Multinational validation of the PREVENT and SCORE2 cardiovascular risk equations across 6.4 million individuals

Brendon L. Neuen; Rupert W. Major; Morgan E. Grams; Yingying Sang; Josef Coresh; Shoshana H. Ballew; Aditya Surapaneni; Natalia Alencar de Pinho; Johan Ärnlöv; Clare Arnott; Samira Bell; Jarett D. Berry; Hermann Brenner; Elizabeth L. Ciemins; Alexander R Chang; Mary Cushman; James A de Lemos; Juan Miguel Diaz-Tocados; Alfredo E. Farjat; Robert A. Fletcher; Ron T. Gansevoort; Hiddo J. L. Heerspink; William G. Herrington; Chuan Hong; Edward J. Horwitz; Shih-Jen Hwang; Simerjot K. Jassal; Philip A. Kalra; Ronit Katz; Sadiya S. Khan; Csaba P Kovesdy; Florian Kronenberg; Jennifer S. Lees; Donald M. Lloyd-Jones; Jose Geraldo Mill; David M. J. Naimark; Chiadi Ndumele; Kevan R. Polkinghorne; Bruce M. Psaty; Patrick Schloemer; Michael G. Shlipak; Prabin Shrestha; Zean Song; Natalie D. Staplin; Dominik Steubl; Priya Vart; Frank L. J. Visseren; Mark Woodward; Kazumasa Yamagishi; Bessie A. Young; Charumathi Sabanayagam; José M. Valdivielso

doi:10.1038/s41591-026-04437-z

Multinational validation of the PREVENT and SCORE2 cardiovascular risk equations across 6.4 million individuals

Brendon L. Neuen
, Rupert W. Major
, Morgan E. Grams (Lead / Corresponding author)
, Yingying Sang
, Josef Coresh (Lead / Corresponding author)
, Shoshana H. Ballew
, Aditya Surapaneni
, Natalia Alencar de Pinho
, Johan Ärnlöv
, Clare Arnott
, Samira Bell
, Jarett D. Berry
, Hermann Brenner
, Elizabeth L. Ciemins
, Alexander R Chang
, Mary Cushman
, James A de Lemos
, Juan Miguel Diaz-Tocados
, Alfredo E. Farjat
, Robert A. Fletcher

Ron T. Gansevoort, Hiddo J. L. Heerspink, William G. Herrington, Chuan Hong, Edward J. Horwitz, Shih-Jen Hwang, Simerjot K. Jassal, Philip A. Kalra, Ronit Katz, Sadiya S. Khan, Csaba P Kovesdy, Florian Kronenberg, Jennifer S. Lees, Donald M. Lloyd-Jones, Jose Geraldo Mill, David M. J. Naimark, Chiadi Ndumele, Kevan R. Polkinghorne, Bruce M. Psaty, Patrick Schloemer, Michael G. Shlipak, Prabin Shrestha, Zean Song, Natalie D. Staplin, Dominik Steubl, Priya Vart, Frank L. J. Visseren, Mark Woodward, Kazumasa Yamagishi, Bessie A. Young, Charumathi Sabanayagam, José M. Valdivielso

