Laboratory-based and office-based risk scores and charts to predict 10-year risk of cardiovascular disease in 182 countries

a pooled analysis of prospective cohorts and health surveys

Peter Ueda, Mark Woodward, Yuan Lu, Kaveh Hajifathalian, Rihab Al-Wotayan, Carlos A Aguilar-Salinas, Alireza Ahmadvand, Fereidoun Azizi, James Bentham, Renata Cifkova, Mariachiara Di Cesare, Louise Eriksen, Farshad Farzadfar, Trevor S. Ferguson, Nayu Ikeda, Davood Khalili, Young-Ho Khang, Vera Lanska, Luz M. León-Muñoz, Dianna J. Magliano & 16 others Paula Margozzini, Kelias P. Msyamboza, Gerald Mutungi, Kyungwon Oh, Sophal Oum, Fernando Rodríguez-Artalejo, Rosalba Rojas-Martinez, Gonzalo Valdivia, Rainford J. Wilks, Jonathan E. Shaw, Gretchen A Stevens, Janne S. Tolstrup, Bin Zhou, Joshua A Salomon, Majid Ezzati, Goodarz Danaei

Research output: Contribution to journalArticleResearchpeer-review

26 Citations (Scopus)

Abstract

Background Worldwide implementation of risk-based cardiovascular disease (CVD) prevention requires risk prediction tools that are contemporarily recalibrated for the target country and can be used where laboratory measurements are unavailable. We present two cardiovascular risk scores, with and without laboratory-based measurements, and the corresponding risk charts for 182 countries to predict 10-year risk of fatal and non-fatal CVD in adults aged 40–74 years. Methods Based on our previous laboratory-based prediction model (Globorisk), we used data from eight prospective studies to estimate coefficients of the risk equations using proportional hazard regressions. The laboratory-based risk score included age, sex, smoking, blood pressure, diabetes, and total cholesterol; in the non-laboratory (office-based) risk score, we replaced diabetes and total cholesterol with BMI. We recalibrated risk scores for each sex and age group in each country using country-specific mean risk factor levels and CVD rates. We used recalibrated risk scores and data from national surveys (using data from adults aged 40–64 years) to estimate the proportion of the population at different levels of CVD risk for ten countries from different world regions as examples of the information the risk scores provide; we applied a risk threshold for high risk of at least 10% for high-income countries (HICs) and at least 20% for low-income and middle-income countries (LMICs) on the basis of national and international guidelines for CVD prevention. We estimated the proportion of men and women who were similarly categorised as high risk or low risk by the two risk scores. Findings Predicted risks for the same risk factor profile were generally lower in HICs than in LMICs, with the highest risks in countries in central and southeast Asia and eastern Europe, including China and Russia. In HICs, the proportion of people aged 40–64 years at high risk of CVD ranged from 1% for South Korean women to 42% for Czech men (using a ≥10% risk threshold), and in low-income countries ranged from 2% in Uganda (men and women) to 13% in Iranian men (using a ≥20% risk threshold). More than 80% of adults were similarly classified as low or high risk by the laboratory-based and office-based risk scores. However, the office-based model substantially underestimated the risk among patients with diabetes. Interpretation Our risk charts provide risk assessment tools that are recalibrated for each country and make the estimation of CVD risk possible without using laboratory-based measurements. Funding National Institutes of Health.

Original languageEnglish
Pages (from-to)196-213
Number of pages18
JournalThe Lancet Diabetes and Endocrinology
Volume5
Issue number3
DOIs
Publication statusPublished - 1 Mar 2017
Externally publishedYes

