Services on Demand
- Cited by SciELO
- Access statistics
- Similars in SciELO
On-line version ISSN 1680-5348Print version ISSN 1020-4989
Rev Panam Salud Publica vol.32 n.2 Washington Aug. 2012
REVIEW ARTÍCULO DE REVISIÓN
Validez de los modelos de predicción del riesgo de enfermedades cardiovasculares en América Latina y en la población hispana en los Estados Unidos de América: una revisión sistemática
Mery Cortes-BergoderiI; Randal J. ThomasI; Felipe N. AlbuquerqueI; John A. BatsisII; Gerard BurdiatIII; Carmen Perez-TerzicIV; Jorge Trejo-GutierrezV; Francisco Lopez-JimenezI,*
IDivision of Cardiovascular Diseases, Mayo Clinic, Rochester, Minnesota, United States of America
IISection of General Internal Medicine, Dartmouth- Hitchcock Medical Center, Lebanon, New Hampshire, and Dartmouth Medical School, Hanover, New Hampshire, United States of America
IIICentro Calidad de Vida, Asociación Española, Montevideo, Uruguay
IVDivision of Physical Medicine and Rehabilitation, Mayo Clinic, Rochester, Minnesota, United States of America
VDivision of Cardiovascular Diseases, Mayo Clinic, Jacksonville, Florida, United States of America.
OBJECTIVE: To assess the use and validity of prediction models to estimate the risk of cardiovascular disease (CVD) in Latin America and among Hispanic populations in the United States of America.
METHODS: This was a systematic review of three databases: Ovid MEDLINE (1 January 1950-15 April 2010), LILACS (1 January 1988-15 April 2010), and EMBASE (1 January 1988-15 April 2010). MeSH search terms and domains were related to CVD, prediction rules, Latin America (including the Caribbean), and Hispanics in the United States. Database searches were supplemented by correspondence with experts in the field.
RESULTS: A total of 1 655 abstracts were identified, of which five cohorts with a total of 13 142 subjects met inclusion criteria. A Mexican cohort showed that the predicted/observed event-rate ratio for coronary heart disease (CHD) according to the Framingham risk score (FRS) was 1.68 (95% CI, 1.26-2.11); incident myocardial infarction, 1.36 (95% CI, 0.90-1.83); and CHD death, 1.21 (95% CI, 0.43-2.00). In Ecuador, a prediction model for CVD and total deaths in hypertensive patients had an area under the curve (AUC) of 0.79 (95% CI, 0.72-0.86), while the World Health Organization method had an AUC of 0.74 (95% CI, 0.67-0.82). A study predicting mortality risk in people with Chagas' disease had an AUC of 0.81 (95% CI, 0.72-0.90). Among a United States cohort that included Hispanics, FRS overestimated CVD risk for Hispanics with an AUC of 0.69. Another study in the United States that assessed FRS factors predicting CVD death among Mexican-Americans had an AUC of 0.78.
CONCLUSIONS: The evidence regarding CVD risk prediction rules in Latin America or among Hispanics in the United States is modest at best. It is likely that the FRS overestimates CVD risk in Hispanics when not properly recalibrated.
Key words: Cardiovascular diseases; risk factors; Hispanic Americans; Latin America.
OBJETIVO: Evaluar el uso y la validez de los modelos de predicción para calcular el riesgo de padecer enfermedades cardiovasculares en América Latina y en poblaciones hispanas en los Estados Unidos de América.
MÉTODOS: Se llevó a cabo una revisión sistemática de tres bases de datos: Ovid MEDLINE (1 de enero de 1950 al 15 de abril del 2010), LILACS (1 de enero de 1988 al 15 de abril del 2010) y Embase (1 de enero de 1988 al 15 de abril del 2010). Los términos de búsqueda MeSH y los dominios se relacionaron con las enfermedades cardiovasculares, las reglas de predicción, América Latina (que incluye el Caribe) y los hispanos en los Estados Unidos. Las búsquedas en las bases de datos se complementaron con la opinión de expertos en el tema.
