BMJ  2003;327:1267 (29 November), doi:10.1136/bmj.327.7426.1267

Primary care

Predictive accuracy of the Framingham coronary risk score in British men: prospective cohort study

¹ Department of Social Medicine, University of Bristol, Bristol BS8 2PR, ² Department of Primary Care and Population Sciences, Royal Free and University College Medical School, London NW3 2PF, ³ Department of Community Health Sciences, St George's Hospital Medical School, London SW17 0RE, ⁴ Tayside Centre for General Practice, University of Dundee, Dundee DD2 4AD

Abstract

Objective To establish the predictive accuracy of the Framingham risk score for coronary heart disease in a representative British population.

Design Prospective cohort study.

Setting 24 towns in the United Kingdom.

Participants 6643 British men aged 40-59 years and free from cardiovascular disease at entry into the British regional heart study.

Main outcome measures Comparison of observed 10 year coronary heart disease mortality and event rates with predicted rates for each individual, using the relevant Framingham risk equation.

Results Of 6643 men, 2.8% (95% confidence interval 2.4% to 3.2%) died from coronary heart disease compared with 4.1% predicted (relative overestimation 47%, P < 0.0001). A fatal or non-fatal coronary heart disease event occurred in 10.2% (9.5% to 10.9%) of the men compared with 16.0% predicted (relative overestimation 57%, P < 0.0001). These relative degrees of overestimation were similar at all levels of coronary heart disease risk, so that overestimation of absolute risk was greatest for those at highest risk. A simple adjustment provided an improved level of accuracy. In a "high risk score" approach, most cases occur in the low risk group. In this case, 84% of the deaths from coronary heart disease and non-fatal events occurred in the 93% of men classified at low risk (< 30% in 10 years) by the Framingham score.

Conclusion Guidelines for the primary prevention of coronary heart disease advocate offering preventive measures to individuals at high risk. Currently recommended risk scoring methods derived from the Framingham study significantly overestimate the absolute coronary risk assigned to individuals in the United Kingdom.

Introduction

Coronary heart disease is a major cause of death and disability in the developed world.¹ Identification of people who are at high risk of developing coronary heart disease but currently have no symptoms has become an accepted method for the primary prevention of coronary heart disease in many countries. The national service framework for coronary heart disease in England and Wales states that people whose estimated risk of coronary heart disease based on a specified risk factor profile is 30% over 10 years should be identified and offered appropriate advice and treatment.² European, American, and Canadian guidelines also use predicted 10 year risk to identify people for risk factor modification.^3-6

It is recommended that risk assessment be performed using one of several methods that combine values for different risk factors to produce a quantitative risk estimate.^7-9 These methods use regression equations derived from a population sample of the Framingham heart study and the Framingham offspring study.¹⁰ Despite evidence that Framingham risk equations systematically overestimate risk of coronary heart disease in populations with lower coronary heart disease mortality, risk scoring methods based on these equations have been introduced widely.^11-13 It remains unclear, however, whether the Framingham risk score accurately predicts risk of coronary heart disease in the British population. We assessed the ability of the Framingham risk equations to predict death from coronary heart disease and the combination of fatal and non-fatal coronary heart disease events that is the outcome used in current scoring methods, in a representative population of British men over a 10 year period.^7-9

Participants and methods

The Framingham studies
The risk assessment methods recommended for British and European use are adapted from published equations derived from 5573 men and women from the Framingham heart study and the Framingham offspring study. People aged 30-74 and free of cardiovascular disease were included, and risk estimates for cardiovascular diseases were derived from around 12 years of follow up. Equations were derived for six outcomes, two of which we consider here: death from coronary heart disease, and all fatal and non-fatal coronary heart disease events (box).^{10 14}

The British regional heart study
The British regional heart study is a prospective study of 7735 men, aged 40-59 years at entry (1978-80), who were randomly selected from the age and sex registers of one general practice in each of 24 towns in the United Kingdom. The towns were selected to represent the range of cardiovascular disease mortality in the United Kingdom at the time.¹⁵ The response rate was 78%, and participants have been followed up for cause specific mortality using the NHS central registers and for cardiovascular morbidity through regular two yearly reviews of general practice records, with fewer than 1% of participants lost to follow up.¹⁶ For the purpose of our analysis, we chose the criteria used to define pre-existing cardiovascular disease in the British regional heart study to match those of the Framingham study as closely as possible (table 1).¹⁷

View this table: [in this window] [in a new window]   Table 1 Risk factor and definitions of end points

 

Framingham risk equations for coronary heart disease death (B1) and coronary heart disease events (B2) in men over 10 years Step 1 For coronary heart disease mortality calculate* µ = 11.2889 - 0.588xlog(systolic blood pressure) - 0.1367xsmoking - 0.3448xlog(total/high density lipoprotein cholesterol) - 0.1237xelectrocardiographic left ventricular hypertrophy - 0.944xlog(age) - 0.0474xdiabetes = exp(2.9851 - 0.9142µ) (B1) For coronary heart disease events calculate* µ = 15.5303 - 0.9119xlog(systolic blood pressure) - 0.2767xsmoking - 0.7181xlog(total/high density lipoprotein cholesterol) - 0.5865xelectrocardiographic left ventricular hypertrophy - 1.4792xlog(age) - 0.1759xdiabetes = exp(- 0.3155 - 0.2784x(µ - 4.4181)) (B2) Step 2 For both equations calculate: µ = (log(10) - µ)/ Length of follow up = 10 years Step 3 The predicted probability is then given by: p=1 - exp(-exp(u)) *Variables smoking, electrocardiographic left ventricular hypertrophy, and diabetes are set to 1 when present and 0 when absent. Systolic blood pressure measured in mm Hg and age in years

