Diverse Populations Collaborative Group. Prediction of mortality from coronary heart disease among diverse populations: is there a common predictive function?

Risk estimation for the primary prevention of cardiovascular disease: considerations for appropriate risk prediction model selection

Cardiovascular diseases remain the number one cause of death globally. Cardiovascular disease risk scores are an integral tool in primary prevention, being used to identify individuals at the highest risk and guide the assignment of preventive interventions. Available risk scores differ substantially in terms of the population sample data sources used for their derivation and, consequently, in the absolute risks they assign to individuals. Differences in cardiovascular disease epidemiology between the populations contributing to the development of risk scores, and the target populations in which they are applied, can result in overestimation or underestimation of cardiovascular disease risks for individuals, and poorly informed clinical decisions. Given the wide plethora of cardiovascular disease risk scores available, identification of an appropriate risk score for a target population can be challenging. This Review provides an up-to-date overview of guideline-recommended cardiovascular disease risk scores from global, regional, and national contexts, evaluates their comparative characteristics and qualities, and provides guidance on selection of an appropriate risk score.

Association between PON1 rs662 gene polymorphism and serum paraoxonase1 level in coronary artery disease patients in Northern India

Background

Coronary artery disease (CAD) is a leading cause of morbidity and mortality, with a shifting trend towards the younger population. Paraoxonase1 (PON1) is a glycoprotein enzyme associated with high-density lipoprotein (HDL) particles in the blood. It has the ability to protect against lipid oxidation, thereby reducing the risk of atherogenesis. PON1 rs662 gene polymorphism may affect serum PON1 levels as well as its activity and may have a significant role in the pathogenesis of CAD. The present study was conducted to identify the association of PON1 rs662 gene polymorphism with serum PON1 levels in CAD patients in the North Indian population. This case–control study included 71 angiography-proven CAD patients (with > 50% luminal stenosis in one or more coronary arteries) and 71 controls (with < 50% luminal obstruction in angiography). PON1 rs662 gene polymorphism was studied using PCR and RFLP under the standardized protocol. Serum PON1 levels were estimated by ELISA.

Results

The serum PON1 level was significantly lower in the CAD group than in the controls (7.79 ± 3.16 vs. 10.79 ± 3.19 ng/mL; p < 0.0001). Logistic regression analysis showed that homozygous GG genotype of PON1 rs662 SNP has ninefold increased risk of developing CAD in an Indian population (OR = 9.0, 95%CI 2.79–29.06, p = 0.0002). A significantly higher frequency of G allele was also observed in CAD patients than in controls (OR 2.64, 95%CI 1.61–4.33, p = 0.001).

Conclusions

The reduced serum PON1 level is associated with CAD. PON1 rs662 gene polymorphism is significantly associated with CAD susceptibility in the North Indian population.

Prediction for cardiovascular diseases based on laboratory data: An analysis of random forest model

Background

To establish a prediction model for cardiovascular diseases (CVD) in the general population based on random forests.

Methods

A retrospective study involving 498 subjects was conducted in Xi'an Medical University between 2011 and 2018. The random forest algorithm was used to screen out the variables that greatly affected the CVD prediction and to establish a prediction model. The important variables were included in the multifactorial logistic regression analysis. The area under the curve (AUC) was compared between logistic regression model and random forest model.

Results

The random forest model revealed the variables, including the age, body mass index (BMI), fasting blood glucose (FBG), diastolic blood pressure (DBP), triglyceride (TG), systolic blood pressure (SBP), total cholesterol (TC), waist circumference, and high‐density lipoprotein‐cholesterol (HDL‐C), were more significant for CVD prediction; the AUC was 0.802 in CVD prediction. Multifactorial logistic regression analysis indicated that the risk factors for CVD included the age [odds ratio (OR): 1.14, 95% confidence intervals (CI): 1.10‐1.17, P < .001], BMI (OR: 1.13, 95% CI: 1.06‐1.20, P < .001), TG (OR: 1.11, 95% CI: 1.02‐1.22, P = .023), and DBP (OR: 1.04, 95% CI: 1.02‐1.06, P = .001); the AUC was 0.843 in CVD prediction. The established logistic regression prediction model was Logit P = Log[P/(1 − P)] = −11.47 + 0.13 × age + 0.12 × BMI + 0.11 × TG + 0.04 × DBP; P = 1/[1 + exp(−Logit P)]. People were prone to develop CVD at the time of P > .51.

Conclusions

A prediction model for CVD is developed in the general population based on random forests, which provides a simple tool for the early prediction of CVD.

Lifestyle behaviour and prevalence of cardiovascular risk factors - a pilot study comparing Kiribati and European seafarers

Background

According to internal observations within a German shipping company, obvious risk-behaviour persists among the crew members coming from the Pacific Island State of Kiribati and representing a large part of the crew aboard merchant vessels of this company. These observations were related to excessive eating habits. This study aims to assess the cardiovascular risk among seafarers and to compare lifestyle factors between Kiribati and European crew members.

Methods

In the present maritime field study 81 sailors (48 Kiribati, 33 European, average age at 38.9 and 36.8 years respectively) were examined from April until August 2014 aboard four container ships crossing the Atlantic Ocean (participation rate of 90.9%).

Results

Based on the number of established risk factors, 35.4% of the Kiribati and 16.7% of the European crew members were regarded as a high risk group for cardiovascular diseases. The HDL-values of Kiribati were found to be considerably lower (34.9 mg/dl) than the references values given by the WHO and in comparison to the European crew members (44.8 mg/dl) (p = 0.002). 91.7% of Kiribati and 51.5% of European participants were found to be overweight according to WHO-criteria - with a mean Body Mass Index (BMI) of 30.3 kg/m² and 25.6 kg/m² (p <  0.001). Regarding lifestyle factors Kiribati often claimed to eat significantly larger amounts of food aboard while most European sailors stated to eat less or about the same during their shipboard stay (p = 0.017). Daily sleeping hours were slight on both sides; however with a mean of 5.2 h a day Kiribati crew members had significant fewer sleep (p = 0.038). The examined Kiribati sailors had a mean increase in weight of 6 kg over a 12 months period of observation.

Conclusions

In total the compiled data points towards a higher risk of cardiovascular diseases particularly due to alimentary habits within the Kiribati crew members. The distinct weight-gain measured among the Kiribati in spite of higher energy consumption levels at sea is alarming. Thus, the results of this study confirm the necessity of health-improving interventions aboard cargo vessels.