Population Health and Genomics

Research output: Contribution to journal › Article › peer-review

Abstract

The American Heart Association’s PREVENT equations estimate risk of total cardiovascular disease (CVD), atherosclerotic CVD (ASCVD), and heart failure (HF) to guide lipid and blood pressure-lowering therapy in people ages 30 to 79 years in the United States. The SCORE2 risk algorithm is used to estimate CVD risk for similar purposes in people ages 40 and older in Europe. Neither set of equations has been comprehensively validated in global observational cohorts and randomized trials. Here, in 44 observational cohorts and 18 randomized trials, we assessed discrimination and calibration of the two risk algorithms across geographical regions (North America, Europe, Asia/other, multi-region trials). We also created scaling factors for risk prediction over 1–9 years using the PREVENT equations, enabling shorter-term risk prediction for research purposes or to facilitate clinical trial enrolment. Over 5.1 years of mean follow-up, 293,737 PREVENT total CVD events (fatal and non-fatal ASCVD or HF) and 258,086 SCORE2 CVD events (myocardial infarction, stroke, or cardiovascular death) were observed among 6,422,714 and 5,437,384 individuals, respectively. Despite differences in CVD outcome definitions, target populations and predictor variables, overall discrimination and calibration were similar for both equations, with generally good performance across regions, including in multi-regional randomized trials. These findings lend support for adoption of PREVENT or SCORE2 for cardiovascular risk stratification across diverse settings.

Original language	English
Journal	Nature Medicine
Early online date	5 May 2026
DOIs	https://doi.org/10.1038/s41591-026-04437-z
Publication status	E-pub ahead of print - 5 May 2026

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This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

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10.1038/s41591-026-04437-z

Cite this

Neuen, B. L., Major, R. W., Grams, M. E., Sang, Y., Coresh, J., Ballew, S. H., Surapaneni, A., de Pinho, N. A., Ärnlöv, J., Arnott, C., Bell, S., Berry, J. D., Brenner, H., Ciemins, E. L., Chang, A. R., Cushman, M., de Lemos, J. A., Diaz-Tocados, J. M., Farjat, A. E., ... Valdivielso, J. M. (2026). Multinational validation of the PREVENT and SCORE2 cardiovascular risk equations across 6.4 million individuals. Nature Medicine. Advance online publication. https://doi.org/10.1038/s41591-026-04437-z

@article{d5f23ace178d49c09d9e60d0074c1bb5,

title = "Multinational validation of the PREVENT and SCORE2 cardiovascular risk equations across 6.4 million individuals",

abstract = "The American Heart Association{\textquoteright}s PREVENT equations estimate risk of total cardiovascular disease (CVD), atherosclerotic CVD (ASCVD), and heart failure (HF) to guide lipid and blood pressure-lowering therapy in people ages 30 to 79 years in the United States. The SCORE2 risk algorithm is used to estimate CVD risk for similar purposes in people ages 40 and older in Europe. Neither set of equations has been comprehensively validated in global observational cohorts and randomized trials. Here, in 44 observational cohorts and 18 randomized trials, we assessed discrimination and calibration of the two risk algorithms across geographical regions (North America, Europe, Asia/other, multi-region trials). We also created scaling factors for risk prediction over 1–9 years using the PREVENT equations, enabling shorter-term risk prediction for research purposes or to facilitate clinical trial enrolment. Over 5.1 years of mean follow-up, 293,737 PREVENT total CVD events (fatal and non-fatal ASCVD or HF) and 258,086 SCORE2 CVD events (myocardial infarction, stroke, or cardiovascular death) were observed among 6,422,714 and 5,437,384 individuals, respectively. Despite differences in CVD outcome definitions, target populations and predictor variables, overall discrimination and calibration were similar for both equations, with generally good performance across regions, including in multi-regional randomized trials. These findings lend support for adoption of PREVENT or SCORE2 for cardiovascular risk stratification across diverse settings.",

