Keywords
INTRODUCTION
Coronary heart disease is one of the main public health problems in Navarra, Spain.1-3 Acute myocardial infarction (AMI) is the second leading cause of death in men and the third in women. One quarter of all deaths before patients reach hospital care occur during the first 28 days after onset of symptoms.3
Some of these deaths could be avoided with effective primary prevention to improve the detection and appropriate management of risk factors for coronary heart disease. It is necessary to promote the primary prevention of cardiovascular disease, balancing activities dealing with prevention with those involving the care of persons who already have coronary heart disease.4
Arteriosclerosis, the main etiopathological cause of ischemic heart disease, is a multiple factor entity. As far as is known, no particular factor is required for its development, but rather it depends on the coexistence and severity of different component factors and the synergistic or antagonistic effect of each factor. Its preventive approach should therefore be multi-factorial as well.5 Evaluation of the risk by means of multiple risk factor models predicts the overall individual risk more precisely and enables primary prevention priorities to be established, adjusting the intensity of the intervention aimed at avoiding the onset of a first cardiovascular episode in asymptomatic but vulnerable persons.
Cardiovascular risk equations are the best tool to establish priorities in primary prevention. These equations estimate the excess risk that a person has of experiencing an event over a certain period of time, usually 5 or 10 years, in relation to the average risk of the population to which that individual belongs. Several different equations or scales exist to calculate the coronary risk, all based on the findings of the North American Framingham cohort. Various epidemiological studies have identified that the use of these equations in Anglo-Saxon populations provides an adequate estimate of the future risk of an event, but their use in low-risk countries such as Spain systematically overestimates this risk.6-10
The most used risk tables in Spain are REGICOR (REgistre GIroní del COR)6,7 and SCORE (Systematic Coronary Risk Evaluation).11 The REGICOR equation has proven to have a good prediction capacity for coronary events in Spanish persons aged 35-74 years—Validación de la Ecuación de Riesgo Individual de Framingham de Incidente Coronario Adaptada (Validation of the Framingham individual risk equation for coronary events Adapted) (VERIFICA)—.12 The SCORE equation, in its version adapted for use in low-risk countries, for the calculation of the risk of cardiovascular death in persons aged 40 to 65 years, has recently been adapted to Spain.13
The estimation of the coronary risk should be based on the follow-up of large cross-sectional cohorts. Navarra currently has a population cohort, though the follow-up period is still not long enough to provide risk estimates according to age and sex that possess the required precision. This, therefore, demands that we use charts that have been generated in other populations or else adapt these charts. The aim of this study was to adapt the Framingham-Wilson equation by calibrating it using the rates of coronary events and the prevalence of cardiovascular risk factors found in Navarra.
METHODS
The estimation of the coronary risk was based on the original equation of the Framingham study in the version published by Wilson et al14 in 1998. This equation includes high-density lipoprotein cholesterol (HDL-C), and estimates the 10-year risk of having a myocardial infarction, whether fatal or not, symptomatic or silent, and angina.
The method used to adapt the Framingham equation is known and has been evaluated in our setting.6,7,12 The calibration was done by substituting the comparison elements of the Framingham population with those of the Navarra population. Estimates are available of the prevalence of cardiovascular risk factors and the rates of major coronary events (fatal or non-fatal symptomatic AMI) of Navarra. Additionally, the original coefficients of the Framingham-Wilson equation were used.14 The calculation of the calibrated equation is described in the appendix.
Adaptation Process
The population data concerning cardiovascular risk factors were obtained from the Riesgo Vascular en Navarra (Vascular risk in Navarra) (RIVANA) study, for the population aged 35 to 74 years in 2003.15,16 The sampling strategy recruited 5197 persons. The final rate of participation was 74.6%. The variables studied were sex, age, total cholesterol, HDL-C, systolic blood pressure (SBP), diastolic blood pressure (DBP), smoking, and a diagnosis of diabetes mellitus. The prevalence of the various risk factors was calculated for each group according to age and sex, using the definitions and cut-off points of the Framingham-Wilson cohort.14
The blood pressure was measured 3 times, with an interval of at least 5 min between each measurement. At the first measurement the blood pressure was measured in both arms, and the value for the arm showing the highest SBP or DBP was used. The measurement was made with an automatic blood pressure monitor (OMRON® M4-1).