Machine learning models in electronic health records can outperform conventional survival models for predicting patient mortality in coronary artery disease

Prognostic modelling is important in clinical practice and epidemiology for patient management and research. Electronic health records (EHR) provide large quantities of data for such models, but conventional epidemiological approaches require significant researcher time to implement. Expert selection of variables, fine-tuning of variable transformations and interactions, and imputing missing values are time-consuming and could bias subsequent analysis, particularly given that missingness in EHR is both high, and may carry meaning. Using a cohort of 80,000 patients from the CALIBER programme, we compared traditional modelling and machine-learning approaches in EHR. First, we used Cox models and random survival forests with and without imputation on 27 expert-selected, preprocessed variables to predict all-cause mortality. We then used Cox models, random forests and elastic net regression on an extended dataset with 586 variables to build prognostic models and identify novel prognostic factors without prior expert input. We observed that data-driven models used on an extended dataset can outperform conventional models for prognosis, without data preprocessing or imputing missing values. An elastic net Cox regression based with 586 unimputed variables with continuous values discretised achieved a C-index of 0.801 (bootstrapped 95% CI 0.799 to 0.802), compared to 0.793 (0.791 to 0.794) for a traditional Cox model comprising 27 expert-selected variables with imputation for missing values. We also found that data-driven models allow identification of novel prognostic variables; that the absence of values for particular variables carries meaning, and can have significant implications for prognosis; and that variables often have a nonlinear association with mortality, which discretised Cox models and random forests can elucidate. This demonstrates that machine-learning approaches applied to raw EHR data can be used to build models for use in research and clinical practice, and identify novel predictive variables and their effects to inform future research.

The strength of the multivariable associations of major risk factors predicting coronary heart disease mortality is homogeneous across different areas of the Seven Countries Study during 50-year follow-up

OBJECTIVES

To compare the magnitude of multivariable coefficients and hazard ratios of four cardiovascular risk factors across five worldwide regions of the Seven Countries Study in predicting 50-year coronary deaths.

MATERIAL AND METHODS

A total of 13 cohorts of middle-aged men at entry (40-59 years old) were enrolled in the mid-1900s from five relatively homogeneous groups of cohorts (areas): USA, Finland and Zutphen - the Netherlands, Italy and Greece, Serbia, Japan for a total of 10,368 middle-aged men. The major risk factors measured at baseline were age, number of cigarettes smoked, systolic blood pressure and serum cholesterol. Cox proportional hazards models were solved for 50-year (45 years for Serbia) deaths from coronary heart disease (CHD), and the multivariable coefficients were compared for heterogeneity.

RESULTS

The highest levels of risk factors and CHD death rates were found in Finland and Zutphen - the Netherlands and the lowest in Japan. All four risk factors were predictive for long-term CHD mortality in all regions, except serum cholesterol in Japan where the mean levels and CHD events were lowest. Tests of heterogeneity of coefficients for single risk factors in predicting CHD mortality were non-significant across the five areas. The same analyses for the first 25 years of follow-up produced similar findings.

CONCLUSIONS

The strength of the multivariable associations of four major traditional CHD risk factors with long-term CHD mortality appears to be relatively homogeneous across areas, pending needed further evidence.

Coronary Artery Disease in French Canadians-Investigation of a Suggested Vulnerable Population

BACKGROUND

There is a perception among Canadian physicians that coronary artery disease (CAD) and adverse cardiac events are more common in those of French Canadian heritage. We sought to compare the prevalence of CAD using coronary computed tomographic angiography (CCTA) in French Canadians and non-French white Canadians.

METHODS

Consecutive patients were prospectively enrolled in our institutional CCTA registry. Of 10,868 CCTA examinations, we analyzed white patients who identified themselves as French Canadian or non-French Canadian. These 2 groups were compared for baseline characteristics, cardiovascular risk factors, and routine markers for CAD on CTCA. Propensity score adjustments were also made to account for differences in demographics.

RESULTS

We identified 1683 French Canadians (mean age, 58.5 ± 10.7 years; 54.2% men) and 5077 non-French white Canadians (mean age, 59.4 ± 11.4 years; 57.3% men). French Canadians were more likely to have a smoking history (64.1% vs 56.1%), diabetes (15.6% vs 13.6%), and a family history of premature CAD (53.3% vs 44.6%) (P < 0.05 for all). There was no significant difference in measures of CAD between French Canadians and non-French white Canadians in obstructive CAD (32.5% vs 32.2%; P = 0.997), total plaque score (4.6 ± 4.3 vs 4.5 ± 4.4; P = 0.616) and Agatston score (168.1 ± 319.8 vs 183.6 ± 433.7; P = 0.371). After propensity score adjustment, there was still no significant difference between the groups.

CONCLUSIONS

Our study suggests that French Canadians in the Champlain region have a greater prevalence of cardiovascular risk factors compared with non-French Canadians; however, they do not appear to have a greater prevalence or severity of coronary atherosclerosis as assessed by CCTA.

Clinical assessment of patients with chest pain; a systematic review of predictive tools

Background

The clinical assessment of patients with chest pain of recent onset remains difficult. This study presents a critical review of clinical predictive tools for the assessment of patients with chest pain.

Methods

Systematic review of observational studies and estimation of probabilities of coronary artery disease (CAD) in patients with chest pain. Searches were conducted in PubMed, Embase, Scopus, and Web of Science to identify studies reporting tools, with at least three variables from clinical history, physical examination or ECG, produced with multivariate analysis, to estimate probabilities of CAD in patients with chest pain of recent onset, published from inception of the database to the 31^st July 2015. The references of previous relevant reviews were hand searched. The methodological quality was assessed with standard criteria. Since the incidence of CAD has changed in the past few decades, the date of publication was acknowledged to be relevant in order to use the tool in clinical practice, and more recent papers were considered more relevant. Probabilities of CAD according to the studies of highest quality were estimated and the evidence provided was graded.

Results

Twelve papers were included out of the 19126 references initially identified. The methodological quality of all of them was high. The clinical characteristics of the chest pain, age, past medical history of cardiovascular disease, gender, and abnormalities in the ECG were the predictors of CAD most commonly reported across the studies. The most recent papers, with highest methodological quality, and most practical for use in clinical settings, reported prediction or exclusion of CAD with area under the curve 0.90 in Primary Care, 0.91 in Emergency department, and 0.79 in Cardiology. These papers provide evidence of high level (1B) and the recommendation to use their results in the management of patients with chest pain is strong (A).

Conclusions

The risk of CAD can be estimated on clinical grounds in patients with chest pain in different clinical settings with high accuracy. The estimation of probabilities of CAD presented in these studies could be used for a better management of patients with chest pain and also in the development of future predictive tools.

Electronic supplementary material

The online version of this article (doi:10.1186/s12872-016-0196-4) contains supplementary material, which is available to authorized users.