Statistical methods
Assessing the accuracy of the Framingham equation
Using the appropriate Framingham equations, we calculated the risk of death from coronary heart disease and all coronary heart disease events over a 10 year period for each of the men in the British regional heart study who were initially free of cardiovascular disease and had complete information on risk factors (see box). We categorised the men into groups defined by quintiles of Framingham risk, systolic blood pressure, total to high density lipoprotein cholesterol ratio, and age. We compared the average predicted event rates within each quintile for both end points with the observed 10 year rates. The Hosmer Lemeshow test was used to assess goodness of fit.¹⁸

Geographical variation
To assess any regional differences between observed and predicted rates, we also categorised the men by region of residence at baseline: Scotland, the north of England, the Midlands and Wales, and the south of England.

Discrimination
To assess the performance of the screening test at identifying individuals at "high risk," we calculated the sensitivity and specificity for risk score thresholds of 30% and 15% over 10 years.

Results

Of 7735 men recruited to the British heart regional study, 6942 (89.7%) were free of definite angina on the Rose angina questionnaire and had no recall of a doctor diagnosis of cardiovascular disease and no electrocardiographic evidence of definite myocardial infarction. Of these men, 6643 (95.7%) had complete data on risk factors at baseline. Table 2 compares the baseline characteristics of these men with those of the 2590 men from the Framingham cohorts used in the derivation of the risk equations.

View this table: [in this window] [in a new window]   Table 2 Baseline characteristics of men in Framingham studies and British regional heart study without pre-existing cardiovascular disease and with complete data on risk factors

 

Observed and predicted coronary heart disease mortality
When the coronary heart disease mortality equation (equation B1 in box) was applied to each of the men in the British regional heart study, the predicted number of deaths from coronary heart disease within 10 years was 270 (4.1%). This compared with an observed 183 deaths from coronary heart disease, giving a rate of 2.8% (95% confidence interval 2.4% to 3.2%) over the first 10 years of follow up. Figure 1 displays predicted and observed mortality from coronary heart disease across a range of risk levels (according to the quintiles of Framingham risk, systolic blood pressure, total to high density lipoprotein cholesterol, and age). This relative over-prediction of mortality risk by 47% (P value for goodness of fit < 0.0001) was similar at all risk levels (fig 1a), so that over-prediction of absolute risk was greatest for people at highest risk. Similarly, figures 1b-d show that significant overestimation of risk occurs at all levels of the risk factors concerned, apart from the lowest level of systolic blood pressure. For the combined outcome of fatal coronary heart disease and any diagnosis of myocardial infarction or angina (equation B2 in box), the observed number of events over 10 years was 677 (event rate 10.2%, 95% confidence interval 9.5% to 10.9%) compared with a predicted 1062 (16.0%)—a relative over-prediction of 57% (P value for goodness of fit < 0.0001; fig 2).

View larger version (44K): [in this window] [in a new window]   Fig 1 Ten year predicted versus observed coronary heart disease mortality with 95% confidence intervals by quintile of Framingham risk, systolic blood pressure, total to high density lipoprotein cholesterol ratio, and age

 

View larger version (44K): [in this window] [in a new window]   Fig 2 Ten year predicted versus observed coronary heart disease event rates with 95% confidence intervals by quintile of Framingham risk, systolic blood pressure, total to high density lipoprotein cholesterol ratio, and age

 

Geographical variation
Table 3 shows the observed versus predicted rates of coronary heart disease mortality and all coronary events by region. Over-prediction by the Framingham equations occurred in all regions but was greatest in the south of England and the Midlands and Wales where there was relatively lower mortality and morbidity than in Scotland and the north of England.

View this table: [in this window] [in a new window]   Table 3 Ten year predicted versus observed rates of coronary heart disease mortality and all coronary events by region

 

Recalibration
As the relative over-prediction was about constant at all levels of risk, it was possible for us to adjust the Framingham scores by dividing the calculated score for each individual by the amount of over-prediction. Recalibrated probabilities of death from coronary heart disease were therefore obtained from the 10 year predictions by dividing the final score by 1.47. For example, an individual predicted to have a 5% chance of a fatal coronary heart disease event within 10 years had a recalibrated risk of 3.4%. After making this correction, the predicted risk became close to the observed rate at all levels of risk (fig 3a), as indicated by a substantial decrease in the ² statistic for goodness of fit from 30.2 to 3.4. Similarly, the risk equation for coronary heart disease events was corrected to take into account the 57% relative over-prediction by dividing the Framingham prediction by 1.57 (fig 3b). Again a large decrease was observed in the goodness of fit statistic from 155.3 to 24.6.

View larger version (27K): [in this window] [in a new window]   Fig 3 Predicted coronary heart disease death and coronary heart disease event risks before and after recalibration with observed 10 year rates

 

Discrimination
When we applied the coronary event equation (see box) to the baseline data in the British regional heart study, 444 men (6.7%) had a predicted 10 year coronary heart disease event risk of 30% (average predicted risk 36.2%), of whom only 106 (out of the 677 men with a coronary heart disease event) actually had a coronary heart disease event within the following 10 years—a sensitivity of 16% (106/677). The sensitivity increased to 75% (509/677) when a 15% risk threshold was used, but this was at the expense of a large drop in specificity from 94% (5628/5966) to 55% (3258/5966) and a large increase in the proportion of men classified as high risk (from 6.7% to 48.4%). Similar estimates of sensitivity and specificity were obtained when using these thresholds to identify individuals at high risk of coronary heart disease death within 10 years.