author = "Neuen, \{Brendon L.\} and Major, \{Rupert W.\} and Grams, \{Morgan E.\} and Yingying Sang and Josef Coresh and Ballew, \{Shoshana H.\} and Aditya Surapaneni and \{de Pinho\}, \{Natalia Alencar\} and Johan {\"A}rnl{\"o}v and Clare Arnott and Samira Bell and Berry, \{Jarett D.\} and Hermann Brenner and Ciemins, \{Elizabeth L.\} and Chang, \{Alexander R\} and Mary Cushman and \{de Lemos\}, \{James A\} and Diaz-Tocados, \{Juan Miguel\} and Farjat, \{Alfredo E.\} and Fletcher, \{Robert A.\} and Gansevoort, \{Ron T.\} and Heerspink, \{Hiddo J. L.\} and Herrington, \{William G.\} and Chuan Hong and Horwitz, \{Edward J.\} and Shih-Jen Hwang and Jassal, \{Simerjot K.\} and Kalra, \{Philip A.\} and Ronit Katz and Khan, \{Sadiya S.\} and Kovesdy, \{Csaba P\} and Florian Kronenberg and Lees, \{Jennifer S.\} and Lloyd-Jones, \{Donald M.\} and Mill, \{Jose Geraldo\} and Naimark, \{David M. J.\} and Chiadi Ndumele and Polkinghorne, \{Kevan R.\} and Psaty, \{Bruce M.\} and Patrick Schloemer and Shlipak, \{Michael G.\} and Prabin Shrestha and Zean Song and Staplin, \{Natalie D.\} and Dominik Steubl and Priya Vart and Visseren, \{Frank L. J.\} and Mark Woodward and Kazumasa Yamagishi and Young, \{Bessie A.\} and Charumathi Sabanayagam and Valdivielso, \{Jos{\'e} M.\}",

year = "2026",

month = may,

day = "5",

doi = "10.1038/s41591-026-04437-z",

language = "English",

journal = "Nature Medicine",

issn = "1078-8956",

publisher = "Nature Research",

}

Neuen, BL, Major, RW, Grams, ME, Sang, Y, Coresh, J, Ballew, SH, Surapaneni, A, de Pinho, NA, Ärnlöv, J, Arnott, C, Bell, S, Berry, JD, Brenner, H, Ciemins, EL, Chang, AR, Cushman, M, de Lemos, JA, Diaz-Tocados, JM, Farjat, AE, Fletcher, RA, Gansevoort, RT, Heerspink, HJL, Herrington, WG, Hong, C, Horwitz, EJ, Hwang, S-J, Jassal, SK, Kalra, PA, Katz, R, Khan, SS, Kovesdy, CP, Kronenberg, F, Lees, JS, Lloyd-Jones, DM, Mill, JG, Naimark, DMJ, Ndumele, C, Polkinghorne, KR, Psaty, BM, Schloemer, P, Shlipak, MG, Shrestha, P, Song, Z, Staplin, ND, Steubl, D, Vart, P, Visseren, FLJ, Woodward, M, Yamagishi, K, Young, BA, Sabanayagam, C & Valdivielso, JM 2026, 'Multinational validation of the PREVENT and SCORE2 cardiovascular risk equations across 6.4 million individuals', Nature Medicine. https://doi.org/10.1038/s41591-026-04437-z

TY - JOUR

T1 - Multinational validation of the PREVENT and SCORE2 cardiovascular risk equations across 6.4 million individuals

AU - Neuen, Brendon L.

AU - Major, Rupert W.

AU - Grams, Morgan E.

AU - Sang, Yingying

AU - Coresh, Josef

AU - Ballew, Shoshana H.

AU - Surapaneni, Aditya

AU - de Pinho, Natalia Alencar

AU - Ärnlöv, Johan

AU - Arnott, Clare

AU - Bell, Samira

AU - Berry, Jarett D.

AU - Brenner, Hermann

AU - Ciemins, Elizabeth L.

AU - Chang, Alexander R

AU - Cushman, Mary

AU - de Lemos, James A

AU - Diaz-Tocados, Juan Miguel

AU - Farjat, Alfredo E.

AU - Fletcher, Robert A.

AU - Gansevoort, Ron T.

AU - Heerspink, Hiddo J. L.

AU - Herrington, William G.

AU - Hong, Chuan

AU - Horwitz, Edward J.

AU - Hwang, Shih-Jen

AU - Jassal, Simerjot K.

AU - Kalra, Philip A.

AU - Katz, Ronit

AU - Khan, Sadiya S.