Traditional Risk Factors Versus Biomarkers for Prediction of Secondary Events in Patients With Stable Coronary Heart Disease: From the Heart and Soul Study

BACKGROUND

Patients with stable coronary heart disease (CHD) have widely varying prognoses and treatment options. Validated models for risk stratification of patients with CHD are needed. We sought to evaluate traditional and novel risk factors as predictors of secondary cardiovascular (CV) events, and to develop a prediction model that could be used to risk stratify patients with stable CHD.

METHODS AND RESULTS

We used independent derivation (912 participants in the Heart and Soul Study) and validation (2876 participants in the PEACE trial) cohorts of patients with stable CHD to develop a risk prediction model using Cox proportional hazards models. The outcome was CV events, defined as myocardial infarction, stroke, or CV death. The annual rate of CV events was 3.4% in the derivation cohort and 2.2% in the validation cohort. With the exception of smoking, traditional risk factors (including age, sex, body mass index, hypertension, dyslipidemia, and diabetes) did not emerge as the top predictors of secondary CV events. The top 4 predictors of secondary events were the following: N-terminal pro-type brain natriuretic peptide, high-sensitivity cardiac troponin T, urinary albumin:creatinine ratio, and current smoking. The 5-year C-index for this 4-predictor model was 0.73 in the derivation cohort and 0.65 in the validation cohort. As compared with variables in the Framingham secondary events model, the Heart and Soul risk model resulted in net reclassification improvement of 0.47 (95% CI 0.25 to 0.73) in the derivation cohort and 0.18 (95% CI 0.01 to 0.40) in the validation cohort.

CONCLUSIONS

Novel risk factors are superior to traditional risk factors for predicting 5-year risk of secondary events in patients with stable CHD.

Cardiovascular risk assessment: a global perspective

An important strategy in primary prevention of cardiovascular diseases (CVD) is the early identification of high-risk individuals. Effective implementation of a strategy to identify these individuals in a clinical setting is reliant on the availability of appropriate CVD risk-assessment models and guideline recommendations. Several well-known models for CVD risk assessment have been developed and utilized in the USA and Europe, but might not be suitable for use in other regions or countries. Very few reports have discussed the development of risk-assessment models and recommendations from a global perspective. In this Review, we discuss why risk-assessment methods developed from studies in one geographical region or ethnic population might not be suitable for other regions or populations, and examine the availability and characteristics of predictive models in areas beyond the USA or Europe. In addition, we compare the differences in risk-assessment recommendations outlined in CVD clinical guidelines from developed and developing countries, and consider their potential effect on clinical practice. This overview of cardiovascular risk assessment from a global perspective can potentially guide low-to-middle-income countries in the development or validation of their own CVD risk-assessment models, and the formulation of recommendations in their own clinical guidelines according to local requirements.

Altered coronary artery calcium scores before bariatric surgery

Introduction

Obesity is an important cause of cardiovascular disease, especially coronary artery disease. Severely obese patients are particularly prone to this risk. The coronary artery calcium (CAC) score is a strong predictor of coronary heart disease and provides incremental information beyond traditional risk factors. We sought to determine the prevalence of abnormally high CAC scores in the preoperative setting among patients undergoing bariatric surgery and to establish risk predictors for higher scores.

Methods

We performed an observational study of 202 patients free of known coronary artery disease who were referred for bariatric surgery. In each patient, the presence of CAC was detected with computed tomography, and coronary risk variables were either measured or determined via questionnaire.

Results

CAC was found in 14.4% of the overall population (26% of male and 10.5% of female patients). Participants with altered CAC scores were older (mean age, 46.8 years). The variables positively associated with an altered CAC score were older age, male sex, type 2 diabetes, hypertension, and hypercholesterolemia. Multivariate-adjusted analysis showed that age (OR, 1.11; 95% CI, 1.06–1.17; p = 0.001), male sex (OR, 4.17; 95% CI, 1.52–11.47; p = 0.006), and hypercholesterolemia (OR, 6.21; 95% CI, 1.81–21.29; p = 0.004) were most closely related to the presence of CAC.

Conclusion

Obese patients in the preoperative bariatric surgery setting have a high prevalence of abnormal CAC scores. Traditional risk factors play a important role in this scenario.

Assessment of the reporting quality of randomized controlled trials on treatment of coronary heart disease with traditional chinese medicine from the chinese journal of integrated traditional and Western medicine: a systematic review

Background

Due to language limitations, little is known about the reporting quality of randomized clinical trials (RCTs) on the treatment of coronary heart disease (CHD) with traditional Chinese medicine (TCM) in Chinese Journal of Integrated Traditional and Western Medicine (CJITWM).

Objective

In this study, we utilized the CONSORT 2010 statement to understand the reporting quality of RCTs on CHD with TCM from the CJITWM.

Methods

The China National Knowledge Infrastructure (CNKI) electronic database was searched for CJITWM RCTs on the treatment of CHD with TCM, published between Janurary 1, 2006 and December 31, 2011. We excluded articles reported as “animal studies,” “topic review,” “diagnostic test,” “editorials,” or “others.” The CONSORT checklist was applied to evaluate the reporting quality of all eligible articles by two independent authors after extensive discussion. Each item was graded as either “yes” or “no” depending on whether the authors had reported it or not.

Results

We identified 21 articles meeting our inclusion criteria. The percentage of 11 of the 37 items was 4.8∼95.2%, 14 of the 37 items were reported in all included articles, while 12 items were not mentioned at all. The average reporting percentage for the “title and abstract” section was 52.4%, for the “introduction” section 100.0%, for the “methods” section 45.4%, for the “results” section 57.1%, for the “discussion” section 79.4%, and for the “other information” section 17.5%.

Conclusion

In general, the reviewed RCTs were not consistent with the CONSORT 2010 statement. Authors should adhere to the CONSORT statement in reporting RCTs; editorial departments may consider the CONSORT statement as a guideline and should instruct authors to write manuscripts, and reviewers to judge them according to CONSORT statutes.

An International Atherosclerosis Society Position Paper: global recommendations for the management of dyslipidemia--full report

An international panel of the International Atherosclerosis Society has developed a new set of recommendations for the management of dyslipidemia. The panel identifies non--high-density lipoprotein cholesterol as the major atherogenic lipoprotein. Primary and secondary prevention are considered separately. Optimal levels for atherogenic lipoproteins are derived for the two forms of prevention. For primary prevention, the recommendations emphasize lifestyle therapies to reduce atherogenic lipoproteins; drug therapy is reserved for subjects at greater risk. Risk assessment is based on estimation of lifetime risk according to differences in baseline population risk in different nations or regions. Secondary prevention emphasizes use of cholesterol-lowering drugs to attain optimal levels of atherogenic lipoproteins.