RESULTADOS: Se identificaron 1 655 resúmenes, de los cuales reunieron los criterios de inclusión cinco cohortes con un total de 13 142 sujetos. En una cohorte mexicana la razón entre las tasas de sucesos previstos y observados para la cardiopatía coronaria según la escala de valoración del riesgo de Framingham (FRS) fue 1,68 (IC de 95%, 1,26-2,11); para el infarto de miocardio nuevo, 1,36 (IC de 95%, 0,90-1,83); y para la muerte por cardiopatía coronaria, 1,21 (IC de 95%, 0,43-2,00). En el Ecuador, un modelo de predicción de defunción por enfermedades cardiovasculares y total en los pacientes hipertensos presentó un área bajo la curva (AUC) de 0,79 (IC de 95%, 0,72-0,86), mientras que el método de la Organización Mundial de la Salud mostró un AUC de 0,74 (IC de 95%, 0,67-0,82). Un estudio enfocado a predecir el riesgo de mortalidad en las personas con enfermedad de Chagas reveló un AUC de 0,81 (IC de 95%, 0,72-0,90). En una cohorte de los Estados Unidos que incluía población hispana, la FRS sobrestimó el riesgo de sufrir enfermedades cardiovasculares para los hispanos con un AUC de 0,69. Otro estudio realizado en los Estados Unidos en el que se evaluó los factores de la FRS que predecían la muerte debida a enfermedades cardiovasculares en estadounidenses de origen mexicano reveló un AUC de 0,78.
CONCLUSIONES: Los datos relacionados con las reglas de predicción del riesgo de sufrir enfermedades cardiovasculares en América Latina o en la población hispana en los Estados Unidos son, en el mejor de los casos, limitados. Es probable que la FRS sobrestime el riesgo de sufrir enfermedades cardiovasculares en la población hispana cuando no se la recalibra de manera adecuada.
Palabras clave: Enfermedades cardiovasculares; factores de riesgo; hispanoamericanos; América Latina.
In 2010, Latin America, including the Caribbean, had a combined population of approximately 600 million people; while another 40 million Hispanics constituted the largest minority (16%) in the United States (1).
According to the World Health Organization (WHO), about 25% of all annual deaths in Latin America are due to cardiovascular diseases (CVD) (2, 3). Cardiovascular risk factors, including obesity, hypertension, hypercholesterolemia, diabetes mellitus, and tobacco use are highly prevalent in Latin America and contribute to three-fourths of its CVD cases (4). The prevalence of most, if not all, of these factors has been steadily increasing in recent years in Latin America, and the trend is expected to continue (3).
Data regarding CVD burden and trends among Hispanics living in the United States is also alarming and represents the most likely cause of death among this population (5), about 31% of all deaths (6). The prevalence of heart disease is 8.1% in Hispanics and 12.1% in Caucasians (7) and the prevalence of obesity (8), diabetes mellitus, hypertension, and dyslipidemia, is generally higher among Hispanics than Caucasians (7, 9).
Estimation of CVD risk using prediction models is considered of high importance to public health since it can aid clinical decision-making, guide therapy, and make interventions more cost effective. It may also help direct public policy when measuring risk trends at the population level (10). In the last few decades, several cardiovascular risk prediction models have been created and introduced worldwide.
The Framingham risk score (FRS) was the first of such tools and is arguably the most commonly used model for calculating 10-year risk for CVD events in the world. The FRS has been validated and recalibrated in several different populations, including Australia, China, Japan, New Zealand, Spain, and the United States (11-14). These studies have shown that the FRS may overestimate CVD risk in some populations and underestimate it in others. Some other prediction models include the Prospective Cardiovascular Munster Heart Study (PROCAM) (15), the Reynolds score (16), and the Systematic Coronary Risk Evaluation system (SCORE) (17).
The aim of this study was to assess the use and validity of CVD risk prediction models in Latin America and the Caribbean and among Hispanic populations in the United States through a systematic review of the literature from 1950-2010.