Cite this

Ueda, Peter ; Woodward, Mark ; Lu, Yuan ; Hajifathalian, Kaveh ; Al-Wotayan, Rihab ; Aguilar-Salinas, Carlos A ; Ahmadvand, Alireza ; Azizi, Fereidoun ; Bentham, James ; Cifkova, Renata ; Di Cesare, Mariachiara ; Eriksen, Louise ; Farzadfar, Farshad ; Ferguson, Trevor S. ; Ikeda, Nayu ; Khalili, Davood ; Khang, Young-Ho ; Lanska, Vera ; León-Muñoz, Luz M. ; Magliano, Dianna J. ; Margozzini, Paula ; Msyamboza, Kelias P. ; Mutungi, Gerald ; Oh, Kyungwon ; Oum, Sophal ; Rodríguez-Artalejo, Fernando ; Rojas-Martinez, Rosalba ; Valdivia, Gonzalo ; Wilks, Rainford J. ; Shaw, Jonathan E. ; Stevens, Gretchen A ; Tolstrup, Janne S. ; Zhou, Bin ; Salomon, Joshua A ; Ezzati, Majid ; Danaei, Goodarz. / Laboratory-based and office-based risk scores and charts to predict 10-year risk of cardiovascular disease in 182 countries : a pooled analysis of prospective cohorts and health surveys. In: The Lancet Diabetes and Endocrinology. 2017 ; Vol. 5, No. 3. pp. 196-213.
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abstract = "Background Worldwide implementation of risk-based cardiovascular disease (CVD) prevention requires risk prediction tools that are contemporarily recalibrated for the target country and can be used where laboratory measurements are unavailable. We present two cardiovascular risk scores, with and without laboratory-based measurements, and the corresponding risk charts for 182 countries to predict 10-year risk of fatal and non-fatal CVD in adults aged 40–74 years. Methods Based on our previous laboratory-based prediction model (Globorisk), we used data from eight prospective studies to estimate coefficients of the risk equations using proportional hazard regressions. The laboratory-based risk score included age, sex, smoking, blood pressure, diabetes, and total cholesterol; in the non-laboratory (office-based) risk score, we replaced diabetes and total cholesterol with BMI. We recalibrated risk scores for each sex and age group in each country using country-specific mean risk factor levels and CVD rates. We used recalibrated risk scores and data from national surveys (using data from adults aged 40–64 years) to estimate the proportion of the population at different levels of CVD risk for ten countries from different world regions as examples of the information the risk scores provide; we applied a risk threshold for high risk of at least 10{\%} for high-income countries (HICs) and at least 20{\%} for low-income and middle-income countries (LMICs) on the basis of national and international guidelines for CVD prevention. We estimated the proportion of men and women who were similarly categorised as high risk or low risk by the two risk scores. Findings Predicted risks for the same risk factor profile were generally lower in HICs than in LMICs, with the highest risks in countries in central and southeast Asia and eastern Europe, including China and Russia. In HICs, the proportion of people aged 40–64 years at high risk of CVD ranged from 1{\%} for South Korean women to 42{\%} for Czech men (using a ≥10{\%} risk threshold), and in low-income countries ranged from 2{\%} in Uganda (men and women) to 13{\%} in Iranian men (using a ≥20{\%} risk threshold). More than 80{\%} of adults were similarly classified as low or high risk by the laboratory-based and office-based risk scores. However, the office-based model substantially underestimated the risk among patients with diabetes. Interpretation Our risk charts provide risk assessment tools that are recalibrated for each country and make the estimation of CVD risk possible without using laboratory-based measurements. Funding National Institutes of Health.",
author = "Peter Ueda and Mark Woodward and Yuan Lu and Kaveh Hajifathalian and Rihab Al-Wotayan and Aguilar-Salinas, {Carlos A} and Alireza Ahmadvand and Fereidoun Azizi and James Bentham and Renata Cifkova and {Di Cesare}, Mariachiara and Louise Eriksen and Farshad Farzadfar and Ferguson, {Trevor S.} and Nayu Ikeda and Davood Khalili and Young-Ho Khang and Vera Lanska and Le{\'o}n-Mu{\~n}oz, {Luz M.} and Magliano, {Dianna J.} and Paula Margozzini and Msyamboza, {Kelias P.} and Gerald Mutungi and Kyungwon Oh and Sophal Oum and Fernando Rodr{\'i}guez-Artalejo and Rosalba Rojas-Martinez and Gonzalo Valdivia and Wilks, {Rainford J.} and Shaw, {Jonathan E.} and Stevens, {Gretchen A} and Tolstrup, {Janne S.} and Bin Zhou and Salomon, {Joshua A} and Majid Ezzati and Goodarz Danaei",
year = "2017",
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pages = "196--213",
journal = "The Lancet Diabetes and Endocrinology",
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Ueda, P, Woodward, M, Lu, Y, Hajifathalian, K, Al-Wotayan, R, Aguilar-Salinas, CA, Ahmadvand, A, Azizi, F, Bentham, J, Cifkova, R, Di Cesare, M, Eriksen, L, Farzadfar, F, Ferguson, TS, Ikeda, N, Khalili, D, Khang, Y-H, Lanska, V, León-Muñoz, LM, Magliano, DJ, Margozzini, P, Msyamboza, KP, Mutungi, G, Oh, K, Oum, S, Rodríguez-Artalejo, F, Rojas-Martinez, R, Valdivia, G, Wilks, RJ, Shaw, JE, Stevens, GA, Tolstrup, JS, Zhou, B, Salomon, JA, Ezzati, M & Danaei, G 2017, 'Laboratory-based and office-based risk scores and charts to predict 10-year risk of cardiovascular disease in 182 countries: a pooled analysis of prospective cohorts and health surveys', The Lancet Diabetes and Endocrinology, vol. 5, no. 3, pp. 196-213. https://doi.org/10.1016/S2213-8587(17)30015-3