Individual risk prediction model for incident cardiovascular disease: a Bayesian clinical reasoning approach

BACKGROUND

A Bayesian clinical reasoning model was developed to predict an individual risk for cardiovascular disease (CVD) for desk-top reference.

METHODS

Three Bayesian models were constructed to estimate the CVD risk by sequentially incorporating demographic features (basic), six metabolic syndrome components (metabolic score) and conventional risk factors (enhanced model). By considering clinical weights (regression coefficients) of each model as normal distribution, individual risk can be predicted making allowance for uncertainty of clinical weights. A community-based cohort that enrolled 64,489 participants free of CVD at baseline and followed up over five years to ascertain newly diagnosed CVD cases during the period through 2000 to 2004 was used for the illustration of the three proposed models (full empirical data are available from website http://homepage.ntu.edu.tw/~chenlin/CVD_prediction_data.rar).

RESULTS

The proposed models can be applied to predicting the CVD risk with any combination of risk factors. For a 47-year-old man, the five-year risk for CVD with the basic model was 11.2% (95% CI: 7.8%-15.6%). His metabolic syndrome score, leading to 1.488 of likelihood ratio, enhanced the risk for CVD up to 15.8% (95% CI: 11.0%-21.5%) and put him in highest deciles. As with the habit of smoking over 2 packs per-day and family history of CVD, yielding the likelihood ratios of 1.62 and 1.47, respectively, the risk was further raised to 30.9% (95% CI: 20.7%-39.8%).

CONCLUSIONS

We demonstrate how to make individual risk prediction for CVD by incorporating routine information with a sequential Bayesian clinical reasoning approach.

Subclinical cardiovascular disease assessment in persons with diabetes

Patients with diabetes mellitus are at particularly high risk for cardiovascular disease. Although global risk factor scoring systems, such as the Framingham Risk Score, are well established for screening asymptomatic adults, they are not as predictive in diabetics. Therefore, there has been considerable interest in new screening tests to establish cardiovascular risk in diabetics. Coronary artery calcium assessment, both baseline levels and progression, have been shown to be additive to risk factor scoring systems and are independently predictive of cardiovascular mortality in diabetics. Current American Heart Association/American College of Cardiology Foundation guidelines recommend coronary calcium scoring for asymptomatic diabetics. Myocardial perfusion studies are recommended for patients with a coronary calcium score >400 but the level of evidence is poor. The data for other screening tests is limited. Further research is required into assessing what would be an appropriate follow-up duration for serial coronary calcium scanning.

Prognostic value of coronary CT angiography and calcium score for major adverse cardiac events in outpatients

OBJECTIVES

This study sought to evaluate the prognostic value of coronary artery calcium score (CACS) and coronary computed tomography angiography (CTA) for major adverse cardiac events (MACE).

BACKGROUND

The prognostic value of CACS has been well described. Few studies use the rich information of coronary CTA to predict future clinical outcomes and compare CACS with coronary CTA.

METHODS

We followed up 5,007 outpatients who were suspected of having coronary artery disease (CAD) and who underwent cardiac CTA. Cardiac CT was assessed for CACS and the extent, the location, the stenosis severity, and the composition of the plaque in coronary CTA. The endpoint was MACE, defined as composite cardiac death, nonfatal myocardial infarction, or coronary revascularization.

RESULTS

Follow-up was completed in 4,425 patients (88.4%), with a median follow-up period of 1,081 days. At the end of the follow-up period, 363 (8.2%) patients had experienced MACE. Cumulative probability of 3-year MACE increased across CT strata for CACS (CACS 0, 2.1%; CACS 1 to 100, 12.9%; CACS 101 to 400, 16.3%; and CACS >400, 33.8%; log-rank p < 0.001); for coronary CTA (no plaque 0.8%, nonobstructive disease 3.7%, 1-vessel disease 27.6%, 2-vessel disease 35.5%, and 3-vessel disease 57.7%; log-rank p < 0.001); and for characteristics of the plaques (5.5% for calcified plaque, 22.7% for noncalcified plaque, and 37.7% for mixed plaque; log-rank p < 0.001). The area under the receiver-operating characteristic curves showed the incremental value of CACS and coronary CTA for predicting MACE: 0.71 for clinical risk factors, which improved to 0.82 by adding CACS and further improved to 0.93 by adding coronary CTA (both p < 0.001).

CONCLUSIONS

The CACS and coronary CTA findings have prognostic value and have incremental value over routine risk factors for MACE, and coronary CTA is superior to CACS. Cardiac CT seems to be a promising noninvasive modality with significant prognostic value.

Comparison of the Framingham and Reynolds Risk scores for global cardiovascular risk prediction in the multiethnic Women's Health Initiative

BACKGROUND

Framingham-based and Reynolds Risk scores for cardiovascular disease (CVD) prediction have not been directly compared in an independent validation cohort.

METHODS AND RESULTS

We selected a case-cohort sample of the multiethnic Women's Health Initiative Observational Cohort, comprising 1722 cases of major CVD (752 myocardial infarctions, 754 ischemic strokes, and 216 other CVD deaths) and a random subcohort of 1994 women without prior CVD. We estimated risk using the Adult Treatment Panel III (ATP-III) score, the Reynolds Risk Score, and the Framingham CVD model, reweighting to reflect cohort frequencies. Predicted 10-year risk varied widely between models, with ≥10% risk in 6%, 10%, and 41% of women with the ATP-III, Reynolds, and Framingham CVD models, respectively. Calibration was adequate for the Reynolds model, but the ATP-III and Framingham CVD models overestimated risk for coronary heart disease and major CVD, respectively. After recalibration, the Reynolds model demonstrated improved discrimination over the ATP-III model through a higher c statistic (0.765 versus 0.757; P=0.03), positive net reclassification improvement (NRI; 4.9%; P=0.02), and positive integrated discrimination improvement (4.1%; P<0.0001) overall, excluding diabetics (NRI=4.2%; P=0.01), and in white (NRI=4.3%; P=0.04) and black (NRI=11.4%; P=0.13) women. The Reynolds (NRI=12.9%; P<0.0001) and ATP-III (NRI=5.9%; P=0.0001) models demonstrated better discrimination than the Framingham CVD model.

CONCLUSIONS

The Reynolds Risk Score was better calibrated than the Framingham-based models in this large external validation cohort. The Reynolds score also showed improved discrimination overall and in black and white women. Large differences in risk estimates exist between models, with clinical implications for statin therapy.

