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Department of Family Medicine

Coronary Heart Disease Risk Assessment

General Note About Validity

M. Lenz and I. Mühlhauser (Kardiovaskuläre Risikoschätzung für eine informierte Patientenentscheidung. Wie valide sind die Prognoseinstrumente? Med. Klinik 99(11): 651-661, 2004) reviewed 12 cardiovascular risk assessment tools and respective validation studies.  They searched for discrimination between risk groups, predictive values, prognostic agreement, and transferability across populations.  They found that Framingham-based instruments overestimate cardiovascular risk for Central European populations by at least 30%.  Prior to application these instruments would need recalibration using regional data before implementation.  External validation of these 12 instruments is weak to non-existent.  Agreement between instruments beyond chance is moderate.

Framingham CHD Prediction Score

  • Authors: Kannel WB, McGee D, and Gordon T (1976)
  • Risk factors included: Sex, age, blood pressure, total cholesterol, LDL cholesterol, HDL cholesterol, smoking, diabetes status, and left ventricular hypertrophy (LVH).
  • Development: The Framingham CHD Prediction Score was originally developed to assess the relative importance of CHD risk factors and to quantify the absolute level of CHD risk for individuals without a history of cardiovascular disease.
  • Links to On-line Risk Assessment:
    National Cholesterol Education Program: Framingham CHD Risk assessment.
  • Assessment in Minorities:  The original Framingham risk equations were updated in 1991 by Anderson et al. to include the Framingham offspring, thereby providing estimates for people between the ages of 30 and 74.  A further update incorporating risk factor categories was made by WIlson et al. in 1998.  This update removed left ventricular hypertrophy from the model.  Because the Framingham Heart Study consists of white middle-class individuals, subsequent validation in minorities using data from other studies was carried out by D'Agostino et al. (2001).  Recalibration of the Framingham Risk Score model was required for some ethnic minorities where the original scores overestimated the 5-year risk of developing CHD.  After recalibration the Framingham Risk Score model worked well.
  • Detailed Notes

UKPDS Risk Engine

  • Authors: United Kingdom Prospective Diabetes Study (UKPDS) Group (2001)
  • Risk factors included: The model is specific for individuals with a diagnosis of diabetes and incorporates glycaemia (as HbA1c), systolic blood pressure, and lipid levels (total : HDL cholesterol ratio) as risk factors, in addition to age at time of diabetes diagnosis, sex, ethnic group, smoking status, and time since diagnosis of diabetes.  Because of treatment changes after the diagnosis of diabetes, several of these values are the mean of measurments taken one year apart.  Values collected only at the time of diagnosis did not have as great a predictive power.
  • Development: The UKPDS model provides an equation for estimating the risk of new CHD events in people with Type II diabetes and no history of CHD or stroke. It provides formulae for incidence rates, estimates of probability for CHD complications, and the relative risks associated with potential risk factors. The model provides equations for absolute risk, incorporating the effect of multiple risk factors to give overall event rates.
  • Assessment in Minorities:  The study population (n=4540) consisted of 7.8% Afro-Caribbean and 9.5% Asian Indian.
  • Reference: RJ Stevens, V Kothari, AI Adler, IM Stratton, and RR Holman on behalf of the United Kingdom Prospective Diabetes Study (UKPDS) Group (2001). The UKPDS risk engine: a model for the risk of coronary heart disease in Type II diabetes (UKPDS 56). Clinical Science 101: 671–679