MATERIALS AND METHODS
Selection criteria and search strategies
A systematic review of the literature was undertaken. The predefined inclusion criteria for the analysis were two: the study was carried out in one or more countries in Latin America or the Caribbean or among a Hispanic population in the United States; and the study involved the creation or validation of a cardiovascular risk prediction model.
Three databases were searched: Ovid MEDLINE® (Ovid Technologies, Inc., New York City, United States); LILACS (Latin American and Caribbean Center on Health Sciences Information, São Paulo, Brazil); and EmbaseTM (Elsevier, B.V., Amsterdam, The Netherlands). Ovid MEDLINE was searched from 1 January 1950-15 April 2010; and both the LILACS and Embase databases were searched from 1 January 1988-15 April 2010.
To identify studies that evaluate prediction models and Latin America or the Caribbean, the search employed MeSH® terms (National Library of Medicine, Washington, DC, United States) for the following domains and their combinations using the commands "ana" and "or": (1) Cardiovascular (cardiovascular diseases or myocardial infarction or coronary heart disease or coronary artery disease or angina or atherosclerosis); and (2) Prediction rule (Framingham score or PROCAM or ASSIGN or QRISK1 or QRISK2 or SCORE or Reynolds Score or calibration or validation or risk score or prediction rule); and (3) Latin America or South America or Central America or Caribbean or Caribe or a Country Name (i.e., Argentina, Belize, Bolivia, Brazil, Chile, Colombia, Costa Rica, Cuba, Dominica, Dominican Republic, Ecuador, El Salvador, Falkland Islands, French Guiana, Guadeloupe, Guatemala, Guyana, Haiti, Honduras, Martinique, Mexico, Nicaragua, Panama, Paraguay, Peru, Puerto Rico, Saint Bartholomey, Saint Lucia, Saint Martin, Suriname, Uruguay, or Venezuela).
To identify studies that evaluate prediction models among Hispanic populations in the United States, the search criteria were applied to the same three databases for the identical time period using the following: (1) Cardiovascular (cardiovascular disease or myocardial infarction or coronary heart disease or coronary artery disease or angina or atherosclerosis), and (2) the MeSH term "Hispanic Americans," as well as Hispanic ethnicity words (Latino or Hispanic or Mexican American or Puerto Rican American or Dominican American or Cuban American), and (3) Prediction rules (Framingham risk score or PROCAM or Reynolds score).
In addition, to minimize publication bias, cross-references were sought and 17 global experts in epidemiology and CVD prediction rules were consulted via email to identify any unpublished studies.
Two reviewers, MCB and FA, then independently screened the studies based on the information included in the titles and abstracts, and excluded those that were unrelated to the primary aim of the project. Agreement between reviewers was assessed using chance-adjusted kappa statistics. Disagreements were resolved by discussion and consensus. Studies considered as publications that would likely meet all the criteria were read in full by two of the researchers to determine final eligibility.
The following predefined variables of interest measured the prognostic performance and were used to compare prediction rules: area under the receiver operating characteristic curve (AUC), ratio of predicted/observed event rates, sensitivity and specificity, and diagnostic accuracy. To assess the methodological quality of the studies included, key components were evaluated that correlate with internal and external validity of studies assessing risk scores. These components included sample characteristics, generalizability, and length of follow up, ascertainment and validation of a new risk score in a subset of the sample, and use of standard statistics to report prognostic performances like C-statistics or AUC. There was no attempt in this study to create a quality score.
The search strategy and number of studies identified in each step are displayed in Figure 1. In all, five studies were identified as validating a cardiovascular risk prediction model: three cohort studies in Latin America/the Caribbean and two among Hispanic populations in United States (Annex 1). The total number of participants in the identified cohorts was 13 142, ranging from 424-8 713 individuals in each. The age range of the subjects was 18-64 years. There was significant heterogeneity in the way the validity of risk scores was reported. General characteristics of the selected studies are shown in Annex 1.