Statistical Relational Learning to Predict Primary Myocardial Infarction from Electronic Health Records

Electronic health records (EHRs) are an emerging relational domain with large potential to improve clinical outcomes. We apply two statistical relational learning (SRL) algorithms to the task of predicting primary myocardial infarction. We show that one SRL algorithm, relational functional gradient boosting, outperforms propositional learners particularly in the medically-relevant high recall region. We observe that both SRL algorithms predict outcomes better than their propositional analogs and suggest how our methods can augment current epidemiological practices.

Projected cost-effectiveness of ezetimibe/simvastatin compared with doubling the statin dose in the United Kingdom: findings from the INFORCE study

OBJECTIVE

To evaluate the incremental cost-effectiveness ratio (ICER) of switching to ezetimibe/simvastatin (Eze/Simva) compared with doubling the submaximal statin doses, in patients with acute coronary syndrome (ACS) events in the INFORCE study.

METHODS

Lifetime treatment costs and benefits were computed using a Markov model. Model inputs included each patient's cardiovascular risk factor profile and actual lipid values at baseline and 12 weeks (endpoint). Cardiovascular event and drug costs were discounted at 3.5%. Age-specific utilities were based on UK literature values and non-coronary heart disease mortality rates on the Office of National Statistics data. In the INFORCE study, 384 patients taking statins at stable doses for ≥6 weeks before hospital admission were stratified by statin dose/potency (low, medium, and high) and then randomized to doubling the statin dose or switching to Eze/Simva 10/40mg for 12 weeks.

RESULTS

The Eze/Simva group (n=195) had a higher mean baseline total cholesterol than the double-statin group (n=189). Analyses were adjusted for baseline characteristics. In the INFORCE study, Eze/Simva reduced low-density lipoprotein cholesterol (LDL-C) by ∼30% (vs. 4% with doubling statin doses) and significantly enhanced LDL-C goal attainment. In the cost-effectiveness analysis, Eze/Simva conferred 0.218 incremental discounted quality-adjusted life year (QALY) at a discounted incremental cost of £2524, for an ICER of £11,571/QALY (95% confidence interval=£8181-£18,600/QALY). The ICER was £13,552/QALY, £11,930/QALY, and £10,148/QALY in the low-, medium-, and high-potency strata, respectively.

CONCLUSIONS

Switching to Eze/Simva 10/40 mg is projected to be a cost-effective treatment (vs. double-statin) in UK patients with ACS.

Predicting the risk of coronary heart disease I. The use of conventional risk markers

This is the first of two articles reviewing recent findings about the risk of coronary heart disease. This paper is concerned with conventional risk factors; the second will review novel molecular biomarkers, genetic markers of risk and the future of risk prediction. Predicting exactly the future occurrence of coronary heart disease (CHD) is not possible, but the risk can be estimated with models based on cohort studies. Most existing models are based on long-standing research on the residents of Framingham, Massachusetts. The findings from Framingham yield inaccurate results when applied to contemporary populations elsewhere. In particular, they may exacerbate health inequalities. This is because the incidence of and mortality from CHD have fallen recently, the Framingham cohort differs from many groups to which findings from it have been applied, important risk factors such as ethnicity, socio-economic deprivation and family history are absent from the Framingham equations and susceptibility to risk factors varies between populations. Attempts to recalibrate or adjust the Framingham equations to improve their performance have not been shown to overcome these problems. SCORE, QRISK, PROCAM and ASSIGN are risk prediction models that have been developed based on different cohorts. The group developing NICE's guideline on lipid modification was uncertain about which risk prediction model to recommend for use in the NHS. Eventually they selected a modified version of the Framingham equation. However, QRISK appears to offer the best long-term promise.

Cardiovascular risk estimation tailored to different clinical settings - the Tromsø study

OBJECTIVE

To develop a cardiovascular risk model simulating different clinical settings using a staged approach.

DESIGN

Using data from 27,477 men and women from the Norwegian Tromsø Study in 1986-1987 and 1994-1995, Cox regression models for either myocardial infarction (MI) or stroke combined with a similar model for the competing event a risk model that assess ten-year risk of MI and stroke was developed. Explanatory variables (questions, simple examinations and blood samples) were added gradually. The model was validated using Hosmer-Lemeshow test, the Brier score, c-index, integrated discrimination improvement (IDI) and Net Reclassification Improvement (NRI).

RESULTS

In total, 1,298 events of MI and 769 events of stroke were registered. For MI the model showed excellent discrimination in each step with c-index from 0.833 to 0.946. For stroke the c-index ranged between 0.817 and 0.898. IDI showed significant increases in discrimination. The Brier scores and goodness of fit test showed well calibrated models in all steps for all sex- and end-point specific models (p>0.05).

CONCLUSIONS

Although the predictive and discriminative ability of the models increased with each step, even the simplest model containing only data from questions or blood samples alone yielded valid estimates of cardiovascular risk.

Sex and ethnic differences in 47 candidate proteomic markers of cardiovascular disease: the Mayo Clinic proteomic markers of arteriosclerosis study

BACKGROUND

Cardiovascular disease (CVD) susceptibility differs between men and women and varies with ethnicity. This variability is not entirely explained by conventional CVD risk factors. We examined differences in circulating levels of 47 novel protein markers of CVD in 2561 men and women of African-American (AA) and non-Hispanic White (NHW) ethnicity, enrolled at geographically distinct sites.

METHODOLOGY/PRINCIPAL FINDINGS

Participants (1,324 AAs, mean age 63.5 y, 71% women; 1,237 NHWs, mean age 58.9 y, 57% women) belonged to sibships ascertained on the basis of hypertension. Solid-phase immunoassays and immunoturbidometric, clot-based, chromogenic, and electrophoretic assays were used to measure the 47 protein markers in plasma or serum. Marker levels were log transformed and outliers were adjusted to within 4 SD. To identify markers independently associated with sex or ethnicity, we employed multivariable regression analyses that adjusted for conventional risk factors, prior history of CVD, medication use and lifestyle factors (physical activity, alcohol consumption and education). Generalized estimating equations were used to correct for intrafamilial correlations. After adjustment for the above covariates, female sex was associated with higher levels of 29 markers and lower levels of 6 markers. Female sex was independently associated with higher levels of several inflammatory markers as well as lipoproteins, adipokines, natriuretic peptides, vasoconstrictor peptides and markers of calcification and thrombosis. AA ethnicity was associated with higher levels of 19 markers and lower levels of 6 markers, including higher levels of several inflammatory makers, higher leptin and lower adiponectin levels, lower levels of vasodilator-natriuretic peptides, higher levels of vasoconstrictor-antidiuretic peptides and markers of calcification and thrombosis.