Laboratory-based and office-based risk scores and charts to predict 10-year risk of cardiovascular disease in 182 countries : a pooled analysis of prospective cohorts and health surveys. / Ueda, Peter; Woodward, Mark; Lu, Yuan; Hajifathalian, Kaveh; Al-Wotayan, Rihab; Aguilar-Salinas, Carlos A; Ahmadvand, Alireza; Azizi, Fereidoun; Bentham, James; Cifkova, Renata; Di Cesare, Mariachiara; Eriksen, Louise; Farzadfar, Farshad; Ferguson, Trevor S.; Ikeda, Nayu; Khalili, Davood; Khang, Young-Ho; Lanska, Vera; León-Muñoz, Luz M.; Magliano, Dianna J.; Margozzini, Paula; Msyamboza, Kelias P.; Mutungi, Gerald; Oh, Kyungwon; Oum, Sophal; Rodríguez-Artalejo, Fernando; Rojas-Martinez, Rosalba; Valdivia, Gonzalo; Wilks, Rainford J.; Shaw, Jonathan E.; Stevens, Gretchen A; Tolstrup, Janne S.; Zhou, Bin; Salomon, Joshua A; Ezzati, Majid; Danaei, Goodarz.

In: The Lancet Diabetes and Endocrinology, Vol. 5, No. 3, 01.03.2017, p. 196-213.

Research output: Contribution to journalArticleResearchpeer-review

TY - JOUR

T1 - Laboratory-based and office-based risk scores and charts to predict 10-year risk of cardiovascular disease in 182 countries

T2 - a pooled analysis of prospective cohorts and health surveys

AU - Ueda, Peter

AU - Woodward, Mark

AU - Lu, Yuan

AU - Hajifathalian, Kaveh

AU - Al-Wotayan, Rihab

AU - Aguilar-Salinas, Carlos A

AU - Ahmadvand, Alireza

AU - Azizi, Fereidoun

AU - Bentham, James

AU - Cifkova, Renata

AU - Di Cesare, Mariachiara

AU - Eriksen, Louise

AU - Farzadfar, Farshad

AU - Ferguson, Trevor S.

AU - Ikeda, Nayu

AU - Khalili, Davood

AU - Khang, Young-Ho

AU - Lanska, Vera

AU - León-Muñoz, Luz M.

AU - Magliano, Dianna J.

AU - Margozzini, Paula

AU - Msyamboza, Kelias P.

AU - Mutungi, Gerald

AU - Oh, Kyungwon

AU - Oum, Sophal

AU - Rodríguez-Artalejo, Fernando

AU - Rojas-Martinez, Rosalba

AU - Valdivia, Gonzalo

AU - Wilks, Rainford J.

AU - Shaw, Jonathan E.

AU - Stevens, Gretchen A

AU - Tolstrup, Janne S.