Jimenez-Corona and colleagues (18) assessed the applicability of the FRS equations to calculate total coronary heart disease (CHD), incident myocardial infarction, and CHD death in a Mexican population using different formulas from the Framingham study. They observed that the FRS overestimated the risk when comparing observed to predicted incidence. The number of total CHD events using the formula suggested by Wilson and colleagues (19) for both sexes was 58 observed cases versus 98 predicted, with a ratio of predicted/ observed of 1.68 (95% CI, 1.26-2.11). For incident myocardial infarction using the formula presented by Anderson and colleagues (20), there was also an overestimation of events, with 34 observed cases versus 46 predicted and a ratio predicted/observed of 1.36 (95% CI, 0.90-1.83). For CHD deaths, using the formula suggested by Anderson and colleagues (20), the number of observed cases was 9 versus 11 predicted, and the ratio of predicted/observed was 1.21 (95% CI, 0.43-2.00). These authors did not report AUC for the models.
Montalvo and colleagues (21) validated a new prediction model for CVD events and total deaths in patients with hypertension in a poor, rural area of Ecuador. The study assessed the predictive power of a risk stratification method based on "essential" methods, described as procedures that were affordable, applicable, and reliable even in the less economically-developed areas of the world. The model included measurement of blood pressure, fasting blood glucose, urinalysis, smoking status, and associated clinical conditions. It was compared in the same population to the method proposed by the 1999 WHO/International Society of Hypertension (ISH) guidelines (22). There was a highly-significant association between the level of predicted risk and the incidence of cardiovascular events and total deaths, with up to three-quarters of all deaths reported among people classified as "high" or "very high" risk with either method. The specificity of the "essential" method was close to that of the WHO/ ISH criteria, presenting an AUC of 0.79 (95% CI, 0.72-0.86) versus 0.74 (95% CI, 0.67-0.82), respectively. As the majority of study participants were of African descent (85%), this study probably does not represent the majority of the Latin American population. Another limitation was that the risk stratification did not provide a quantitative risk estimate (absolute risk), limiting its clinical value.
Rassi and colleagues (23) conducted a long-term, follow-up study of a large group of well-characterized patients with Chagas' disease and cardiac involvement in order to develop a predictive model for risk of death. A combination of clinical factors were used including New York Heart Association class III or IV, presence of cardiomegaly on chest radiography, segmental or global wall motion abnormality on echocardiography, non-sustained ventricular tachycardia on 24-hour Holter monitor-ing, low QRS voltage on electrocardiography, and male sex. To calculate a risk score, each of the six prognostic variables were assigned a number of points that was proportionate to its regression coefficient. The mean follow-up was 7.9 years. The validation cohort consisted of patients with Chagas' disease treated in another institution, with characteristics similar to those of the development cohort. The AUC for the derivation cohort was 0.84 (95% CI, 0.79-0.89), and for the validation cohort, 0.81 (95% CI, 0.72-0.90). The difference in the probability of death between the high-risk and the lower-risk groups was 0.53% at 5 years and 0.76% at 10 years.
For the Hispanic populations in the United States, two articles assessed the FRS and FRS factors among Mexican-Americans and Puerto Ricans. D'Agostino and colleagues (24) tested the validity and transportability of the Framingham CHD prediction functions in a multiethnic group, including the Puerto Rico Heart Health Program cohort. Per their observations, the FRS systematically overestimated CHD risk among Hispanics. The diagnostic performance was fair, with an AUC of 0.69.
Hurley and colleagues (5) assessed the ability of Framingham risk factors to predict cardiovascular death in Caucasians compared to Mexican-Americans and African-Americans. The risk factors identified were sex, age, smoking, diabetes, total cholesterol (without categorization), HDL cholesterol, and systolic blood pressure (treated or not). The association between age and CVD mortality for Mexican-Americans was not as strong as in Caucasians; that is, the hazard ratio (HR) was 2.46 (95% CI, 1.95-3.11) versus 3.37 (95% CI, 2.80-4.05), respectively. The AUC for CVD death was 0.78 for Mexican-Americans. It was observed that the predicted/observed mortality rate was higher for Mexican-Americans than for non-Hispanics Caucasians. The calibration goodness-of-fit x2 statistics for CVD mortality for Mexican-Americans indicated adequate fit for racial/ethnic group when the model was developed separately for each racial/ ethnic group.
