Predictive accuracy of the ‘Framingham’s general CVD algorithm’ in a Middle Eastern population: Tehran Lipid and Glucose Study , 2011, International journal of clinical practice.

[56]  E. Steyerberg,et al.  Clinical usefulness of the Framingham cardiovascular risk profile beyond its statistical performance: the Tehran Lipid and Glucose Study. , 2012, American journal of epidemiology.

[57]  Mike Kirby,et al.  Joint British Societies' Guidelines on Prevention of Cardiovascular Disease in Clinical Practice , 2005 .

[58]  Jennifer G. Robinson,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 , 2014, Circulation.