AU - Zhou, Bin

AU - Salomon, Joshua A

AU - Ezzati, Majid

AU - Danaei, Goodarz

PY - 2017/3/1

Y1 - 2017/3/1

N2 - Background Worldwide implementation of risk-based cardiovascular disease (CVD) prevention requires risk prediction tools that are contemporarily recalibrated for the target country and can be used where laboratory measurements are unavailable. We present two cardiovascular risk scores, with and without laboratory-based measurements, and the corresponding risk charts for 182 countries to predict 10-year risk of fatal and non-fatal CVD in adults aged 40–74 years. Methods Based on our previous laboratory-based prediction model (Globorisk), we used data from eight prospective studies to estimate coefficients of the risk equations using proportional hazard regressions. The laboratory-based risk score included age, sex, smoking, blood pressure, diabetes, and total cholesterol; in the non-laboratory (office-based) risk score, we replaced diabetes and total cholesterol with BMI. We recalibrated risk scores for each sex and age group in each country using country-specific mean risk factor levels and CVD rates. We used recalibrated risk scores and data from national surveys (using data from adults aged 40–64 years) to estimate the proportion of the population at different levels of CVD risk for ten countries from different world regions as examples of the information the risk scores provide; we applied a risk threshold for high risk of at least 10% for high-income countries (HICs) and at least 20% for low-income and middle-income countries (LMICs) on the basis of national and international guidelines for CVD prevention. We estimated the proportion of men and women who were similarly categorised as high risk or low risk by the two risk scores. Findings Predicted risks for the same risk factor profile were generally lower in HICs than in LMICs, with the highest risks in countries in central and southeast Asia and eastern Europe, including China and Russia. In HICs, the proportion of people aged 40–64 years at high risk of CVD ranged from 1% for South Korean women to 42% for Czech men (using a ≥10% risk threshold), and in low-income countries ranged from 2% in Uganda (men and women) to 13% in Iranian men (using a ≥20% risk threshold). More than 80% of adults were similarly classified as low or high risk by the laboratory-based and office-based risk scores. However, the office-based model substantially underestimated the risk among patients with diabetes. Interpretation Our risk charts provide risk assessment tools that are recalibrated for each country and make the estimation of CVD risk possible without using laboratory-based measurements. Funding National Institutes of Health.

AB - Background Worldwide implementation of risk-based cardiovascular disease (CVD) prevention requires risk prediction tools that are contemporarily recalibrated for the target country and can be used where laboratory measurements are unavailable. We present two cardiovascular risk scores, with and without laboratory-based measurements, and the corresponding risk charts for 182 countries to predict 10-year risk of fatal and non-fatal CVD in adults aged 40–74 years. Methods Based on our previous laboratory-based prediction model (Globorisk), we used data from eight prospective studies to estimate coefficients of the risk equations using proportional hazard regressions. The laboratory-based risk score included age, sex, smoking, blood pressure, diabetes, and total cholesterol; in the non-laboratory (office-based) risk score, we replaced diabetes and total cholesterol with BMI. We recalibrated risk scores for each sex and age group in each country using country-specific mean risk factor levels and CVD rates. We used recalibrated risk scores and data from national surveys (using data from adults aged 40–64 years) to estimate the proportion of the population at different levels of CVD risk for ten countries from different world regions as examples of the information the risk scores provide; we applied a risk threshold for high risk of at least 10% for high-income countries (HICs) and at least 20% for low-income and middle-income countries (LMICs) on the basis of national and international guidelines for CVD prevention. We estimated the proportion of men and women who were similarly categorised as high risk or low risk by the two risk scores. Findings Predicted risks for the same risk factor profile were generally lower in HICs than in LMICs, with the highest risks in countries in central and southeast Asia and eastern Europe, including China and Russia. In HICs, the proportion of people aged 40–64 years at high risk of CVD ranged from 1% for South Korean women to 42% for Czech men (using a ≥10% risk threshold), and in low-income countries ranged from 2% in Uganda (men and women) to 13% in Iranian men (using a ≥20% risk threshold). More than 80% of adults were similarly classified as low or high risk by the laboratory-based and office-based risk scores. However, the office-based model substantially underestimated the risk among patients with diabetes. Interpretation Our risk charts provide risk assessment tools that are recalibrated for each country and make the estimation of CVD risk possible without using laboratory-based measurements. Funding National Institutes of Health.

UR - http://www.scopus.com/inward/record.url?scp=85010190596&partnerID=8YFLogxK

U2 - 10.1016/S2213-8587(17)30015-3

DO - 10.1016/S2213-8587(17)30015-3

M3 - Article

VL - 5

SP - 196

EP - 213

JO - The Lancet Diabetes and Endocrinology

JF - The Lancet Diabetes and Endocrinology

SN - 2213-8587

IS - 3

ER -