This study identified five studies that assessed cardiovascular risk prediction models in cohorts from Latin America or Hispanic populations in the United States (5, 18, 21, 23, 24). Overall, evidence supporting the validity of CV prediction rules among these populations is scare.
The limited number of studies and the heterogeneity of the manner in which results were reported did not allow for a meta-analysis. Nonetheless, the results of this systematic review provide important insights and information useful to public policy and CVD prevention in Latin America and among Hispanics. This study may help to fill the gaps considering the lack of evidence and resources for developing a predictor model designed for this population group, which is at-risk and does not share the same characteristics as the populations that validated the models currently in use.
Estimation of CVD risk and interventions on the modifiable risk factors could be of high impact to CVD morbidity and mortality, as well as to each country's economics. First, risk prediction models, including the FRS, could help stratify cardiovascular risk events among Hispanics, but the models need to be recalibrated to the level of underlying cardiovascular risk observed in this population, which is generally lower than that from which the Framingham was derived. It has been shown that among young individuals with multiple CVD risk factors, the 10-year risk may be low, but the long-term risk may be high (24). This has been seen in Latin American countries whose populations are younger than the populations used to validate FRS, and is probably a reason for the observed CVD risk underestimation (24).
In the two studies assessing FRS prognostic performance (18, 24), the predicted number of events among Hispanics was almost double the number of actual events that occurred in those cohorts. After recalibration, the diagnostic performance of the FRS improved significantly. Of note, the FRS applicability among Puerto Ricans yielded a modest AUC, suggesting that the diagnostic performance of the FRS might still be inferior among Hispanics versus Caucasians, even after recalibration. These results are consistent with other studies that have tried to implement the FRS in populations other than the one in which it was derived (13, 25-27). In China, Liu and colleagues (14) compared the performance of the FRS to that of a local risk-prediction equation derived from a local cohort. The FRS systematically overestimated the event rates, but after recalibration for this specific population's underlying cardiovascular risk, its prognostic capabilities improved.
Principally, the FRS commonly needs recalibration because the risk prediction score used to calculate absolute risk is strongly influenced by the populationspecific risk. Since it would be impractical to have a risk prediction rule developed for each country in the world, it seems most feasible to use well-known cardiovascular risk prediction rules, recalibrating them according to the underlying cardiovascular risk of each specific country or geographic area (e.g., Latin America). In Chile, Icaza and colleagues (28) applied the FRS, but recalibrated the risk assuming a cardiovascular event rate lower than that of the United States, based on their national epidemiologic data for cardiovascular mortality. European populations with a low underlying cardiovascular risk have used the SCORE prediction system, adjusted for a low 10-year risk for fatal CVD (17). Because the recalibration process relies on accurate estimates of CVD event rates, epidemiologists and investigators must have valid sources reporting regional or national CVD events, using definitions of outcomes similar to the definitions used during the development and validation of the scores to be implemented.
The search also identified a study that validated the WHO/ISH cardiovascular risk score system (22). It tested a modified minimalist method and showed good performance when applied to a sample of hypertensive individuals in Ecuador. The system relies on hypothetical data sets for each WHO Region on the basis of risk factor prevalence and other information, as part of a collaborative risk assessment project (22). Conclusions by Montalvo and colleagues (21) might be implemented in areas of Latin America that have scare healthcare resources and where policymakers are willing to implement public health policies focused on primary prevention of CVD.