Joint British Societies Coronary Risk Prediction Charts

  • Authors: British Cardiac Society, British Hyperlipidaemia Association, British Hypertension Society (1998)
  • Risk factors included: Age, gender, smoking, blood pressure, total cholesterol, HDL cholesterol, diabetes, and ECG evidence of LVH.  Blood pressure and cholesterol are treated as continuous variables. Family history of CHD or atherosclerotic disease is not included specifically in the calculation of CHD risk; however, it can be included by increasing the risk estimate by 1.5.
  • Development: These charts are based upon the Framingham data.  The aim of these joint recommendations is to encourage a unified approach to the management of patients with established CHD and/or other atherosclerotic disease, as well as Individuals at high risk for developing CHD or other atherosclerotic disease (i.e. those with hypertension, dyslipidaemia, diabetes mellitus, family history of premature CHD, or a combination of these risk factors). Patients with diabetes mellitus are at particularly high risk of CHD. The specific objectives of CHD prevention,
    and the prevention of other major atherosclerotic disease, are to reduce the risk of a further major cardiac event—that is, unstable angina or myocardial infarction (MI), or reinfarction, the need for
    coronary revascularisation procedures—and to reduce overall mortality in patients with established CHD.  In high risk individuals in the general population, the objective is to substantially reduce the risk of such individuals developing coronary disease or other major atherosclerotic disease.
    The computer program “Cardiac Risk Assessor” developed for these recommendations is the preferred method of calculating absolute 10 year CHD risk for an individual based on the Framingham function; it can also be used to calculate cardiovascular risk (including stroke) over the same period. This program is designed only for use with Microsoft Excel (version 5 or higher).
    The computer program or thecharts should not be used in patients with established CHD or other atherosclerotic disease, familial hypercholesterolaemia, or malignant hypertension. The CHD risk is calculated as a probability (%) of developing CHD (non-fatal MI or coronary death) over 10 years. Family history is not included in this risk equation from the Framingham study. Adjusting the computed risk upwards by a factor of 1.5 is appropriate in patients who have a first degree male relative developing CHD, or other atherosclerotic disease, before the age of 55 years, or a female first degree relative with a similar history before the age of 65 years.
  • Assessment in Minorities:  In ethnic minorities the Framingham risk equation should be used with caution as it has not been validated in these populations.
  • Reference: British Cardiac Society, British Hyperlipidaemia Association, British Hypertension Society,
    endorsed by the British Diabetic Association (1998) Joint British recommendations on prevention of
    coronary heart disease in clinical practice. Heart, 80(supplement 2): S1–S29.
  • Acquiring the Computer Program: An MS DOS version of the Cardiac Risk Assessor program is available from Professor Paul Durrington, Department of Medicine, Manchester Royal Infirmary, Oxford Road, Manchester M13 9WL, UK.


  • Authors: Assmann G, Cullen P, Schulte H (2002)
  • Risk factors included: In order of importance: age, LDL cholesterol, smoking, HDL cholesterol, systolic blood pressure, family history of premature MI, diabetes mellitus, triglycerides.  This study included only men.
  • Development: The Prospective Cardiovascular Münster (PROCAM) study included 5389 men ages 35 to 65 at the time of recruitment.  At the time of recruitment individuals who had a history of MI, stroke, or angina pectoris, or if the ECG showed signs of ischemic heart disease, were excluded from the study.  For each risk factor, categories were constructed based on the National Cholesterol Education Program III guidelines and the number of points for each category are presented in a table.  The PROCAM score is generated by summing the points received for each risk factor.  Another table shows the risk of having an acute coronary event (fatal or nonfatal MI or acute coronary death) depending on the PROCAM score.  The discrimination of the PROCAM model (based upon receiver-operating characteristics curve analysis) was 82.4%. In comparison, the Framingham model discrimination was significantly less (77.8%) in the same population.  The Framingham model consistently overestimated the risk in this population.
  • Assessment in Minorities:  The study population included no minorities, women, or men over the age of 65 at the time of recruitment.
  • Reference: Assmann G, Cullen P, Schulte H (2002) 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. Circulation 105: 310-315.

The European SCORE Project

  • Authors: Conroy RM, Pyörälä K, Fitzgerald AP, Sans S et al. (2003)
  • Risk factors included: Sex, age, smoking, systolic blood pressure, and either total cholesterol or the total/HDL cholesterol ratio.  Diabetes was excluded due to the lack of universally collected information with consistent definitions.  Only minor differences in risk assessment between the models using total cholesterol and those using the total/HDL cholesterol ratio were observed.
  • Development: The SCORE (Systematic COronary Risk Evaluation) project was initiated to develop a risk scoring system for use in the clinical management of cardiovascular risk in European clinical practice.  The project assembled a pool of datasets from 12 European cohort studies, mainly carried out in general population settings. Ten-year risk of fatal cardiovascular disease was calculated using a Weibull model in which age was used as a measure of exposure time to risk rather than as a risk factor. Separate estimation equations were calculated for coronary heart disease and for non-coronary cardiovascular disease. These were calculated for high-risk and low-risk regions of Europe. Two parallel estimation models were developed, one based on total cholesterol and the other on total cholesterol/HDL cholesterol ratio. Four sets of figures provide the risk of fatal CVD based upon European risk region, gender, smoking status, age, systolic blood pressure, and cholesterol.  Because calculating the risks of non-fatal CVD events is critically dependent on definitions and methods used in their ascertainment , the SCORE project shifted its emphasis to fatal CVD events only.  Formulas for calculating the risk of fatal CVD as well as the underlying risks of CHD and non-coronary CVD are given in the Appendix.
  • Assessment in Minorities:  The SCORE project was conducted using information from 12 European countries.  Race was never considered in the development of the SCORE project.
  • Reference: Conroy RM, Pyörälä K, Fitzgerald AP, Sans S, Menotti A, De Backer G, De Bacquer D, Ducimetière P, Jousilahti P, Keil U, Njølstad I, Oganov RG, Thomsen T, Tunstall-Pedoe H, Tverdal A, Wedel H, Whincup P, Wilhelmsen L, Graham IM, SCORE project group. (2003) Estimation of ten-year risk of fatal cardiovascular disease in Europe: the SCORE project. European Heart Journal 24(11):987-1003.