AU - Kovesdy, Csaba P

AU - Kronenberg, Florian

AU - Lees, Jennifer S.

AU - Lloyd-Jones, Donald M.

AU - Mill, Jose Geraldo

AU - Naimark, David M. J.

AU - Ndumele, Chiadi

AU - Polkinghorne, Kevan R.

AU - Psaty, Bruce M.

AU - Schloemer, Patrick

AU - Shlipak, Michael G.

AU - Shrestha, Prabin

AU - Song, Zean

AU - Staplin, Natalie D.

AU - Steubl, Dominik

AU - Vart, Priya

AU - Visseren, Frank L. J.

AU - Woodward, Mark

AU - Yamagishi, Kazumasa

AU - Young, Bessie A.

AU - Sabanayagam, Charumathi

AU - Valdivielso, José M.

PY - 2026/5/5

Y1 - 2026/5/5

N2 - The American Heart Association’s PREVENT equations estimate risk of total cardiovascular disease (CVD), atherosclerotic CVD (ASCVD), and heart failure (HF) to guide lipid and blood pressure-lowering therapy in people ages 30 to 79 years in the United States. The SCORE2 risk algorithm is used to estimate CVD risk for similar purposes in people ages 40 and older in Europe. Neither set of equations has been comprehensively validated in global observational cohorts and randomized trials. Here, in 44 observational cohorts and 18 randomized trials, we assessed discrimination and calibration of the two risk algorithms across geographical regions (North America, Europe, Asia/other, multi-region trials). We also created scaling factors for risk prediction over 1–9 years using the PREVENT equations, enabling shorter-term risk prediction for research purposes or to facilitate clinical trial enrolment. Over 5.1 years of mean follow-up, 293,737 PREVENT total CVD events (fatal and non-fatal ASCVD or HF) and 258,086 SCORE2 CVD events (myocardial infarction, stroke, or cardiovascular death) were observed among 6,422,714 and 5,437,384 individuals, respectively. Despite differences in CVD outcome definitions, target populations and predictor variables, overall discrimination and calibration were similar for both equations, with generally good performance across regions, including in multi-regional randomized trials. These findings lend support for adoption of PREVENT or SCORE2 for cardiovascular risk stratification across diverse settings.

AB - The American Heart Association’s PREVENT equations estimate risk of total cardiovascular disease (CVD), atherosclerotic CVD (ASCVD), and heart failure (HF) to guide lipid and blood pressure-lowering therapy in people ages 30 to 79 years in the United States. The SCORE2 risk algorithm is used to estimate CVD risk for similar purposes in people ages 40 and older in Europe. Neither set of equations has been comprehensively validated in global observational cohorts and randomized trials. Here, in 44 observational cohorts and 18 randomized trials, we assessed discrimination and calibration of the two risk algorithms across geographical regions (North America, Europe, Asia/other, multi-region trials). We also created scaling factors for risk prediction over 1–9 years using the PREVENT equations, enabling shorter-term risk prediction for research purposes or to facilitate clinical trial enrolment. Over 5.1 years of mean follow-up, 293,737 PREVENT total CVD events (fatal and non-fatal ASCVD or HF) and 258,086 SCORE2 CVD events (myocardial infarction, stroke, or cardiovascular death) were observed among 6,422,714 and 5,437,384 individuals, respectively. Despite differences in CVD outcome definitions, target populations and predictor variables, overall discrimination and calibration were similar for both equations, with generally good performance across regions, including in multi-regional randomized trials. These findings lend support for adoption of PREVENT or SCORE2 for cardiovascular risk stratification across diverse settings.

U2 - 10.1038/s41591-026-04437-z

DO - 10.1038/s41591-026-04437-z

M3 - Article

C2 - 42086979

SN - 1078-8956

JO - Nature Medicine

JF - Nature Medicine

ER -

Multinational validation of the PREVENT and SCORE2 cardiovascular risk equations across 6.4 million individuals

Abstract

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