CONCLUSIONS/SIGNIFICANCE

Plasma levels of several novel protein markers of CVD differ significantly in the context of sex and ethnicity. These results have implications for individualized CVD risk assessment.

Improving global vascular risk prediction with behavioral and anthropometric factors. The multiethnic NOMAS (Northern Manhattan Cohort Study)

OBJECTIVES

This study sought to improve global vascular risk prediction with behavioral and anthropometric factors.

BACKGROUND

Few cardiovascular risk models are designed to predict the global vascular risk of myocardial infarction, stroke, or vascular death in multiethnic individuals, and existing schemes do not fully include behavioral risk factors.

METHODS

A randomly derived, population-based, prospective cohort of 2,737 community participants free of stroke and coronary artery disease was followed up annually for a median of 9.0 years in the NOMAS (Northern Manhattan Study) (mean age 69 years, 63.2% women, 52.7% Hispanic, 24.9% African American, and 19.9% white). A global vascular risk score (GVRS) predictive of stroke, myocardial infarction, or vascular death was developed by adding variables to the traditional Framingham cardiovascular variables based on the likelihood ratio criteria. Model utility was assessed through receiver-operating characteristics, calibration, and effect on reclassification of subjects.

RESULTS

Variables that significantly added to the traditional Framingham profile included waist circumference, alcohol consumption, and physical activity. Continuous measures for blood pressure and fasting blood sugar were used instead of hypertension and diabetes. Ten-year event-free probabilities were 0.95 for the first quartile of GVRS, 0.89 for the second quartile, 0.79 for the third quartile, and 0.56 for the fourth quartile. The addition of behavioral factors in our model improved prediction of 10-year event rates compared with a model restricted to the traditional variables.

CONCLUSIONS

A GVRS that combines traditional, behavioral, and anthropometric risk factors; uses continuous variables for physiological parameters; and is applicable to nonwhite subjects could improve primary prevention strategies.

Evaluation of quantitative IFN-gamma response for risk stratification of active tuberculosis suspects

RATIONALE

The contribution of interferon-gamma release assays (IGRAs) to appropriate risk stratification of active tuberculosis suspects has not been studied.

OBJECTIVES

To determine whether the addition of quantitative IGRA results to a prediction model incorporating clinical criteria improves risk stratification of smear-negative-tuberculosis suspects.

METHODS

Clinical data from tuberculosis suspects evaluated by the San Francisco Department of Public Health Tuberculosis Control Clinic from March 2005 to February 2008 were reviewed. We excluded tuberculosis suspects who were acid fast-bacilli smear-positive, HIV-infected, or under 10 years of age. We developed a clinical prediction model for culture-positive disease and examined the benefit of adding quantitative interferon (IFN)-gamma results measured by QuantiFERON-TB Gold (Cellestis, Carnegie, Australia).

MEASUREMENTS AND MAIN RESULTS

Of 660 patients meeting eligibility criteria, 65 (10%) had culture-proven tuberculosis. The odds of active tuberculosis increased by 7% (95% confidence interval [CI], 3-11%) for each doubling of IFN-gamma level. The addition of quantitative IFN-gamma results to objective clinical data significantly improved model performance (c-statistic 0.71 vs. 0.78; P < 0.001) and correctly reclassified 32% of tuberculosis suspects (95% CI,11-52%; P < 0.001) into higher-risk or lower-risk categories. However, quantitative IFN-gamma results did not significantly improve appropriate risk reclassification beyond that provided by clinician assessment of risk (4%; 95% CI, -7 to +22%; P = 0.14).

CONCLUSIONS

Higher quantitative IFN-gamma results were associated with active tuberculosis, and added clinical value to a prediction model incorporating conventional risk factors. Although this benefit may be attenuated within highly experienced centers, the predictive accuracy of quantitative IFN-gamma levels should be evaluated in other settings.

Central obesity and cigarette smoking are key determinants of cardiovascular disease deaths in Australia: a public health perspective

BACKGROUND

Our objective is to develop a parsimonious model to predict coronary heart disease (CHD) and cardiovascular disease (CVD) deaths using individual components of the Framingham risk score plus measures of central obesity.

METHODS

15 year mortality follow-up of 8662 representative Australian adults in the National Heart Foundation Risk Factor Prevalence Survey of 1989, excluding those with a baseline history of heart disease, stroke or diabetes. Measures included blood pressure, fasting lipids, smoking history, body mass index (BMI), waist circumference (WC) and waist to hip ratio (WHR). Multivariable logistic regression was used to assess the effects of the Framingham risk variables and central obesity variables on cardiovascular disease mortality.

RESULTS

Smoking status, high density lipoprotein cholesterol (HDL-C) and the total cholesterol (TC) to HDL-C ratio were significant univariate predictors of CHD deaths. These together with systolic blood pressure were significant predictors of CVD deaths. The obesity measures of WC and WHR were significant univariate predictors but BMI was not. In multivariable analyses, only smoking status and waist to hip ratio were identified as key independent risk factors for CHD and CVD deaths, although TC to HDL-C ratio contributed minimally to CHD deaths. Receiver operator characteristic (ROC) curves for the Framingham risk score in comparison to the WHR plus smoking model were virtually identical, with no added effect of the lipid ratio.

CONCLUSION

The preferred model for predicting CHD and CVD deaths uses central obesity plus smoking with no added influence of measured lipids or blood pressure. A public health focus on identifying and modifying central obesity is at least as important as the measurement and treatment of lipids and hypertension.

Overview of risk prediction models in cardiovascular disease research

Many risk prediction models have been developed for cardiovascular diseases in different countries during the past three decades. However, there has not been consistent agreement regarding how to appropriately assess a risk prediction model, especially when new markers are added to an established risk prediction model. Researchers often use the area under the receiver operating characteristic curve (ROC) to assess the discriminatory ability of a risk prediction model. However, recent studies suggest that this method has serious limitations and cannot be the sole approach to evaluate the usefulness of a new marker in clinical and epidemiological studies. To overcome the shortcomings of this traditional method, new assessment methods have been proposed. The aim of this article is to overview various risk prediction models for cardiovascular diseases, to describe the receiver operating characteristic curve method and discuss some new assessment methods proposed recently. Some of the methods were illustrated with figures from a cardiovascular disease study in Australia.