When the recalibrated equation was used, those in the high risk group identified by using the 30% threshold would now constitute only 0.5% of the population and identify only 1.8% (12/677) of the coronary heart disease events occurring within 10 years, so that preventive interventions restricted to this group would have a limited population impact. If a 15% threshold was used with the recalibrated equation, 17% of the population would be classified as high risk, and 37% (249/677) of coronary heart disease events would be identified. The specificities at the 30% or more and 15% or more thresholds using the recalibrated equation would be 99.6% (5944/5966)and 85% (5055/5966), respectively.

Discussion

The Framingham equations used in current risk scoring methods over-predict the risk of mortality from coronary heart disease and all fatal and non-fatal coronary heart disease events by 47% and 57%, respectively, compared with observed events in a representative sample of British men. The relative degree of over-prediction was similar at all levels of individual risk.

Limitations of study
The Framingham study included the category "unrecognised myocardial infarction" in the ascertainment of non-fatal coronary heart disease events, therefore a potential source of bias could exist. However, this seems to have had little effect, as both fatal and all events were similarly overestimated. This is probably because the definition of a coronary heart disease event in the British regional heart study was broad, including all possible cases of myocardial infarction and angina documented in the medical records. Although coronary heart disease death is a more accurately defined end point, there is still a possible source of bias in the way the cause of death was identified. The British regional heart study used death certificates and postmortem reports, whereas in the Framingham study the cause of death documented on the certificate was verified by reviewing autopsy data, hospital records, and records of the attending doctor. However, coronary heart disease is an over-reported cause of death on death certificates, so any bias would tend to result in our analyses being conservative, underestimating the level of over-prediction.¹⁹ Some minor differences are apparent in the individuals excluded from both studies and in the use of a more sensitive Framingham definition of diabetes. The numbers of patients with diabetes, however, are small, and because the unidentified predicted risk for such patients would be underestimated, any bias would again lead to our results being conservative. A further limitation of our study is that its conclusions cannot be assumed to apply to women, although the effect of altering risk factors and the accuracy of models predicting coronary heart disease are similar in both men and women and therefore the findings are likely to be relevant to risk prediction in women.^{12 20}

Other studies
The Whickham (UK) study, conducted between 1972 and 1974 with a single follow up 20 years later, compared observed events in 1700 men and women with rates predicted by a Framingham equation.^{21 22} The observed and predicted event rates in the higher risk population (coronary heart disease event rate greater than 1.5% per year) were similar, but the Framingham equation underestimated risk in those at lower risk. In the Whickham study, the annual coronary heart disease event rate was 1.56% compared with 1.02% for men in the British regional heart study. This may reflect the true risk of the population from the north east of England, or might be because the ascertainment of coronary heart disease events was broad, including all participants who had had minor electrocardiographic changes on follow up and all deaths with any mention of ischaemic heart disease.

A trial investigating the effectiveness of pravastatin in the primary prevention of coronary heart disease found a close agreement between the observed coronary heart disease event rate in the placebo group over 4.4 years and the value predicted from the Framingham equation. Both the Scottish location and the other inclusion criteria of the trial, however, led to the inclusion of a group at particularly high absolute risk, with an annual coronary heart disease event rate in the placebo group of 1.59%.²³ In German, Italian, and Danish studies, Framingham risk scores with differing outcomes have been shown to overestimate risk by up to 50%.^{12 13 24} A European based risk score has been devised to address this.²⁵ In a comparison of the British regional heart study, the prospective cardiovascular Munster (PROCAM) heart study, Dundee, and Framingham risk functions, no direct validation was possible because different end points were used and no follow up data were collected.²⁶

Explanations for different predicted and observed risk
The over-prediction of 10 year risk by the Framingham equations in our analysis is likely to reflect a true difference in the levels of risk between the two populations and is unlikely to be due to over fitting of the Framingham data, as the number of risk factors considered is modest compared with the number of events observed.²⁷ Coronary heart disease mortality in England and Wales in 1980 was 30% lower than that in the United States in 1970.²⁸ The difference between this figure and the 47% overestimation found in our study may be due to differences between national statistics and the study populations as well as the predictive inaccuracy of the Framingham equation in the population participating in the British regional heart study. Furthermore, possible explanations for the differences in US and British mortality may be better control of coronary risk factors and better treatment of coronary heart disease experienced by the later British cohort.

Risk functions derived from the Framingham study and others are reasonably consistent at ranking individuals according to their relative risk, and differences between the observed and predicted risk usually depend on the background risk of the population to which the function is applied.^{12 24} We have shown inter-regional variation suggesting that over-prediction is greater in the regions of Britain with lower background coronary heart disease risk. Differences in observed and predicted risk have been shown in different countries and between ethnic groups and may be attributable to other risk factors that are not included in the model.^{12 24 29}

Implications
Overestimation of an individual's true risk and the poor sensitivity of the recommended tool to identify and target individuals for treatment have important implications for a national screening test.² An overestimated assessment of coronary heart disease risk will undermine a patient's ability to make an informed choice about starting preventive treatment, may cause unnecessary anxiety, and may affect life insurance premiums.³⁰ If the patient's absolute risk is lower than predicted, the absolute benefits of intervention will be smaller and the balance of risks and benefits less favourable. Additionally, overestimation of risk prediction will adversely affect direct prescribing costs as well as the costs of drug monitoring and dealing with side effects.

