World Health Organization cardiovascular disease risk charts: revised models to estimate risk in 21 global regions.
WHO CVD Risk Chart Working Group,
The Lancet. Global health
MetadataShow full item record
WHO CVD Risk Chart Working Group,. (2019). World Health Organization cardiovascular disease risk charts: revised models to estimate risk in 21 global regions.. The Lancet. Global health, 7 (10), e1332-e1345. https://doi.org/10.1016/s2214-109x(19)30318-3
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. Funding World Health Organization, British Heart Foundation (BHF), BHF Cambridge Centre for Research Excellence, UK Medical Research Council, and National Institute for Health Research.
WHO CVD Risk Chart Working Group, Humans, Cardiovascular Diseases, Risk Assessment, Risk Factors, Prospective Studies, Adult, Aged, Aged, 80 and over, Middle Aged, World Health Organization, Egypt, Uganda, Female, Male
This work was commissioned to the coordinating center (Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK) by WHO to revise the 2007 WHO–International Society of Hypertension cardiovascular disease risk prediction charts and was done through an informal technical working group convened by WHO. The coordinating centre was supported by underpinning funding from the British Heart Foundation (BHF; SP/09/002, RG/13/13/30194, and RG/18/13/33946), BHF Cambridge Centre for Research Excellence (RE/13/6/30180), UK Medical Research Council (MR/L003120/1), and the National Institute for Health Research (NIHR; Cambridge Biomedical Research Centre at the Cambridge University Hospitals NHS Foundation Trust). This work was also supported by Health Data Research UK, which is funded by the UK Medical Research Council, Engineering and Physical Sciences Research Council, Economic and Social Research Council, Department of Health and Social Care (England), Chief Scientist Office of the Scottish Government Health and Social Care Directorates, Health and Social Care Research and Development Division (Welsh Government), Public Health Agency (Northern Ireland), BHF, and Wellcome. JD is supported by a BHF Personal Professorship and an NIHR Senior Investigator Award. The views expressed are those of the authors and not necessarily those of the NHS, the NIHR, or the Department of Health and Social Care. This research has been done using the UK Biobank Resource under application number 26865. The coordinating centre provides links to websites of the component studies (or consortia), many of which describe their funding.
British Heart Foundation (RG/13/13/30194)
Cambridge University Hospitals NHS Foundation Trust (CUH) (unknown)
British Heart Foundation (CH/12/2/29428)
British Heart Foundation (RE/13/6/30180)
Department of Health (via National Institute for Health Research (NIHR)) (NF-SI-0617-10149)
British Heart Foundation (RG/18/13/33946)
External DOI: https://doi.org/10.1016/s2214-109x(19)30318-3
This record's URL: https://www.repository.cam.ac.uk/handle/1810/294950
Creative Commons Attribution
Licence URL: https://creativecommons.org/licenses/by/4.0/