Central obesity and multivariable cardiovascular risk as assessed by the Framingham prediction scores

To evaluate the role of measurements of central obesity in the multivariable prediction of cardiovascular risk using the Framingham risk scores, we studied 4,175 representative men from Australian cities, free of heart disease, stroke, and diabetes in 1989, and followed the cohort for mortality to 2004. Baseline lipids, blood pressure, and current cigarette smoking were recorded. Obesity was assessed by body mass index, waist circumference (WC), and waist-to-hip ratio (WHR) by strictly standardized methods. The Framingham equations were strong predictors of coronary heart disease (CHD) and cardiovascular disease (CVD) deaths. Of the obesity measurements, WHR and WC predicted deaths using Cox proportional hazards regression but body mass index did not. In the multivariable analyses, WHR was an independent predictor of CHD deaths, and WHR and WC were independent predictors of CVD deaths. There was little or no attenuation of hazard ratios for WHR and WC after correction for the Framingham scores. The 2 measurements of central obesity were more strongly predictive of CHD and CVD deaths in subjects at the lower levels of Framingham risk. In contrast, cigarette smoking risk appeared to contribute more in the higher Framingham risk categories. In conclusion, central obesity significantly and independently contributes to cardiovascular outcomes and to residual risk after accounting for the Framingham equations.

Coronary calcium as a predictor of coronary events in four racial or ethnic groups

BACKGROUND

In white populations, computed tomographic measurements of coronary-artery calcium predict coronary heart disease independently of traditional coronary risk factors. However, it is not known whether coronary-artery calcium predicts coronary heart disease in other racial or ethnic groups.

METHODS

We collected data on risk factors and performed scanning for coronary calcium in a population-based sample of 6722 men and women, of whom 38.6% were white, 27.6% were black, 21.9% were Hispanic, and 11.9% were Chinese. The study subjects had no clinical cardiovascular disease at entry and were followed for a median of 3.8 years.

RESULTS

There were 162 coronary events, of which 89 were major events (myocardial infarction or death from coronary heart disease). In comparison with participants with no coronary calcium, the adjusted risk of a coronary event was increased by a factor of 7.73 among participants with coronary calcium scores between 101 and 300 and by a factor of 9.67 among participants with scores above 300 (P<0.001 for both comparisons). Among the four racial and ethnic groups, a doubling of the calcium score increased the risk of a major coronary event by 15 to 35% and the risk of any coronary event by 18 to 39%. The areas under the receiver-operating-characteristic curves for the prediction of both major coronary events and any coronary event were higher when the calcium score was added to the standard risk factors.

CONCLUSIONS

The coronary calcium score is a strong predictor of incident coronary heart disease and provides predictive information beyond that provided by standard risk factors in four major racial and ethnic groups in the United States. No major differences among racial and ethnic groups in the predictive value of calcium scores were detected.

Estimation of 10-year risk of fatal cardiovascular disease and coronary heart disease in Iceland with results comparable with those of the Systematic Coronary Risk Evaluation project

BACKGROUND

No data are available on the comparison between an absolute 10-year risk of fatal cardiovascular disease (CVD) and coronary heart disease (CHD) morbidity using the risk assessments of the Systematic Coronary Risk Evaluation (SCORE) project.

DESIGN

Data from the prospective Reykjavik Study of 15,782 patients were used to estimate the 10-year risk of fatal CVD and CHD morbidity in Iceland.

METHODS

Survival to fatal CVD event was defined as in the SCORE project. Survival to CHD morbidity was defined as having a myocardial infarction, coronary artery bypass graft, or angioplasty. The statistical methodology of SCORE was used.

RESULTS

Relative risk in Iceland was comparable with SCORE results but baseline risk was similar to the low-risk version of SCORE, which contradicted previous suggestions for the countries of northern Europe. Correlation between absolute risk of CHD morbidity and risk for fatal CVD was high (r=0.96), resulting in similar ranking of individuals by risk and discriminatory capacity. This is the first published comparison between total fatal CVD risk and CHD morbidity in a population-based cohort using the current risk assessment guidelines of the European Societies on Coronary Prevention.

CONCLUSIONS

Risk for fatal CVD in Iceland has the same characteristics as those in a European nation with results varying in accordance with the SCORE project. The risk estimate to be used, CHD morbidity or fatal CVD, is a choice of clinical preference. The data, however, suggest that 5% high-risk threshold of fatal CVD corresponds to a 12% CHD-morbidity risk, which is a significant change from the conventional reference value of 20%.

Metabolic syndrome, dysglycaemia and vascular disease: making sense of the evidence

" 'Diagnosis' of metabolic syndrome by any current criteria is not needed and adds little to clinical practice. Attention and resources should be focused on the major modifiable risk factors and more should be done to engender sustainable lifestyle changes in all with vascular disease."

Waist circumference and BMI cut-off based on 10-year cardiovascular risk: evidence for "central pre-obesity"

OBJECTIVE

The objective was to assess the waist circumference (WC) cut-off point that best identifies a level of 10-year cardiovascular disease (CVD) risk with optimal balance of sensitivity and specificity in Chinese subjects according to their predicted 10-year CVD risk.

RESEARCH METHODS AND PROCEDURES

A community-based cross-sectional observational study involving 14,919 Hong Kong Chinese subjects. The 10-year CVD risk based on various prediction models was calculated. The projected WC cut-off points were then determined.

RESULTS

There were 4837 (32.4%) men and 10,082 (67.6%) women (mean age +/- standard deviation, 47.3 +/- 13.5 years; age range, 18 to 93 years; median age, 45.0 years). The mean optimal WC or BMI predicting a 15% to 30% 10-year CVD risk were 83 to 88 cm and 25 kg/m(2) for men, and 76 cm and 23 kg/m(2) for women, respectively. With WC >or=90 cm in men and >or=80 cm in women, the likelihood ratio at various WC cut-off points to develop a >or=20% 10-year CVD risk is 1.5 to 2.0 in men and 3.0 in women. The likelihood ratio was 1.5 in men with WC at 84 cm and in women at 70 cm.

DISCUSSION

Our results agree with the present guidelines on the definition of general and central obesity in Asia-Pacific regions. We propose the creation of an intermediate state of high WC, the "central pre-obesity" for Chinese men with WC >or=84 to 90 cm (>or=33 to 36 inches) and women with WC >or=74 to 80 cm (>or=29 to 32 inches). People with central pre-obesity, similar to those with overweight (BMI >or=23 to 25 kg/m(2)), already have an increased risk of co-morbidities.

Coronary risks among seafarers aboard German-flagged ships

OBJECTIVES

Cardiovascular diseases belong to the major causes of maritime service disablement (approximately 18%). The aim of this study was to investigate the frequency of coronary risk factors in seamen on vessels sailing under the German flag and to assess the risk of coronary heart disease (CHD) dependent on job-related factors.

METHODS

Within a medical surveillance program, a cross-sectional study with interview, blood sampling, and blood pressure measurements was conducted among a total of 205 male seafarers sailing under the German flag (response 84.9%). Due to missing blood analysis, 13 seamen were excluded. The predicted 10-year risk of an acute coronary event of a study subgroup of 45 German seafarers was compared to the corresponding risk of a sample of the German working population (PROCAM study).

