Abstract
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.
Original language | English |
---|---|
Pages (from-to) | e1332-e1345 |
Journal | The Lancet Global Health |
Volume | 7 |
Issue number | 10 |
DOIs | |
Publication status | Published - 1 Oct 2019 |
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In: The Lancet Global Health, Vol. 7, No. 10, 01.10.2019, p. e1332-e1345.
Research output: Contribution to journal › Article › Academic › peer-review
TY - JOUR
T1 - World Health Organization cardiovascular disease risk charts
T2 - revised models to estimate risk in 21 global regions
AU - Kaptoge, Stephen
AU - Pennells, Lisa
AU - De Bacquer, Dirk
AU - Cooney, Marie Therese
AU - Kavousi, Maryam
AU - Stevens, Gretchen
AU - Riley, Leanne Margaret
AU - Savin, Stefan
AU - Khan, Taskeen
AU - Altay, Servet
AU - Amouyel, Philippe
AU - Assmann, Gerd
AU - Bell, Steven
AU - Ben-Shlomo, Yoav
AU - Berkman, Lisa
AU - Beulens, Joline W.
AU - Björkelund, Cecilia
AU - Blaha, Michael
AU - Blazer, Dan G.
AU - Bolton, Thomas
AU - Bonita Beaglehole, Ruth
AU - Brenner, Hermann
AU - Brunner, Eric J.
AU - Casiglia, Edoardo
AU - Chamnan, Parinya
AU - Choi, Yeun Hyang
AU - Chowdry, Rajiv
AU - Coady, Sean
AU - Crespo, Carlos J.
AU - Cushman, Mary
AU - Dagenais, Gilles R.
AU - D'Agostino, Ralph B.
AU - Daimon, Makoto
AU - Davidson, Karina W.
AU - Engström, Gunnar
AU - Ford, Ian
AU - Gallacher, John
AU - Gansevoort, Ron T.
AU - Gaziano, Thomas Andrew
AU - Giampaoli, Simona
AU - Grandits, Greg
AU - Grimsgaard, Sameline
AU - Grobbee, Diederick E.
AU - Gudnason, Vilmundur
AU - Guo, Qi
AU - Tolonen, Hanna
AU - Humphries, Steve
AU - Iso, Hiroyasu
AU - Jukema, J. Wouter
AU - Moons, Karel G.M.
N1 - Funding Information: SK reports grants from UK Medical Research Council, British Heart Foundation, and UK National Institute of Health Research, during the conduct of the study. PA reports personal fees from Servier, Total, Genoscreen, and Fondation Alzheimer, outside the submitted work. MJB reports grants from US National Institutes of Health (NIH), US Food and Drug Administration (FDA), American Heart Association, Aetna Foundation, and Amgen Foundation; and personal fees from Amgen Foundation Sanofi, Regeneron, Novartis, Novo Nordisk, and Bayer, outside the submitted work. TAG reports grants from Novartis, United Healthcare, and NIH; and personal fees from Teva and Takeda, outside the submitted work. SH reports grants from the British Heart Foundation (PG08/008), during the conduct of the study. JWJ (and his department) has received research grants from or was speaker (with or without lecture fees) on Continuing Medical Education-accredited meetings sponsored by Amgen, Athera, AstraZeneca, Biotronik, Boston Scientific, Daiichi Sankyo, Lilly, Medtronic, Merck-Schering-Plough, Pfizer, Roche, Sanofi Aventis, The Medicine Company, Netherlands Heart Foundation, CardioVascular Research the Netherlands, Interuniversity Cardiology Institute of the Netherlands, and the European Community Framework KP7 Programme, during the conduct of the study. HMK reports grants from Medtronic and FDA, Medtronic and Johnson and Johnson, and Shenzhen Center for Health Information; personal fees from National Center for Cardiovascular Disease in Beijing, UnitedHealth, IBM Watson Health, Element Science, Aetna, Arnold & Porter, Ben C Martin Law Firm, and Facebook; ownership (with spouse) of Hugo; and contracts from the Centers for Medicare & Medicaid Services, outside the submitted work. WK reports personal fees from AstraZeneca, Novartis, Pfizer, The Medicines Company, DalCor, Kowa, Amgen, Sanofi, Berlin-Chemie, Roche Diagnostics, Beckmann, Singulex and Abbott; and non-financial support from Roche Diagnostics, Beckmann, Singulex and Abbott, outside the submitted work. PJN reports grants from NIH, during the conduct of the study. AP reports grants from Australian National Health and Medical Research Council (NHMRC), during the conduct of the study. PMR reports grants from Novartis, Amgen, Pfizer, and Kowa; and personal fees from Novartis, Pfizer, AstraZeneca, Merck, outside the submitted work. RR reports grants from Sanofi, Eli Lilly, MSD, Amgen, AstraZeneca, and Servier; personal fees from Sanofi, Eli Lilly, MSD, Novo Nordisk, Physiogenex, AstraZeneca, Abbott, Medtronic, and Servier; and non-financial support from Sanofi and Novo Nordisk, outside the submitted work. JS is an Advisory board member for Itrim. JES reports grants from Commonwealth Department of Health and Aged Care, Abbott Australasia, Alphapharm, AstraZeneca, Aventis Pharmaceutical, Bristol-Myers Squibb Pharmaceuticals, Eli Lilly (Aust), GlaxoSmithKline, Janssen-Cilag (Aust), Merck Lipha, Merck Sharp & Dohme (Aust), Novartis Pharmaceutical (Aust), Novo Nordisk Pharmaceutical, Pharmacia and Upjohn, Pfizer, Sanofi Synthelabo, Servier Laboratories (Aust), Australian Kidney Foundation, and Diabetes Australia, during the conduct of the study; and personal fees from AstraZeneca, Mylan, Boehringer Ingelheim, Sanofi, Merck Sharp & Dohme, Novo Nordisk and Eli Lilly, outside the submitted work. VS reports a research collaboration with funding to their institute from Bayer, a conference trip from Novo Nordisk, and personal fees from Novo Nordisk, outside the submitted work. MW reports personal fees from Amgen and Kirin, outside the submitted work. ME reports a charitable grant from AstraZeneca Young Health Programme, and personal fees from Prudential, Scor, and Third Bridge, all outside the submitted work. RJ reports grants from Health Research Council of New Zealand, during the conduct of the study. JD report grants from Merck Sharp & Dohme, Novartis, British Heart Foundation, European Research Council, National Institute for Health Research (NIHR), National Health Service (NHS) Blood and Transplant, Pfizer, UK MRC, Wellcome Trust, and AstraZeneca; personal fees from Merck Sharp & Dohme and Novartis; and non-financial support from Merck Sharp & Dohme and Novartis, outside the submitted work. EDA reports grants from NHS Blood and Transplant, British Heart Foundation, UK Medical Research Council, and NIHR, outside the submitted work. All other members of the writing committee declare no competing interests. Funding Information: 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. Funding Information: 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. Publisher Copyright: © 2019 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license
PY - 2019/10/1
Y1 - 2019/10/1
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85072221516&partnerID=8YFLogxK
U2 - 10.1016/S2214-109X(19)30318-3
DO - 10.1016/S2214-109X(19)30318-3
M3 - Article
C2 - 31488387
AN - SCOPUS:85072221516
SN - 2214-109X
VL - 7
SP - e1332-e1345
JO - The Lancet Global Health
JF - The Lancet Global Health
IS - 10
ER -