Laboratory Measurements
All the analyses were centralized at the laboratory of the Hospital de Navarra (Pamplona). All the analytical procedures were calibrated and standardized in order to guarantee the quality of the biochemical determinations. Internal and external controls were made systematically. The internal quality control consisted of a daily control and weekly calibration. The internal controls were made with Precinorm U and Precipath U for the measurements of total cholesterol and glucose, and Precipath lipids for the HDL-C (Roche Diagnostics). Concurrent external quality controls were made with Unity (BioRad Laboratories). The total cholesterol was measured with the CHOD-PAP enzymatic-colorimetric method and the HDL-C with the second generation direct HDL plus method (without pretreatment). The glucose was measured by the hexokinase method.
The study used the data from the Navarra population registry of AMI, which records all patients with an AMI, both fatal and non-fatal. The registry covers the years 1997-1998 and 2003-2004.3,17 A simple weighting of the observed rate was made for each point in the series (1997, 1998, 2003, and 2004); each year had an equal contribution (weighting K =2.5) to the estimated rate of coronary events at 10 years.
The calculation of the rates included all cases of myocardial infarction in Navarra, classified according to the algorithm of the MONICA project (MONItoring of trends and determinants in CArdiovascular diseases).18 Each case studied was classified as: definite AMI, fatal or not; possible AMI, or AMI with insufficient data. The 4 categories compose definition 1 of the MONICA study, which is that used to calculate the rate. Given that the Wilson equation, besides symptomatic AMI, also includes cases of angina and silent AMI, data that are not known in Navarra, the proportion was assumed to be similar to that of Framingham. The following ratio was used for the estimate:
Ho(t)/FramAll/Ho(t)/FramMajor
where t is the follow-up time, in our case 10 years; Ho(t)/FramAll, the rate of coronary events including angina and silent myocardial infarction in Framingham, and Ho(t)/FramMajor, the rate of fatal or non-fatal symptomatic infarction. The value of this quotient was 1.4 for men and 1.91 for women.7 Thus, as the rate of major events in Navarra in men according to the registry was 3.6%, this was multiplied by 1.4 to obtain the estimated rate of all coronary events (5.1%). This, in turn, enabled us to calculate the population rate free of coronary events at 10 years: 100%-5.1%=94.9%. For women, the rate of major events was 0.9%, which multiplied by 1.91 gives an estimated rate of all coronary events of 1.8%. The female population rate free of events was therefore 100%-1.8%=98.2%.
Charts were constructed to show the absolute risks, calculated with the adapted equation, rounded to the next nearest whole figure, for each box of the combination of the risk factor categories. The absolute risks were calculated for an HDL-C concentration of 35-59 mg/dL. The risk was classified in 5 levels: low ( <5 mild 5 -9 moderate 10 -19 high 20 -39 and very 39%). A color code was used for the intensity of the risk for the various risk factor combinations, for men and women, diabetic and non-diabetic, individually.
RESULTS
Table 1 shows the frequency distribution by sex of the risk factors of the population of Navarra, as well as the values for the Framingham population.
Comparison of the 2 distributions shows that they differ in several categories in a few factors, in both men and women. The most relevant finding here was the high concentration of HDL-C in the population of Navarra. The HDL-C had a mean population value of 63.9 mg/dL (95% confidence interval [CI], 63.4-64.4); 56.7 mg/dL (95% CI, 56.1-57.3) in men and 70.1 mg/dL (95% CI, 69.4-70.8) in women. Likewise, the prevalence of smoking was much lower in Navarra, in both men and women. The data for hypertension, however, showed a higher prevalence in the Navarra men but not the women.
Concerning the incidence rate of coronary events, the rate in both sexes was significantly lower in Navarra (Table 1).