RESULTS

In the total sample (n = 161), 55 seamen (34.2%) had at least three CHD risk factors. The most prominent independent CHD risk factors in seafarers were hypertension (49.7%), high triglycerides (41.6%), older age (39.8%), and smoking (37.3%). Compared with non-Europeans, European seafarers were about twice as likely to have more than three risk factors after adjusting for age [OR 2.4 (95% CI 1.01-4.55)]. Particularly engine room officers and galley/operating staff were at a higher coronary risk. After standardizing for age, the German seamen investigated showed a similar predicted 10-year CHD risk as the German population of about the same age working ashore of the PROCAM study.

CONCLUSIONS

The CHD risks in seafarers should be reduced by low-fat diets, anti-smoking campaigns and blood pressure control/treatment. In spite of the seafarers' regular medical surveillance examination, their CHD risk was comparable to a reference population working ashore. Our results support the hypothesis that working on vessels may augment the risk of CHD.

C-reactive protein in cardiovascular risk assessment: a review of the evidence

C-reactive protein (CRP) is an inflammatory biomarker that is strongly associated with coronary heart disease, inflammation, and the metabolic syndrome. Large-scale prospective cohort trials have shown that measurement of CRP may add predictive accuracy to the Framingham risk score, but interpretation of these data are conflicting. In the primary prevention setting, CRP can be used to reclassify patients in low or intermediate Framingham risk score groups to a higher risk category, thus making them eligible for more intensive pharmacologic interventions.

A coronary heart disease risk model for predicting the effect of potent antiretroviral therapy in HIV-1 infected men

BACKGROUND

Many HIV-infected patients on highly active antiretroviral therapy (HAART) experience metabolic complications including dyslipidaemia and insulin resistance, which may increase their coronary heart disease (CHD) risk. We developed a prognostic model for CHD tailored to the changes in risk factors observed in patients starting HAART.

METHODS

Data from five cohort studies (British Regional Heart Study, Caerphilly and Speedwell Studies, Framingham Offspring Study, Whitehall II) on 13,100 men aged 40-70 and 114,443 years of follow up were used. CHD was defined as myocardial infarction or death from CHD. Model fit was assessed using the Akaike Information Criterion; generalizability across cohorts was examined using internal-external cross-validation.

RESULTS

A parametric model based on the Gompertz distribution generalized best. Variables included in the model were systolic blood pressure, total cholesterol, high-density lipoprotein cholesterol, triglyceride, glucose, diabetes mellitus, body mass index and smoking status. Compared with patients not on HAART, the estimated CHD hazard ratio (HR) for patients on HAART was 1.46 (95% CI 1.15-1.86) for moderate and 2.48 (95% CI 1.76-3.51) for severe metabolic complications.

CONCLUSIONS

The change in the risk of CHD in HIV-infected men starting HAART can be estimated based on typical changes in risk factors, assuming that HRs estimated using data from non-infected men are applicable to HIV-infected men. Based on this model the risk of CHD is likely to increase, but increases may often be modest, and could be offset by lifestyle changes.

Prediction of first coronary events with the Framingham score: a systematic review

BACKGROUND

Uncertainty exists about the performance of the Framingham risk score when applied in different populations.

OBJECTIVE

We assessed calibration of the Framingham risk score (ie, relationship between predicted and observed coronary event rates) in US and non-US populations free of cardiovascular disease.

METHODS

We reviewed studies that evaluated the performance of the Framingham risk score to predict first coronary events in a validation cohort, as identified by Medline, EMBASE, BIOSIS, and Cochrane library searches (through August 2005). Two reviewers independently assessed 1496 studies for eligibility, extracted data, and performed quality assessment using predefined forms.

RESULTS

We included 25 validation cohorts of different population groups (n = 128,000) in our main analysis. Calibration varied over a wide range from under- to overprediction of absolute risk by factors of 0.57 to 2.7. Risk prediction for 7 cohorts (n = 18658) from the United States, Australia, and New Zealand was well calibrated (corresponding figures: 0.87-1.08; for the 5 biggest cohorts). The estimated population risks for first coronary events were strongly associated (goodness of fit: R2 = 0.84) and in good agreement with observed risks (coefficient for predicted risk: beta = 0.84; 95% CI 0.41-1.26). In 18 European cohorts (n = 109499), the corresponding figures indicated close association (R2 = 0.72) but substantial overprediction (beta = 0.58, 95% CI 0.39-0.77). The risk score was well calibrated on the intercept for both population clusters.

CONCLUSION

The Framingham score is well calibrated to predict first coronary events in populations from the United States, Australia, and New Zealand. Overestimation of absolute risk in European cohorts requires recalibration procedures.

Cardiovascular risk prediction tools for populations in Asia

BACKGROUND

Cardiovascular risk equations are traditionally derived from the Framingham Study. The accuracy of this approach in Asian populations, where resources for risk factor measurement may be limited, is unclear.

OBJECTIVE

To compare "low-information" equations (derived using only age, systolic blood pressure, total cholesterol and smoking status) derived from the Framingham Study with those derived from the Asian cohorts, on the accuracy of cardiovascular risk prediction.

DESIGN

Separate equations to predict the 8-year risk of a cardiovascular event were derived from Asian and Framingham cohorts. The performance of these equations, and a subsequently "recalibrated" Framingham equation, were evaluated among participants from independent Chinese cohorts.

SETTING

Six cohort studies from Japan, Korea and Singapore (Asian cohorts); six cohort studies from China; the Framingham Study from the US.

PARTICIPANTS

172,077 participants from the Asian cohorts; 25,682 participants from Chinese cohorts and 6053 participants from the Framingham Study.

MAIN RESULTS

In the Chinese cohorts, 542 cardiovascular events occurred during 8 years of follow-up. Both the Asian cohorts and the Framingham equations discriminated cardiovascular risk well in the Chinese cohorts; the area under the receiver-operator characteristic curve was at least 0.75 for men and women. However, the Framingham risk equation systematically overestimated risk in the Chinese cohorts by an average of 276% among men and 102% among women. The corresponding average overestimation using the Asian cohorts equation was 11% and 10%, respectively. Recalibrating the Framingham risk equation using cardiovascular disease incidence from the non-Chinese Asian cohorts led to an overestimation of risk by an average of 4% in women and underestimation of risk by an average of 2% in men.

INTERPRETATION

A low-information Framingham cardiovascular risk prediction tool, which, when recalibrated with contemporary data, is likely to estimate future cardiovascular risk with similar accuracy in Asian populations as tools developed from data on local cohorts.