The search also identified a study that created and validated a risk prediction rule for Chagas' disease and proves that risk prediction models for conditions other than atherosclerotic CVD can be created and validated with good results and potential clinical use (23). Chagas is the leading cause of heart failure in the Amazon area that spans several countries, and its prevalence is growing in some parts of South America. Thus, these prediction rules will likely help clinicians in a large area of South America to stratify patients with Chagas' disease according to risk of death and support the clinical decision making process.
Very limited data from the published literature was found that could assist with calculating cardiovascular risk in Latin America and among Hispanics in the United States. With more than 600 million Hispanics in Latin America and the worrisome trends in CVD risk factors, the expectation was that there would be more data supporting the use or validity of risk prediction rules in this large segment of the world population. The scarcity of research on which to base and validate cardiovascular prediction rules is not limited to Latin America or Hispanics in the United States; nearly every less developed area of the world and most minority groups in the United States are challenged by it. About 75% of all cardiovascular deaths in the world occur in less developed countries, but all of the major scores to predict cardiovascular events have been created and validated in North America and Europe. The epidemiologic transition in less developed countries has prompted WHO and others to take important steps toward creating simple predictive rules that use a pragmatic approach to target modifiable cardiovascular risk factors (29). The development and validation of risk prediction rules will help to target primary prevention strategies to those who will benefit the most, thereby improving the cost-effectiveness of atherosclerotic CVD prevention programs and treatment.
This systematic review has several limitations. There are possibly some articles on validation of cardiovascular risk scores that were missed because they were either unpublished or were published by a Latin American medical journal that was not indexed by the major indices for scientific publications. In an effort to overcome this limitation, unpublished data was sought through direct contact with leaders in preventive cardiology in Latin America, and with epidemiologists with CVD risk prediction expertise in the United States.
Another limitation is the heterogeneity of Latin American populations and the inability to do further subgroup analysis among the intermediate risk populations. The databases are simply not available. Latin America boasts significant variability in diet, lifestyle, and even, genetics. Some areas, such as Argentina and the southern part of Brazil, have populations of predominantly Caucasian descent, and a diet rich in saturated fat and red meat, while vast portions of Central America have a large percentage of Indigenous Americans and a diet based on grains and vegetables. Therefore, because of the important differences among countries and communities in Latin America, the recalibration process applied in one country would need to be tested for validity in another.
A final limitation is that the definition of "Hispanic" includes a heterogeneous group of people linked by cultural and ethnic factors, and a common language that may, or may not, have anything to do with underlying CVD risk. Although studies have shown that Hispanics living in the United States may have lower CVD incidence than Caucasians, other studies have challenged this determination (9).
This systematic review revealed that the evidence of testing and validating CVD risk prediction rules among Latin American populations and/or Hispanics in United States is modest at best. Without proper recalibration, the FRS tested among Hispanic populations overestimates CVD risk. Ideally, risk prediction tools should incorporate affordable and accessible clinical and demographic information.
There are now a few cohort studies that could be imminently useful: in the United States, the Design and Implementation of the Hispanic Community Health Study/Study of Latinos (30); and in Latin America, the CESCAS I study in Argentina, Chile, and Uruguay (31); the INTERHEART study in Argentina, Brazil, Colombia, Chile, Guatemala, and Mexico) (3); and the Estudo Longitudinal de Salude do Adulto (ELSA) study in Brazil (32). The information from these could be helpful to future efforts to validate or calibrate current risk prediction rules in Latin America and among Hispanics in the United States.
Acknowledgments. The search for publications was conducted at the Mayo Clinic Plummer Library (Rochester, Minnesota, United States) by a librarian with expertise in systematic reviews. The authors gratefully acknowledge Patricia J. Erwin of the Plummer Library.