The accuracy of risk estimates derived from cohort studies or from randomised controlled trials are always open to the criticism of being out of date compared with current morbidity rates, owing to the delay between the collection of baseline data and the reporting of incident events.³¹ If coronary heart disease rates continue to fall, the discrepancy between predicted and actual risk is likely to increase, as the decline is not entirely attributable to falls in the risk factors included in the Framingham equation.³² Furthermore, fewer people will fall into the high risk group, causing the proportion of coronary heart disease events prevented by targeting only these individuals to be reduced.

We have shown that current risk scoring methods seem to overestimate coronary heart disease risk and that a simple adjustment can improve their predictive accuracy in the British population. Nevertheless, further refinements are necessary before the substantial variations in coronary heart disease risk found between different regions and different ethnic groups, socioeconomic status, and family history of coronary heart disease can be accommodated into an accurate and effective treatment decision aid.

What is already known on this topic Primary prevention of coronary heart disease involves identifying patients at high risk and offering them lifelong preventive treatment Most risk assessment methods rely on equations derived from the Framingham study Evidence is conflicting as to the suitability of these equations for British and other European populations What this study adds Recommended risk scoring methods overestimated coronary risk in a representative British male population This was similar at all levels of coronary heart disease risk and could be reduced by a simple adjustment Use of a predicted 30% coronary heart disease 10 year event rate threshold to identify patients at high risk can fail to identify most who go on to have a coronary heart disease event over the following 10 years

---

Editorial by Hense

Baseline serum total cholesterol and high density lipoprotein cholesterol were measured at the Wolfson Research Laboratories, Birmingham. The British regional heart study is a British Heart Foundation Research Group with additional support from the Department of Health, England. Margaret May provided helpful comments on an early draft of the paper.

Contributors: SE and TF developed the original idea for this study. PB drafted the paper and JE performed the analyses assisted by FL. PW and MW contributed to the design and execution of the British regional heart study. All authors contributed to the interpretation of data and the writing of the paper and have seen and approved the final version. PB and JE will act as guarantors for the paper.

Funding: PB is funded by the Wellcome Trust. The views expressed here are those of the authors and not necessarily those of the funding agencies. The funding agencies had no role in the data collection or in the writing of this paper. The guarantors accept full responsibility for the conduct of the study, had access to the data, and controlled the decision to publish.

Competing interests: None declared.

Ethical approval: None required.