New Zealand CVD Risk-Benefit Prediction Guide

  • Authors: Jackson R and the Dyslipidaemia Advisory Group (1996)
  • Risk factors included: Sex, age, diabetes status, smoking status, blood pressure, and total/HDL cholesterol ratio.
  • Development: This guide provides a simple quantitative method for assessing a person's risk of CVC and the likely benefits of lowering blood pressure or cholesterol with drugs.  The charts are based on the Framingham Heart Study prognostic algorithm of Anderson et al. (1991).  The benefit of drug treatment is presented as the number of CVD events prevented per 100 treated individuals for 5 years.
  • Assessment in Minorities:  These charts are based upon the Framingham algorithms of 1991 and do not include any assessments in Minorities.
  • References: Jackson R (2000) Updated New Zealand cardiovascular disease risk-benefit predection guide.  BMJ 320: 709-710.
    Dyslipidaemia Advisory Group (1996) 1996 National Heart Foundation clinical guidelines for the assessment and management of dyslipidaemia. NZ Med J 109: 224-232.

Sheffield Risk Table

  • Authors: Haq IU, Jackson PR, Yeo WW, Ramsay LE (1995)
  • Risk factors included: The categorical variables of sex, age, hypertension, smoking, diabetes, and left ventricular hypertrophy.  The continuous variable of total serum cholesterol (mmol/L) is used in the earlier table (1995) and the total/HDL cholesterol ratio is used in the later table (2000).
  • Development: The Sheffield Risk Tables are based upon a logistic regression equation predicting coronary death risk derived from the Framingham population.  For people without a history of CVD the table presented in Haq et al. (1995) identifies subjects who have a specified degree of coronary risk, shows the serum cholesterol concentration that confers that degree of risk, and identifies subjects who will not have this degree of risk, irrespective of their cholesterol concentration.  For each combination of sex, hypertension, smoking, diabetes, and LVH, the table reports the total cholesterol level that confers a 1.5% or greater risk of having a fatal coronary event within one year.  These are the patients who could most benefit from treatment with an inhibitor of hydroxymethylglutaryl-coenzyme-A reductase.  The table was updated by Wallis et al. (2000) and identifies people at thresholds of 15% or 30% risk of a fatal CVD event over 10 years.  The table also incorporates the total/HDL cholesterol ratio rather than simply total serum cholesterol.  This updated table was tested with a population of 1000 taken from the 1995 Scottish Health Survey.  The table had 97% sensitivity and 95% specificity for coronary risk of >15% over 10 years when compared with the risk calculated from the Framingham algorithms.
  • Assessment in Minorities:  Having been based on the Framingham cohort, there is no specific assessment in minorities.  However, there is a note in Wallis et al. (2000) that the table underestimates CHD risk in British Asians.
  • References: Haq IU, Jackson PR, Yeop WW, Ramsay LE (1995) Sheffield risk and treatment table for cholesterol lowering for primary prevention of coronary heart disease.  Lancet 346: 1467-1471.
    Wallis EF, Ramsay LE, Haq IU, Ghahramani P, Jackson PR, Rowland-Yeo K, Yeo WW (2000) Coronary and cardiovascular risk estimation for primary prevention: validation of a new Sheffield table in the 1995 Scottish health survey population.  BMJ 320: 671-676.

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