1. United States Census Bureau. Overview of race and Hispanic origin, 2010. Available at: http://www.census.gov/prod/cen2010/briefs/c2010br-02.pdf Accessed on 12 January 2012. [ Links ]
2. American Heart Association. International cardiovascular disease statistics, 2004. Available at: http://www.muschealth.com/heart/2004StatUpdate.pdf Accessed on 12 January 2012. [ Links ]
3. Lanas F, Avezum A, Bautista LE, Diaz R, Luna M, Islam S, et al. Risk factors for acute myocardial infarction in Latin America: the INTERHEART Latin American study. Circulation. 2007;115(9):1067-74. [ Links ]
4. Schargrodsky H, Hernandez-Hernandez R, Champagne BM, Silva H, Vinueza R, Silva Aycaguer LC, et al. CARMELA: assessment of cardiovascular risk in seven Latin American cities. Am J Med. 2008;121(1):58-65. [ Links ]
5. Hurley LP, Dickinson LM, Estacio RO, Steiner JF, Havranek EP. Prediction of cardiovascular death in racial/ethnic minorities using Framingham risk factors. Circ Cardiovasc Qual Outcomes. 2010;3(2):181-7. [ Links ]
6. Barcelo A. Cardiovascular diseases in Latin America and the Caribbean. Lancet. 2006; 368(9536):625-6. [ Links ]
7. American Heart Association. Heart disease and stroke statistics, 2010. Available at: http://my.americanheart.org/idc/groups/ahamah-public/@wcm/@sop/documents/downloadable/ucm_319689.pdf Accessed on 10 August 2011. [ Links ]
8. Batsis JA, Nieto-Martinez RE, Lopez-Jimenez F. Metabolic syndrome: from global epidemiology to individualized medicine. Clin Pharmacol Ther. 2007;82(5):509-24. [ Links ]
9. Hunt KJ, Resendez RG, Williams K, Haffner SM, Stern MP, Hazuda HP. All-cause and cardiovascular mortality among Mexican-American and non-Hispanic White older participants in the San Antonio Heart Studyevidence against the "Hispanic paradox." Am J Epidemiol. 2003;158(11):1048-57. [ Links ]
10. Batsis JA, Lopez-Jimenez F. Cardiovascular risk assessment-from individual risk prediction to estimation of global risk and change in risk in the population. BMC Med. 2010; 8(May 25):29. [ Links ]
11. Eichler K, Puhan MA, Steurer J, Bachmann LM. Prediction of first coronary events with the Framingham score: a systematic review. Am Heart J. 2007;153(5):722-31. [ Links ]
12. Suka M, Sugimori H, Yoshida K. Application of the updated Framingham risk score to Japanese men. Hypertens Res. 2001;24(6):685-9. [ Links ]
13. Marrugat J, Solanas P, D'Agostino R, Sullivan L, Ordovas J, Cordon F, et al. Coronary risk estimation in Spain using a calibrated Framingham function. Rev Esp de Cardiol. 2003; 56(3):253-61. [ Links ]
14. Liu J, Hong Y, D'Agostino RB Sr., Wu Z, Wang W, Sun J, et al. Predictive value for the Chinese population of the Framingham CHD risk assessment tool compared with the Chinese Multi-Provincial Cohort Study. JAMA. 2004;291(21):2591-9. [ Links ]
15. Assmann G, Cullen P, Schulte H. Simple scoring scheme for calculating the risk of acute coronary events based on the 10-year follow-up of the prospective cardiovascular Munster (PROCAM) study. Circulation. 2002;105(3):310-5. [ Links ]
16. Ridker PM, Buring JE, Rifai N, Cook NR. Development and validation of improved algorithms for the assessment of global cardiovascular risk in women: the Reynolds Risk Score. JAMA. 2007;297(6):611-9. [ Links ]
17. Conroy RM, Pyorala K, Fitzgerald AP, Sans S, Menotti A, De Backer G, De Bacquer D, Ducimetiere P, Jousilahti P, Keil U, Njolstad I, Oganov RG, Thomsen T, Tunstall-Pedoe H, Tverdal A, Wedel H, Whincup P, Wilhelmsen L, Graham IM. Estimation of ten-year risk of fatal cardiovascular disease in Europe: the SCORE project. Euro Heart J. 2003;24(11):987-1003. [ Links ]