bmj.com 2003;327:1267

References

1. Petersen S, Rayner M. Coronary heart disease statistics: 2002 edition. London: British Heart Foundation Statistics Database, 2002: 1-164.
2. Department of Health. National service framework for coronary heart disease. London: DoH, 2000.
3. Wood D, De Backer G, Faergeman O, Graham I, Mancia G, Pyorala K. Prevention of coronary heart disease in clinical practice: recommendations of the second joint task force of European and other societies on coronary prevention. Atherosclerosis 1998;140: 199-270.[CrossRef][Web of Science][Medline]
4. Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults. 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). JAMA 2001;285: 2486-97.[Free Full Text]
5. Grundy SM, Pasternak R, Greenland P, Smith S Jr, Fuster V. Assessment of cardiovascular risk by use of multiple-risk-factor assessment equations: a statement for healthcare professionals from the American Heart Association and the American College of Cardiology. Circulation 1999;100: 1481-92.[Free Full Text]
6. Fodor JG, Frohlich JJ, Genest JJ Jr, McPherson PR. Recommendations for the management and treatment of dyslipidemia. Report of the working group on hypercholesterolemia and other dyslipidemias. CMAJ 2000;162: 1441-7.[Free Full Text]
7. Joint British recommendations on prevention of coronary heart disease in clinical practice. British Cardiac Society, British Hyperlipidaemia Association, British Hypertension Society, endorsed by the British Diabetic Association. Heart 1998;80(suppl 2): S1-29.
8. Jackson PR. Updated New Zealand cardiovascular disease risk-benefit prediction guide. BMJ 2000;320: 709-10.[Free Full Text]
9. Wallis EJ, Ramsay LE, Haq IU, Ghahramani P, Jackson PR, Rowland-Yeo K, et al. Coronary and cardiovascular risk estimation for primary prevention: validation of a new Sheffield table in the 1995 Scottish health survey population. BMJ 2000;320: 671-6.[Abstract/Free Full Text]
10. Anderson KM, Wilson PW, Odell PM, Kannel WB. An updated coronary risk profile. A statement for health professionals. Circulation 1991;83: 356-62.[Free Full Text]
11. Laurier D, Nguyen PC, Cazelles B, Segond P. Estimation of CHD risk in a French working population using a modified Framingham model. The PCV-METRA Group. J Clin Epidemiol 1994;47: 1353-64.[CrossRef][Web of Science][Medline]
12. Hense HW, Schulte H, Lowel H, Assmann G, Keil U. Framingham risk function overestimates risk of coronary heart disease in men and women from Germany—results from MONICA Augsburg and the PROCAM cohorts. Eur Heart J 2003;3: 1-9.
13. Menotti A, Puddu PE, Lanti M. Comparison of the Framingham risk function-based coronary chart with a risk function from an Italian population study. Eur Heart J 2000;21: 365-70.[Abstract/Free Full Text]
14. Anderson KM, Odell PM, Wilson PW, Kannel WB. Cardiovascular disease risk profiles. Am Heart J 1991;121: 293-8.[CrossRef][Web of Science][Medline]
15. Shaper AG, Pocock SJ, Walker M, Cohen NM, Wale CJ, Thomson AG. British regional heart study: cardiovascular risk factors in middle-aged men in 24 towns. BMJ 1981;283: 179-86.
16. Walker M, Shaper AG, Lennon L, Whincup PH. Twenty year follow-up of a cohort based in general practices in 24 British towns. J Public Health Med 2000;22: 479-85.[Abstract/Free Full Text]
17. Shaper AG, Cook DG, Walker M, Macfarlane PW. Prevalence of ischaemic heart disease in middle aged British men. Br Heart J 1984;51: 595-605.[Abstract/Free Full Text]
18. Hosmer DW, Lemeshow S. Applied logistic regression. New York: Wiley, 1989.
19. Lloyd-Jones DM, Martin DO, Larson MG, Levy D. Accuracy of death certificates for coding coronary heart disease as the cause of death. Ann Intern Med 1998;129: 1020-6.[Abstract/Free Full Text]
20. Gueyffier F, Boutitie F, Boissel JP, Pocock S, Coope J, Cutler J, et al. Effect of antihypertensive drug treatment on cardiovascular outcomes in women and men. A meta-analysis of individual patient data from randomized, controlled trials. The INDANA Investigators. Ann Intern Med 1997;126: 761-7.[Abstract/Free Full Text]
21. Vanderpump MP, Tunbridge WM, French JM, Appleton D, Bates D, Clark F, et al. The development of ischemic heart disease in relation to autoimmune thyroid disease in a 20-year follow-up study of an English community. Thyroid 1996;6: 155-60.[Web of Science][Medline]
22. Ramachandran S, French JM, Vanderpump MP, Croft P, Neary RH. Using the Framingham model to predict heart disease in the United Kingdom: retrospective study. BMJ 2000;320: 676-7.[Free Full Text]
23. West of Scotland Coronary Prevention Study Group. Influence of pravastatin and plasma lipids on clinical events in the west of Scotland coronary prevention study (WOSCOPS). Circulation 1998;97: 1440-5.[Abstract/Free Full Text]
24. Thomsen TF, McGee D, Davidsen M, Jorgensen T. A cross-validation of risk-scores for coronary heart disease mortality based on data from the Glostrup Population Studies and Framingham Heart Study. Int J Epidemiol 2002;31: 817-22.[Abstract/Free Full Text]
25. Conroy RM, Pyorala K, Fitzgerald AP, Sans S, Menotti A, De Backer G, et al. Estimation of ten-year risk of fatal cardiovascular disease in Europe: the SCORE project. Eur Heart J 2003;24: 987-1003.[Abstract/Free Full Text]
26. Haq IU, Ramsay LE, Yeo WW, Jackson PR, Wallis EJ. Is the Framingham risk function valid for northern European populations? A comparison of methods for estimating absolute coronary risk in high risk men. Heart 1999;81: 40-6.[Abstract/Free Full Text]
27. Mantel N, Haenszel W. Statistical aspects of the analysis of data from retrospective studies of disease. J Natl Cancer Inst 1959;22: 719-48.
28. Lawlor DA, Ebrahim S, Davey SG. Sex matters: secular and geographical trends in sex differences in coronary heart disease mortality. BMJ 2001;323: 541-5.[Abstract/Free Full Text]
29. D'Agostino RB Sr, Grundy S, Sullivan LM, Wilson P, CHD Risk Prediction Group. Validation of the Framingham coronary heart disease prediction scores: results of a multiple ethnic groups investigation. JAMA 2001;286: 180-7.[Abstract/Free Full Text]
30. Brindle P, Fahey T. Primary prevention of coronary heart disease. BMJ 2002;325: 56-7.[Free Full Text]
31. Pocock SJ, McCormack V, Gueyffier F, Boutitie F, Fagard RH, Boissel JP. A score for predicting risk of death from cardiovascular disease in adults with raised blood pressure, based on individual patient data from randomised controlled trials. BMJ 2001;323: 75-81.[Abstract/Free Full Text]
32. Kuulasmaa K, Tunstall-Pedoe H, Dobson A, Fortmann SP, Sans S, Tolonen H, et al. Estimation of contribution of changes in classic risk factors to trends in coronary-event rates across the WHO MONICA project populations. Lancet 2000;355: 675-87.[CrossRef][Web of Science][Medline]

(Accepted October 16, 2003)

CiteULike    Complore    Connotea    Del.icio.us    Digg    Reddit    StumbleUpon    Technorati    What's this?