Figure 1 shows the risk table for AMI, fatal or non-fatal, with or without symptoms, and angina for men, with different combinations of risk factors. Figure 2 shows the same for the diabetic men. Figure 3 shows the risk table for women and Figure 4 for the diabetic women.
Figure 1. Risk of myocardial infarction, fatal or non-fatal, with or without symptoms, or angina in non-diabetic men with high-density lipoprotein cholesterol (HDL-C) concentrations of 35-59 mg/dL.
Figure 2. Risk of myocardial infarction, fatal or non-fatal, with or without symptoms, or angina in diabetic men with HDL-C concentrations of 35-59 mg/dL.
Figure 3. Risk of myocardial infarction, fatal or non-fatal, with or without symptoms, or angina in non-diabetic women in non-diabetic women with HDL-C of 35-59 mg/dL.
Figure 4. Risk of myocardial infarction, fatal or non-fatal, with or without symptoms, or angina in diabetic women with HDL-C concentrations of 35-59 mg/dL.
The proportion of combinations of risk factors determining a high or very high risk of coronary heart disease (≥20% risk at 10 years) in the whole set of calibrated tables was 3.3 times lower in Navarra than in the original tables for the Framingham population (Table 2). The proportion of combinations of factors leading to a moderate to very high risk was 1.82 times lower (Table 2). At this level of risk, the reduction was very notable in the non-diabetic women.
The tables show the corresponding likelihood at the various different combinations of risk factors, for an HDL-C concentration of 35-59 mg/dL. The risk, calculated using the adapted Framingham-Navarra equation (RICORNA) corresponding to HDL-C values <35 mg dl was approximately 50 greater than that seen in the tables and for an hdl-c concentration of 60 lower those persons with concentrations between 35 59 had risk indicated by box combination factors though nearer were slightly higher about 3 percentage points again this correction is proposed order to simplify use fact including effect estimate our setting definitely important as 73 women 36 men aged 74 years navarra level 8805 p
DISCUSSION
We present proposed tables for overall 10-year coronary risk for use in the population of Navarra, based on the Framingham-Wilson equation, calibrated according to the prevalence of risk factors and rate of events recorded for Navarra.
Generally speaking, the risk calculated from the RICORNA (Framingham-Navarra) equation for the various combinations of risk factors is significantly lower than in the original Framingham study. The proportion of coronary risk estimations that were moderate to very high was 1.82 times lower in the adapted tables than in the original tables.
Several different epidemiological studies have shown that mathematical functions based on the original data of the Framingham cohort overestimate the absolute coronary risk in populations with a low incidence of coronary disease and associated mortality rate.6-10 Navarra is among the regions of the developed world with the lowest mortality rates, both for overall mortality due to cardiovascular disease and for mortality due to coronary heart disease, as well as for cerebrovascular disease.1-3,19,20 The results of our study are in accordance with these data and corroborate the starting hypothesis that the coronary risk is overestimated in our population.
The guidelines of the national and international scientific societies are aimed at promoting the adaptation of the recommendations concerning cardiovascular prevention to the particular characteristics and circumstances of the end-user population.21,22 In accordance with these recommendations, various Spanish research groups over recent years have undertaken notable efforts to obtain precise, reliable prediction models, adapted to the characteristics of the Spanish population. For instance, the 1998 version of the Framingham equation has been calibrated according to the data for the population of Gerona, and the REGICOR equation obtained. With the same method as that used for the REGICOR study, but based on a different population, the DORICA (Dislipemia, Obesidad y Riesgo Cardiovascular-Dyslipidemia, Obesity, and Cardiovascular Risk) tables were obtained.23 Finally, the European SCORE project, in which Spain participated with 3 cohorts, gave rise to the SCORE scale in its version adapted to low-risk countries to calculate the risk of cardiovascular death in persons aged 40 to 65 years. The low-risk SCORE model has been calibrated for Spain.13
The researchers involved in the REGICOR study recently analyzed the validity of the equation calibrated from the VERIFICA study.12 The VERIFICA study (Validación de la Ecuación de Riesgo Individual de Framingham de Incidente Coronario Adaptada) has proved to have a good 5-year predictive capacity of coronary events for the Spanish population aged between 35 and 74 years, both in men and women, and also in diabetic patients. This is the first, and only, risk equation validated for the Spanish population.