18. Jimenez-Corona A, Lopez-Ridaura R, Williams K, Gonzalez-Villalpando ME, Simon J, Gonzalez-Villalpando C. Applicability of Framingham risk equations for studying a low-income Mexican population. Salud publica Mex. 2009;51(4):298-305. [ Links ]
19. Wilson PW, D'Agostino RB, Levy D, Belanger AM, Silbershatz H, Kannel WB. Prediction of coronary heart disease using risk factor categories. Circulation. 1998;97(18):1837-47. [ Links ]
20. Anderson KM, Wilson PW, Odell PM, Kannel WB. An updated coronary risk profile. A statement for health professionals. Circulation. 1991;83(1):356-62. [ Links ]
21. Montalvo G, Avanzini F, Anselmi M, Prandi R, Ibarra S, Marquez M, et al. Diagnostic evaluation of people with hypertension in low income country: cohort study of "essential" method of risk stratification. BMJ. 2008;337: 1387. [ Links ]
22. Chalmers J, MacMahon S, Mancia G, Whitworth J, Beilin L, Hansson L, et al. World Health Organization-International Society of Hypertension Guidelines for the management of hypertension. Clin Exp Hypertens. 1999;21(5-6):1009-60. [ Links ]
23. Rassi A Jr., Rassi A, Little WC, Xavier SS, Rassi SG, Rassi AG, et al. Development and validation of a risk score for predicting death in Chagas' heart disease. N Engl J Med. 2006; 355(8):799-808. [ Links ]
24. D'Agostino RB, Sr., Grundy S, Sullivan LM, Wilson P. Validation of the Framingham coronary heart disease prediction scores: results of a multiple ethnic groups investigation. JAMA. 2001;286(2):180-7. [ Links ]
25. Brindle P, Emberson J, Lampe F, Walker M, Whincup P, Fahey T, et al. Predictive accuracy of the Framingham coronary risk score in British men: prospective cohort study. BMJ. 2003; 327(7426):1267. [ Links ]
26. Empana JP, Ducimetiere P, Arveiler D, Ferrieres J, Evans A, Ruidavets JB, et al. Are the Framingham and PROCAM coronary heart disease risk functions applicable to different European populations? The PRIME Study. Eur Heart J 2003;24(21):1903-11. [ Links ]
27. 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 the MONICA Augsburg and the PROCAM cohorts. Eur Heart J. 2003;24(10):937-45. [ Links ]
28. Icaza G, Nunez L, Marrugat J, Mujica V, Escobar MC, Jimenez AL, et al. Estimación de riesgo de enfermedad coronaria mediante la función de Framingham adoptada para la población chilena. Rev Med de Chil. 2009; 137(10):1273-82. [ Links ]
29. Gaziano TA, Young CR, Fitzmaurice G, Atwood S, Gaziano JM. Laboratory-based versus non-laboratory-based method for assessment of cardiovascular disease risk: the NHANES I follow-up study cohort. Lancet. 2008;371(9616):923-31. [ Links ]
30. Sorlie PD, Aviles-Santa LM, Wassertheil-Smoller S, Kaplan RC, Daviglus ML, Giachello AL, et al. Design and implementation of the Hispanic Community Health Study/Study of Latinos. Ann Epidemiol. 2010;20(8):629-41. [ Links ]
21. Rubinstein AL, Irazola VE, Poggio R, Bazzano L, Calandrelli M, Lanas Zanetti FT, et al. Detection and follow-up of cardiovascular disease and risk factors in the Southern Cone of Latin America: the CESCAS I study. BMJ Open. 2011;1(1):e000126. [ Links ]
32. Aquino EM, Barreto SM, Bensenor IM, Carvalho MS, Chor D, Duncan BB, et al. Brazilian Longitudinal Study of Adult Health (ELSA-Brasil): objectives and design. Am J Epidemiol. 2012;175(4):315-24. [ Links ]
Manuscript received on 6 June 2011.
Revised version accepted for publication on 28 March 2011.