Relevant Articles

An independent external validation and evaluation of QRISK cardiovascular risk prediction: a prospective open cohort study

Gary S Collins and Douglas G Altman
BMJ 2009 339: b2584. [Abstract] [Full Text] [PDF]

Derivation and validation of QRISK, a new cardiovascular disease risk score for the United Kingdom: prospective open cohort study

Julia Hippisley-Cox, Carol Coupland, Yana Vinogradova, John Robson, Margaret May, and Peter Brindle
BMJ 2007 335: 136. [Abstract] [Full Text] [PDF]

Cardiovascular risk estimation: important but may be inaccurate

Vishnu Madhok and Tom Fahey
BMJ 2006 332: 1422. [Full Text] [PDF]

Predicting prognosis in stable angina—results from the Euro heart survey of stable angina: prospective observational study

Caroline A Daly, Bianca De Stavola, Jose L Lopez Sendon, Luigi Tavazzi, Eric Boersma, Felicity Clemens, Nicholas Danchin, Francois Delahaye, Anselm Gitt, Desmond Julian, David Mulcahy, Witold Ruzyllo, Kristian Thygesen, Freek Verheugt, Kim M Fox on behalf of the Euro Heart Survey Investigators
BMJ 2006 332: 262-267. [Abstract] [Full Text] [PDF]

Estimating the high risk group for cardiovascular disease in the Norwegian HUNT 2 population according to the 2003 European guidelines: modelling study

Linn Getz, Johann A Sigurdsson, Irene Hetlevik, Anna Luise Kirkengen, Solfrid Romundstad, and Jostein Holmen
BMJ 2005 331: 551. [Abstract] [Full Text] [PDF]

Current assessment methods overestimate coronary risk
BMJ 2003 327: 0. [Full Text]

The NHS experiment

Kamran Abbasi
BMJ 2003 327: 0. [Extract] [Full Text] [PDF]

Risk factor scoring for coronary heart disease

Hans-Werner Hense
BMJ 2003 327: 1238-1239. [Extract] [Full Text] [PDF]

This article has been cited by other articles:

• van der Heijden, A. A.W.A., Ortegon, M. M., Niessen, L. W., Nijpels, G., Dekker, J. M. (2009). 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 32: 2094-2098 [Abstract] [Full text]  
• Chia Yook Chin, , Pengal, S. (2009). Cardiovascular Disease Risk in a Semirural Community in Malaysia. Asia Pac J Public Health 21: 410-420 [Abstract]  
• Collins, G. S, Altman, D. G (2009). An independent external validation and evaluation of QRISK cardiovascular risk prediction: a prospective open cohort study. BMJ 339: b2584-b2584 [Abstract] [Full text]  
• Chow, C K, Joshi, R, Celermajer, D S, Patel, A, Neal, B C (2009). Recalibration of a Framingham risk equation for a rural population in India. J. Epidemiol. Community Health 63: 379-385 [Abstract] [Full text]  
• Prati, P., Tosetto, A., Vanuzzo, D., Bader, G., Casaroli, M., Canciani, L., Castellani, S., Touboul, P.-J. (2008). Carotid Intima Media Thickness and Plaques Can Predict the Occurrence of Ischemic Cerebrovascular Events. Stroke 39: 2470-2476 [Abstract] [Full text]  
• Christiaens, T. (2008). Cardiovascular risk tables. BMJ 0: bmj.a480v1-a480 [Full text]  
• Simmons, R. K., Sharp, S., Boekholdt, S. M., Sargeant, L. A., Khaw, K.-T., Wareham, N. J., Griffin, S. J. (2008). Evaluation of the Framingham Risk Score in the European Prospective Investigation of Cancer-Norfolk Cohort: Does Adding Glycated Hemoglobin Improve the Prediction of Coronary Heart Disease Events?. Arch Intern Med 168: 1209-1216 [Abstract] [Full text]  
• Krones, T., Keller, H., Sonnichsen, A., Sadowski, E.-M., Baum, E., Wegscheider, K., Rochon, J., Donner-Banzhoff, N. (2008). Absolute Cardiovascular Disease Risk and Shared Decision Making in Primary Care: A Randomized Controlled Trial. Ann Fam Med 6: 218-227 [Abstract] [Full text]  
• Bibbins-Domingo, K., Coxson, P., Pletcher, M. J., Lightwood, J., Goldman, L. (2007). Adolescent Overweight and Future Adult Coronary Heart Disease. NEJM 357: 2371-2379 [Abstract] [Full text]  
• Preston, R. A., Harvey, P., Herfert, O., Dykstra, G., Jukema, J. W., Sun, F., Gillen, D. (2007). A Randomized, Placebo-Controlled Trial to Evaluate the Efficacy, Safety, and Pharmacodynamic Interaction of Coadministered Amlodipine and Atorvastatin in 1660 Patients With Concomitant Hypertension and Dyslipidemia: The Respond Trial. J Clin Pharmacol 47: 1555-1569 [Abstract] [Full text]  
• May, M., Sterne, J. A C, Shipley, M., Brunner, E., d'Agostino, R., Whincup, P., Ben-Shlomo, Y., Carr, A., Ledergerber, B., Lundgren, J. D, Phillips, A. N, Massaro, J., Egger, M. (2007). A coronary heart disease risk model for predicting the effect of potent antiretroviral therapy in HIV-1 infected men. Int J Epidemiol 36: 1309-1318 [Abstract] [Full text]  
• Macleod, J., Metcalfe, C., Smith, G. D., Hart, C. (2007). Does consideration of either psychological or material disadvantage improve coronary risk prediction? Prospective observational study of Scottish men. J. Epidemiol. Community Health 61: 833-837 [Abstract] [Full text]  
• Sampalis, J. S, Bissonnette, S., Habib, R., Boukas, S., for the Ezetrol Add-On Investigators, (2007). Reduction in Estimated Risk for Coronary Artery Disease After Use of Ezetimibe with a Statin. The Annals of Pharmacotherapy 41: 1345-1351 [Abstract] [Full text]  
• Hippisley-Cox, J., Coupland, C., Vinogradova, Y., Robson, J., May, M., Brindle, P. (2007). Derivation and validation of QRISK, a new cardiovascular disease risk score for the United Kingdom: prospective open cohort study. BMJ 335: 136-136 [Abstract] [Full text]  
• Authors/Task Force Members, , Ryden, L., Standl, E., Bartnik, M., Berghe, G. V. d., Betteridge, J., de Boer, M.-J., Cosentino, F., Jonsson, B., Laakso, M., Malmberg, K., Priori, S., Ostergren, J., Tuomilehto, J., Thrainsdottir, I., Other Contributors, , Vanhorebeek, I., Stramba-Badiale, M., Lindgren, P., Qiao, Q., ESC Committee for Practice Guidelines (CPG), , Priori, S. G., Blanc, J.-J., Budaj, A., Camm, J., Dean, V., Deckers, J., Dickstein, K., Lekakis, J., McGregor, K., Metra, M., Morais, J., Osterspey, A., Tamargo, J., Zamorano, J. L., Document Reviewers, , Deckers, J. W., Bertrand, M., Charbonnel, B., Erdmann, E., Ferrannini, E., Flyvbjerg, A., Gohlke, H., Juanatey, J. R. G., Graham, I., Monteiro, P. F., Parhofer, K., Pyorala, K., Raz, I., Schernthaner, G., Volpe, M., Wood, D. (2007). Guidelines on diabetes, pre-diabetes, and cardiovascular diseases: full text: 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 Suppl 9: C3-C74 [Full text]  
• Asia Pacific Cohort Studies Collaboration, (2007). Cardiovascular risk prediction tools for populations in Asia. J. Epidemiol. Community Health 61: 115-121 [Abstract] [Full text]  
• Authors/Task Force Members, , Ryden, L., Standl, E., Bartnik, M., Van den Berghe, G., Betteridge, J., de Boer, M.-J., Cosentino, F., Jonsson, B., Laakso, M., Malmberg, K., Priori, S., Ostergren, J., Tuomilehto, J., Thrainsdottir, I., Other Contributors, , Vanhorebeek, I., Stramba-Badiale, M., Lindgren, P., Qiao, Q., ESC Committee for Practice Guidelines (CPG), , Priori, S. G., Blanc, J.-J., Budaj, A., Camm, J., Dean, V., Deckers, J., Dickstein, K., Lekakis, J., McGregor, K., Metra, M., Morais, J., Osterspey, A., Tamargo, J., Zamorano, J. L., Document Reviewers, , Deckers, J. W., Bertrand, M., Charbonnel, B., Erdmann, E., Ferrannini, E., Flyvbjerg, A., Gohlke, H., Juanatey, J. R. G., Graham, I., Monteiro, P. F., Parhofer, K., Pyorala, K., Raz, I., Schernthaner, G., Volpe, M., Wood, D. (2007). 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 28: 88-136 [Full text]  
• Marrugat, J., Subirana, I., Comin, E., Cabezas, C., Vila, J., Elosua, R., Nam, B.-H., Ramos, R., Sala, J., Solanas, P., Cordon, F., Gene-Badia, J., D'Agostino, R. B, for the VERIFICA (Validez de la Ecuacion de Riesgo, (2007). Validity of an adaptation of the Framingham cardiovascular risk function: the VERIFICA study. J. Epidemiol. Community Health 61: 40-47 [Abstract] [Full text]  
• Brindle, P, Beswick, A, Fahey, T, Ebrahim, S (2006). Accuracy and impact of risk assessment in the primary prevention of cardiovascular disease: a systematic review. Heart 92: 1752-1759 [Abstract] [Full text]  
• Jurgensen, J S (2006). The value of risk scores. Heart 92: 1713-1714 [Abstract] [Full text]  
• May, M, Lawlor, D A, Brindle, P, Patel, R, Ebrahim, S (2006). Cardiovascular disease risk assessment in older women: can we improve on Framingham? British Women's Heart and Health prospective cohort study. Heart 92: 1396-1401 [Abstract] [Full text]  
• Mcelduff, P, Jaefarnezhad, M, Durrington, P N (2006). American, British and European recommendations for statins in the primary prevention of cardiovascular disease applied to British men studied prospectively. Heart 92: 1213-1218 [Abstract] [Full text]  
• Madhok, V., Fahey, T. (2006). Cardiovascular risk estimation: important but may be inaccurate. BMJ 332: 1422-1422 [Full text]  
• Donnan, P. T., Donnelly, L., New, J. P., Morris, A. D. (2006). Derivation and Validation of a Prediction Score for Major Coronary Heart Disease Events in a U.K. Type 2 Diabetic Population.. Diabetes Care 29: 1231-1236 [Abstract] [Full text]  
• Thomas, C., Hypponen, E., Power, C. (2006). Type 2 diabetes mellitus in midlife estimated from the cambridge risk score and body mass index.. Arch Intern Med 166: 682-688 [Abstract] [Full text]  
• Tunstall-Pedoe, H, Woodward, M, for the SIGN group on risk estimation, (2006). By neglecting deprivation, cardiovascular risk scoring will exacerbate social gradients in disease. Heart 92: 307-310 [Abstract] [Full text]  
• Reilly, B. M., Evans, A. T. (2006). Translating Clinical Research into Clinical Practice: Impact of Using Prediction Rules To Make Decisions. ANN INTERN MED 144: 201-209 [Abstract] [Full text]  
• Daly, C. A, De Stavola, B., Sendon, J. L L., Tavazzi, L., Boersma, E., Clemens, F., Danchin, N., Delahaye, F., Gitt, A., Julian, D., Mulcahy, D., Ruzyllo, W., Thygesen, K., Verheugt, F., Fox, K. M, on behalf of the Euro Heart Survey Investigators, (2006). Predicting prognosis in stable angina--results from the Euro heart survey of stable angina: prospective observational study. BMJ 332: 262-267 [Abstract] [Full text]  
• Wannamethee, S. G., Shaper, A. G., Lennon, L., Morris, R. W. (2005). Metabolic Syndrome vs Framingham Risk Score for Prediction of Coronary Heart Disease, Stroke, and Type 2 Diabetes Mellitus. Arch Intern Med 165: 2644-2650 [Abstract] [Full text]  
• Prepared by: British Cardiac Society, British Hype, (2005). JBS 2: Joint British Societies' guidelines on prevention of cardiovascular disease in clinical practice. Heart 91: v1-v52 [Full text]  
• Smith, A., Patterson, C., Yarnell, J., Rumley, A., Ben-Shlomo, Y., Lowe, G. (2005). Which Hemostatic Markers Add to the Predictive Value of Conventional Risk Factors for Coronary Heart Disease and Ischemic Stroke?: The Caerphilly Study. Circulation 112: 3080-3087 [Abstract] [Full text]  
• Getz, L., Sigurdsson, J. A, Hetlevik, I., Kirkengen, A. L., Romundstad, S., Holmen, J. (2005). Estimating the high risk group for cardiovascular disease in the Norwegian HUNT 2 population according to the 2003 European guidelines: modelling study. BMJ 331: 551- [Abstract] [Full text]  
• Ferrario, M., Chiodini, P., Chambless, L. E, Cesana, G., Vanuzzo, D., Panico, S., Sega, R., Pilotto, L., Palmieri, L., Giampaoli, S., for the CURORE Project Research Group, (2005). Prediction of coronary events in a low incidence population. Assessing accuracy of the CUORE Cohort Study prediction equation. Int J Epidemiol 34: 413-421 [Abstract] [Full text]  
• Walker, M., Whincup, P., Shaper, A. (2004). The British Regional Heart Study 1975-2004. Int J Epidemiol 33: 1185-1192 [Full text]  
• Anand, S. S., Razak, F., Yi, Q., Davis, B., Jacobs, R., Vuksan, V., Lonn, E., Teo, K., McQueen, M., Yusuf, S. (2004). C-Reactive Protein as a Screening Test for Cardiovascular Risk in a Multiethnic Population. Arterioscler. Thromb. Vasc. Bio. 24: 1509-1515 [Abstract] [Full text]  
• Ridker, P. M, Wilson, P. W.F., Grundy, S. M. (2004). Should C-Reactive Protein Be Added to Metabolic Syndrome and to Assessment of Global Cardiovascular Risk?. Circulation 109: 2818-2825 [Abstract] [Full text]  
• Brindle, P. M, Holt, T. A (2004). Cardiovascular risk assessment--time to look beyond cohort studies. Int J Epidemiol 33: 614-615 [Full text]  
• Hense, H.-W. (2004). Observations, predictions and decisions--assessing cardiovascular risk assessment. Int J Epidemiol 33: 235-239 [Full text]  
• Emberson, J., Whincup, P., Morris, R., Walker, M., Ebrahim, S. (2004). Evaluating the impact of population and high-risk strategies for the primary prevention of cardiovascular disease. Eur Heart J 25: 484-491 [Abstract] [Full text]  
• Hense, H.-W. (2003). Risk factor scoring for coronary heart disease. BMJ 327: 1238-1239 [Full text]  

