Background To help adapt cardiovascular disease risk prediction approaches to low-income and middle-income countries, WHO has convened an effort to develop, evaluate, and illustrate revised risk models. Here, we report the derivation, validation, and illustration of the revised WHO cardiovascular disease risk prediction charts that have been adapted to the circumstances of 21 global regions. Methods In this model revision initiative, we derived 10-year risk prediction models for fatal and non-fatal cardiovascular disease (ie, myocardial infarction and stroke) using individual participant data from the Emerging Risk Factors Collaboration. Models included information on age, smoking status, systolic blood pressure, history of diabetes, and total cholesterol. For derivation, we included participants aged 40-80 years without a known baseline history of cardiovascular disease, who were followed up until the first myocardial infarction, fatal coronary heart disease, or stroke event. We recalibrated models using age-specific and sex-specific incidences and risk factor values available from 21 global regions. For external validation, we analysed individual participant data from studies distinct from those used in model derivation. We illustrated models by analysing data on a further 123 743 individuals from surveys in 79 countries collected with the WHO STEPwise Approach to Surveillance. Findings Our risk model derivation involved 376 177 individuals from 85 cohorts, and 19 333 incident cardiovascular events recorded during 10 years of follow-up. The derived risk prediction models discriminated well in external validation cohorts (19 cohorts, 1 096 061 individuals, 25 950 cardiovascular disease events), with Harrell's C indices ranging from 0•685 (95% CI 0•629-0•741) to 0•833 (0•783-0•882). For a given risk factor profile, we found substantial variation across global regions in the estimated 10-year predicted risk. For example, estimated cardiovascular disease risk for a 60-year-old male smoker without diabetes and with systolic blood pressure of 140 mm Hg and total cholesterol of 5 mmol/L ranged from 11% in Andean Latin America to 30% in central Asia. When applied to data from 79 countries (mostly low-income and middle-income countries), the proportion of individuals aged 40-64 years estimated to be at greater than 20% risk ranged from less than 1% in Uganda to more than 16% in Egypt. Interpretation We have derived, calibrated, and validated new WHO risk prediction models to estimate cardiovascular disease risk in 21 Global Burden of Disease regions. The widespread use of these models could enhance the accuracy, practicability, and sustainability of efforts to reduce the burden of cardiovascular disease worldwide.

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IMPORTANCEThe elimination of racial and ethnic differences in health status and health care access is a US goal, but it is unclear whether the country has made progress over the last 2 decades. OBJECTIVE To determine 20-year trends in the racial and ethnic differences in self-reported measures of health status and health care access and affordability among adults in the US.

Aims There is debate about the optimum algorithm for cardiovascular disease (CVD) risk estimation. We conducted head-to-head comparisons of four algorithms recommended by primary prevention guidelines, before and after “re-calibration”, a method that adapts risk algorithms to take account of differences in the risk characteristics of the populations being studied. Methods and Results Using individual-participant data on 360,737 participants without CVD at baseline in 86 prospective studies from 22 countries, we compared the Framingham Risk Score (FRS), Systematic Coronary Risk Evaluation (SCORE), Pooled Cohort Equations (PCE), and Reynolds Risk Score (RRS). We calculated measures of risk discrimination and calibration, and modelled clinical implications of initiating statin therapy in people judged to be at “high” 10-year CVD risk. Original risk algorithms were re-calibrated using the risk factor profile and CVD incidence of target populations. The four algorithms had similar risk discrimination. Before re-calibration, FRS, SCORE and PCE over-predicted CVD risk on average by 10%, 52%, and 41%, respectively, while RRS under-predicted by 10%. Original versions of algorithms classified 29-39% of individuals aged ≥40 years as high-risk. By contrast, re-calibration reduced this proportion to 22-24% for every algorithm. We estimated that to prevent one CVD event, it would be necessary to initiate statin therapy in 44-51 such individuals using original algorithms, in contrast to 37-39 individuals with re-calibrated algorithms. Conclusion Before re-calibration, the clinical performance of four widely used CVD risk algorithms varied substantially. By contrast, simple re-calibration nearly equalised their performance and improved modelled targeting of preventive action to clinical need.

The World Health Organization (WHO) Model List of Essential Medicines (EML) is a key tool for improving global access to medicines for all conditions, including cardiovascular diseases (CVDs). The WHO EML is used by member states to determine their national essential medicine lists and policies and to guide procurement of medicines in the public sector. Here, we describe our efforts to modernize the EML for global CVD prevention and control. We review the recent history of applications to add, delete, and change indications for CVD medicines, with the aim of aligning the list with contemporary clinical practice guidelines. We have identified 4 issues that affect decisions for the EML and may strengthen future applications: 1) cost and cost-effectiveness; 2) presence in clinical practice guidelines; 3) feedback loops; and 4) community engagement. We share our lessons to stimulate others in the global CVD community to embark on similar efforts.