At the present time, the REGICOR and SCORE tables are the most used in general practice for the stratification of cardiovascular risk in our health care setting.
Ideally, the estimation of coronary risk in Navarra should be based on the follow-up of a cohort of our population, with a sufficient sample size to estimate the probabilities precisely. Additionally, it should include those persons aged up to 74 years, and more especially the estimation of coronary risk in women, whose life expectancy is greater. Currently, Navarra has a population cohort of 4168 persons aged between 35 and 84 years, though the follow-up period is still short (4 years). This therefore explains the need for the time being to use equations generated in other populations or else to adapt these equations.
Spain is a country with a wide geographic variability in the pattern of the incidence and mortality from coronary heart disease,24-26 as well as marked geographic differences in the burden and distribution of risk factors that could contribute to the explanation of these differences.27,28 In this study we characterized a representative sample of the population of Navarra with an HDL-C concentration of 63.9 mg/dL (56.7 mg/dL in men and 70.1 mg/dL in women). These figures are higher than those of other regions in our setting, especially those found for women.27,28 Numerous studies have shown that HDL is one of the most important independent protectors against the arteriosclerosis that underlies coronary heart disease.29-31 The high concentration of HDL-C found in the population of Navarra may well contribute to the low coronary morbidity and mortality.
Comparison of the risk tables adapted for Navarra with those of REGICOR7 shows that the risk of a coronary event is slightly higher in the population of Navarra, reflecting the different pattern of prevalence of risk factors included in the model, in spite of the fact that the 2 populations have similar rates of heart disease. In this context, it seems justified to have risk tables adjusted to the particular characteristics of our population. The present study was designed to respond to this need using a well-established method.
The study reported here has certain limitations that should be taken into account. One limitation is that the tables shown have not been validated in a prospective, population-based study. Nevertheless, the method used to adapt the tables has been used before and has a reasonable guarantee of validity.
Population data are not available that would enable us to confirm that the proportion of silent AMI and angina with respect to the total number of coronary events in Navarra is similar to that found in the Framingham study. This option, chosen as a measure of safety, endows the tables with a conservative character, as is it very unlikely that the true values in Navarra are greater than those of the American city.
Finally, the cardiovascular risk equations, despite their limitations, are the best screening tool that we currently have for the selection of patients in whom to apply the various different primary prevention strategies, as well as to determine their intensity. Any equation nowadays is far from being an ideal tool, and it should simply be considered as useful in primary prevention and is no substitute for the correct clinical judgment, and any specific conditions must be taken into account when the tool is applied.
CONCLUSIONS
We believe that the tables proposed here may be useful instruments for the more precise estimation of the overall coronary risk of the population of Navarra. The RICORNA equation answers the need for tables to calculate the coronary risk adapted to the characteristics of the population of Navarra.
Use of the original Framingham equation should be avoided as it overestimates excessively the true risk of coronary heart disease in the population of Navarra.
The population-based cohort in the RIVANA Study could provide information that will soon enable the RICORNA equation to be validated.
ABBREVIATIONS
AMI: acute myocardial infarction
HDL-C: high-density lipoprotein cholesterol
REGICOR: Registre Gironí del Cor (Gerona Heart Registry)
RICORNA: Riesgo Coronario Navarra (Navarra Coronary Risk)
SCORE: Systematic Coronary Risk Evaluation
VERIFICA: Validación de la Ecuación de Riesgo Individual de Framingham de Incidente Coronario Adaptada (Validation of the Framingham individual risk equation for coronary events - Adapted)
Correspondence: Dr. P. González Diego.
Servicio de Medicina Preventiva y Gestión de Calidad. Santa Soria, 22. 31200 Estella. Navarra. España.
E-mail: paulino.gonzalez.diego@cfnavarra.es
Received February 6, 2009.
Accepted for publication May 11, 2009.