Rapid Responses:

Read all Rapid Responses

Maybe the equation is wrong

GH Hall
bmj.com, 29 Nov 2003 [Full text]

Prediction of Coronary risk

Undurti N Das, et al.
bmj.com, 29 Nov 2003 [Full text]

When were you born?

Tom H Hughes-Davies
bmj.com, 1 Dec 2003 [Full text]

Prior assumptions and coronary risk: efficient use of coronary risk scores

John Robson
bmj.com, 10 Dec 2003 [Full text]

After Framingham: does the new SCORE inflate treatment thresholds?

John Robson
bmj.com, 11 Dec 2003 [Full text]

Risk prediction based on the Framingham equation is still the best available for the UK population

Iftikhar U Haq, et al.
bmj.com, 24 Dec 2003 [Full text]

Most first MI are not detected using the UK high risk definition !

Benoit J Boland, et al.
bmj.com, 31 Dec 2003 [Full text]

Re: Most first MI are not detected using the UK high risk definition !

L S Lewis
bmj.com, 1 Jan 2004 [Full text]

Re: Most first MI are not detected ...

Benoit J Boland
bmj.com, 2 Jan 2004 [Full text]

Re: Re: Most first MI are not detected ...

L S Lewis
bmj.com, 3 Jan 2004 [Full text]

PS: Re: Re: Most first MI are not detected ...

L S Lewis
bmj.com, 3 Jan 2004 [Full text]

Lifestyle differences

Neal Pinckcney
bmj.com, 9 Jan 2004 [Full text]

Re: Is a reduced cost effectiveness analysis an appropriate means to evaluate the value of prevention

Geert Goderis, et al.
bmj.com, 16 Jan 2004 [Full text]

The accuracy of the Framingham coronary risk score: Authors response

Peter M Brindle, et al.
bmj.com, 23 Jan 2004 [Full text]

Online poll

Find out more >>